1

Comparative Analysis Report: 

The Benefits of Using Intelligent Transportation 

Systems in Work Zones 

Report Number FHWA-HOP-09-002 

October 2008 

Notice 

The Federal Highway Administration provides high-quality information to serve Government, industry, and 

the public in a manner that promotes public understanding. Standards and policies are used to ensure and 

maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews 

quality issues and adjusts its programs and processes to ensure continuous quality improvement. 
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Foreword 

This report is part of a series of Federal Highway Administration (FHWA) products that 

examines the use of Intelligent Transportation Systems (ITS) in work zones. This 

document provides a summary of the findings of a national FHWA study to quantify the 

benefits of ITS applications for work zone traffic management. A summary report of this 

study was published in April 2008 (Report No. FHWA-HOP-08-021). Also, a crosscutting study (Report No. FHWA-OP-02-025) and four case studies on the use of ITS in 

work zones were published earlier. 

All of these documents are available at http://www.ops.fhwa.dot.gov/wz/its/index.htm. 

The summary report of this study and the earlier reports were also published in hardcopy. 

To request a hardcopy of the summary report or the earlier reports, please send an email 

with the name of the publication you are requesting, number of copies needed, and 

shipping directions to workzonepubs@dot.gov. More information on applications of ITS 

in work zones is available in other documents, including Intelligent Transportation 

Systems in Work Zones — A Cross-Cutting Study. 

Acknowledgements 

The authors of this report greatly appreciate the time, information, insights, and access 

provided by representatives of the following public agencies: 

• District of Columbia Department of Transportation 

• Texas Department of Transportation 

• Michigan Department of Transportation 

• Arkansas State Highway and Transportation Department 

• North Carolina Department of Transportation. 

The authors also greatly appreciate the cooperation and assistance with data collection 

and archiving as provided by the following vendors: 

• ASTI Transportation Systems Incorporated 

• Give 'Em A Break Safety 

• International Road Dynamics 

• Protection Services Incorporated 

• Scientex Corporation 

• United Rentals Highway Technologies.
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Table of Contents 

Executive Summary............................................................................................................ 7 

Introduction......................................................................................................................... 9 

Purpose............................................................................................................................ 9 

Site Selection - Process and Criteria............................................................................... 9 

Timing of the Evaluations............................................................................................. 11 

Common Measures and Metrics for Work Zone ITS Evaluations ................................... 12 

Mobility......................................................................................................................... 12 

Safety ............................................................................................................................ 12 

Effectiveness of Work Zone Information Dissemination ............................................. 13 

System Performance ..................................................................................................... 13 

DC-295 Washington, DC.................................................................................................. 15 

Study Site Work Zone................................................................................................... 16 

ITS Description............................................................................................................. 16 

Measures and Metrics ................................................................................................... 17 

Findings......................................................................................................................... 17 

Tips and Lessons Learned............................................................................................. 25 

I-35 Hillsboro, Texas ........................................................................................................ 27

Study Site Work Zone................................................................................................... 28 

ITS Description............................................................................................................. 29 

Measures and Metrics ................................................................................................... 30 

Findings......................................................................................................................... 32 

Tips and Lessons Learned............................................................................................. 41 

US-131 Kalamazoo, Michigan.......................................................................................... 42 

Study Site Work Zone................................................................................................... 43 

ITS Description............................................................................................................. 44 

Measures and Metrics ................................................................................................... 45 

Findings......................................................................................................................... 46 

Tips and Lessons Learned............................................................................................. 51 

I-30 Little Rock to Benton, Arkansas ............................................................................... 52 

Study Site Work Zone................................................................................................... 52 

Measures and Metrics ................................................................................................... 56 

Findings......................................................................................................................... 57 

Summary of Findings - Arkansas ................................................................................. 74 

Tips and Lessons Learned............................................................................................. 76 

I-40 Winston - Salem, North Carolina.............................................................................. 78 

Study Site Work Zone................................................................................................... 79 

ITS Description............................................................................................................. 79 

Measures and Metrics ................................................................................................... 81 

Findings......................................................................................................................... 82 

Tips and Lessons Learned............................................................................................. 88 

Overall Findings................................................................................................................ 91 

Findings on Key Measures Across Sites....................................................................... 91 

Cross-Cutting Tips and Lessons Learned ..................................................................... 93 

Comparisons with Results of Other Studies ..................................................................... 96 

Enforceable Merge Systems ......................................................................................... 96 
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Traffic Information Systems......................................................................................... 97 

Additional Comparative Data ....................................................................................... 98 

Suggested Future Work..................................................................................................... 99 

List of Figures 

Figure 1. DC-295 Work Zone Area and ITS Layout........................................................ 15 

Figure 2. Average Speed by Time of Day – April 13, 2007............................................. 21 

Figure 3. Volume Levels by Time of Day ........................................................................ 22 

Figure 4. Volume Levels by Time of Day ........................................................................ 23 

Figure 5. I-35 Work Zone and Signed Alternate Routes (Taken from TXDOT’s Website)

........................................................................................................................................... 27 

Figure 6. Modified Corridor Map Showing Data Collection Sensor Locations............... 31 

Figure 7. Volume Patterns (Q3: 35E SB) – October 12th Lane Closure (without ITS)... 35 

Figure 8. Occupancy Values (System Q4: 35E SB) – October 12th lane closure (without 

ITS) ................................................................................................................................... 36 

Figure 9. Occupancy Values (System Q1: I-35 NB) – November 26 Incident (With ITS)

........................................................................................................................................... 37 

Figure 10. Volumes (Q2: I-35 NB) – November 26 Incident (With ITS) ....................... 38 

Figure 11. 2003 Peak Hour Volume Counts on US-131 .................................................. 43 

Figure 12. DLM Layout Along Northbound US-131 ....................................................... 45 

Figure 13. DLM System Setup ......................................................................................... 46 

Figure 14. Dangerous Merge Maneuvers by Approach.................................................... 48 

Figure 15. Daily Traffic Counts by Approach and Detection System.............................. 51 

Figure 17. Overview of I-30, Little Rock to Benton, Arkansas Work Zone .................... 55 

Figure 18. Distribution of Driver’s Opinions on the Statement “DMS Makes Drivers Feel 

Safer in the Construction Zone” (Private & CVDs) ......................................................... 59 

Figure 19. Distribution of Sources Used to Get Information about Traffic Conditions on 

I-30.................................................................................................................................... 61 

Figure 20. Activity in Work Zone Webpage Servers (8/16/2005 was a Tuesday)........... 62 

Figure 21. Distribution of Responses to the Statement, “Just Having The DMS 

Information Makes Me Feel Less Bothered By The Delays In The Construction Zone.” 65 

Figure 22. Distribution Of Responses To The Statement, “Just Having The Website 

Information Makes Me Feel Less Bothered By The Delays In The Construction Zone.” 65 

Figure 23. Location of Ramps Used for Hypothesis No. 9............................................... 68 

Figure 24. Locations of Detectors Used for Hypothesis 11.............................................. 71 

Figure 25. I-40 Work Zone and Signed Alternate Routes ................................................ 78 

Figure 26. I-40 Smart Work Zone Deployment Near Winston Salem ............................. 80 

Figure 27. Daily Volume Totals Reported by System Detector #9 .................................. 85 
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List of Tables 

Table 1. Hypotheses and Measures for Evaluation........................................................... 17 

Table 2. Construction and Lane Closure Information ...................................................... 18 

Table 3. Construction and Lane Closure Information ...................................................... 19 

Table 4. Percent Change in Volume by Time Period ...................................................... 22 

Table 5. Example Queue Thresholds - 35W Southbound................................................. 29 

Table 6. Key Hypothesis, Measures, and Data Sources for Evaluation ........................... 32 

Table 7. Construction and Lane Closure Information (October 2006)............................ 33 

Table 8. Construction and Lane Closure Information (November-December 2006) ....... 33 

Table 9. Diversion Rates for November 23rd Incident Compared with Other Thursdays in 

November.......................................................................................................................... 39 

Table 10. Diversion Rates for November 26th Incident Compared with Other Sundays in 

November.......................................................................................................................... 39 

Table 11. Measures and Metrics for the Michigan DLM deployment ............................ 45 

Table 12. Aggregate Aggressive Driving Observation Classifications by Date 

(Northbound)..................................................................................................................... 47 

Table 13. Aggregate Aggressive Driving Observation Classifications by Date 

(Southbound)..................................................................................................................... 47 

Table 14. Statistics for 2 Days Flashers Were On and 6 Days They Were Off................ 49 

Table 15. Location of DMS Used for Hypothesis No. 9 .................................................. 69 

Table 16. Summary Findings for Each Hypothesis .......................................................... 74 

Table 17. Hypotheses and Measures for Evaluation......................................................... 81 

Table 18. Construction and Lane Closure Information (without ITS).............................. 83 

Table 19. Construction and Lane Closure Information (with ITS)................................... 84 

Table 20. Average Speed Values Reported As "240"....................................................... 86 

Table 21. Comparison of Key Measures by Site .............................................................. 92 

Table 22. Drivers’ Agreement with the Statement That DMSs Better Prepare Them To 

React to Stopped or Slow Traffic.................................................................................... 113 

Table 23. Driver’s Agreement with the Statement That DMS Makes Them Feel Safer 113 

Table 24. Drivers Agree The Web Site Improved Trip Planning................................... 114 

Table 25. Drivers Agree DMS Contain Enough Detail .................................................. 114 

Table 26. Drivers Agree DMS Are Located in the Right Places.................................... 114 

Table 27. Drivers Agree HAR Messages are Detailed Enough to Help Them Make 

Decisions......................................................................................................................... 115 

Table 28. Driver Response to Statement that DMS are Easy to Understand.................. 115 

Table 29. Driver Response to the Statement that DMS are Detailed Enough to Help Me 

Make Decisions............................................................................................................... 116 

Table 30. Drivers Response to Statement that HAR Broadcast Quality is Too Poor to 

Hear................................................................................................................................. 116 

Table 31. Drivers’ Response to Statement that HAR Messages are Detailed Enough to 

Help Make Decisions...................................................................................................... 117 

Table 32. Drivers Agree the Information on the Web Site is Accurate.......................... 117 

Table 33. Drivers Find the DMS Messages To Be Accurate.......................................... 118 

Table 34. Drivers Find HAR Messages To Be Useful................................................... 118 

Table 35. Drivers Find HAR Messages to Be Accurate ................................................ 118 

Table 36. Drivers Find HAR Messages To Be Updated Frequently Enough................. 119 
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Table 37. Combined Volume From The ITS Detectors (62 and 26) Was Significantly 

Higher Than The AHTD Tube Data ............................................................................... 119 

Table 38. Combined Volume From The ITS Detectors (63 and 25) Was Not Different 

Than The AHTD Tube Data ........................................................................................... 120 
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Executive Summary 

This report presents the results of a Federal Highway Administration study that examined 

the use of Intelligent Transportation Systems (ITS) for work zone traffic management. 

Congestion and safety issues often arise in and around work zones as agencies work to 

implement necessary construction and maintenance projects. Degraded facilities, 

narrowed lanes, and lane restrictions often result in unpredictable, unstable traffic flow. 

With recent efforts that focus on improving work zone operations, including the recently 

implemented Work Zone Safety and Mobility Rule, State Departments of Transportation 

(DOTs) are looking to tools and applications that can help improve mobility and safety 

by actively managing traffic through the work zone. ITS applications are one tool that 

agencies can use to mitigate traffic impacts caused by construction. 

A number of states have used ITS for work zone traffic management. These systems 

often take the form of mobile, portable traffic monitoring and management to provide 

information to motorists to help with route choice, provide advance warning of slowed or 

stopped traffic, and ease overall frustration due to not knowing what to expect. To 

promote further use of ITS technology to monitor and manage traffic through the work 

zone, more information is needed on the quantified benefits of use and the lessons 

learned by agencies that have tested and implemented these systems. 

The purpose of this study is to highlight “before and after” or “with and without” 

analyses that quantify the mobility and safety benefits of using ITS applications for work 

zone traffic management. The study focused on sites that provided an opportunity for 

comparison of traffic conditions both with and without ITS. The study team focused on 

sites with the best potential for adequate data prior to system deployment (and with 

impacts from construction) for comparison with traffic conditions during system 

deployment. Five sites were assessed for this study. This study also examined findings 

from other work zone ITS research as compared with the findings presented from the five 

study sites. 

The study team analyzed data from sites in the District of Columbia, Texas, Michigan, 

Arkansas, and North Carolina. For some of the sites, it was difficult to determine 

quantifiable benefits due to issues with deployment schedules and difficulties in 

implementing data collection plans due to varying construction schedules. Other sites 

showed clear, quantified benefits. Some key lessons learned that can help deploying 

agencies are presented for all sites. Additionally, quantitative benefits information is 

included for several sites, such as: 

• Reductions in aggressive maneuvers at work zone lane drops (Michigan) – Forced 

merges were seven times less frequent and dangerous merges were three times less 

frequent when the ITS system was on (flashers on). 

• Significant traffic diversion rates and lower observed mainline volumes (Texas, 

District of Columbia) in response to appropriate messages displayed during congested 

conditions, and an enhanced ability to manage traffic and incidents during 
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construction. In Texas, an average of 10 percent diversion (range of 1 to 28 percent) 

was observed, while in the District of Columbia an average of 52 percent (range of 3 

to 90 percent) lower mainline volume (combination of diversion, demand reduction, 

and congestion) was observed. 

• Improved ability to react to stopped or slow traffic (Arkansas) – 82 percent of 

surveyed drivers felt that the ITS system improved their ability to react to stopped or 

slow traffic. 

• Driver perception of improved work zone safety (Arkansas) – 49 percent of surveyed 

drivers indicated that that the ITS electronic messages made them feel safer, 17 

percent were neutral, 32 percent disagreed, and 2 percent did not answer. 
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Introduction 

Purpose 

In 2003, the Federal Highway Administration (FHWA) developed plans for a study to 

quantify the benefits of deploying Intelligent Transportation Systems (ITS) for mitigating 

impacts caused by highway construction and maintenance. The Work Zone Mobility and 

Delay Reporting Assessment began in August 2003 to document the tangible benefits of 

work zone ITS in a quantitative way. This study was intended to increase the body of 

knowledge regarding the effects of deploying work zone ITS so that practitioners have 

additional information to draw from in designing and deploying ITS in work zones. 

In the recent past, some owner-agencies across the nation have deployed portable ITS 

technologies to monitor traffic and manage mobility and safety during construction. 

Portable systems provide a solution for deployment, maintenance, operation, and 

remobilization of monitoring systems, especially since the roadway characteristics often 

change dramatically during construction. Most of these systems take the form of mobile 

traffic monitoring and management through the use of portable sensors to collect traffic 

data and integrated portable changeable message signs (PCMS) to display speed and/or 

delay information in real-time. Agencies also often integrate a Web site into the overall 

system to provide motorists with pre-trip information to allow for better trip planning. A 

few agencies have also used portable ITS to help manage merging behavior approaching 

work zone lane closures. 

Site Selection - Process and Criteria 

To supplement a list of potential sites developed by FHWA, the study team performed 

research to learn about additional sites across the country. Out of over 30 initial sites, the 

study team eliminated more than 20 because they were not specifically work zone 

systems or because the deployments were already underway (which meant that there was 

little or no chance for comparison “without” data). The study team then developed a 

master site list and a technical memorandum that highlighted information on the sites that 

provided the best opportunity to quantify the benefits of using technology to mitigate the 

mobility, safety, and delay impacts caused by highway work zones. 

The study team held conversations with deploying agency representatives to discuss the 

main goals and objectives of each system deployment, the schedule for construction, the 

status of system deployment, and estimated capacity reduction and construction impacts 

to traffic. The study team then applied primary and secondary site assessment criteria, as 

shown below, to the potential sites to determine which deployments would provide the 

best opportunity to measure impacts in and around the work zone. Some of the sites on 

this narrowed list of 10 potential sites did not appear to provide an opportunity for a 

quantitative evaluation. Other sites/systems had a design and concept of operations that 

would likely have proven very difficult to evaluate given cost constraints. The study 

team applied the criteria to help narrow the list and choose five sites to study. 
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Primary site selection criteria included: 

• Availability of archived data and the infrastructure for data collection. 

• Anticipated availability of “before” data (before the work zone). 

• Anticipated availability of “without” data (work zone without ITS applications). 

• Deployment probability. 

• Status of ITS system deployment schedule. 

• Existing relationships with either the vendor or the deploying agency that would 

facilitate a cooperative effort. 

• Anticipated availability of data from other evaluations at the site. 

• Location type (rural, urban, downtown). 

• Typical volume/capacity or level of congestion. 

• Percentage of local traffic versus through traffic, percent trucks, percent commuter 

traffic. 

• Roadway type and number of lanes. 

• Construction schedule. 

• The State’s ability to articulate specific goals and objectives for what it hoped to 

accomplish by using the system. 

• Primary purpose or goal for using the system (safety versus mobility). 

• Type of system being implemented. 

• Type of traveler information to be provided by the system. 

Secondary site selection criteria included: 

• Existence of a traffic management center for support/data. 

• Size of construction project. 

• Contractor’s ability to change schedule for increased productivity. 

• State’s experience with the use of ITS in work zones. 

• Geographic location. 

• System vendor. 

Where appropriate, a rating of “high,” “medium,” or “low” was applied to each site for 

each criterion. For classification-based criteria such as location type, each site was 

classified based on its characteristics. Once this step was completed, the study team 

further eliminated sites based on these primary and secondary criteria, to remove those 

sites that may not be appropriate for inclusion in this project. 

Based on discussions with local contacts and a preliminary assessment, the study team 

selected two sites, one in Arkansas’ and one in North Carolina, early on in the process. 

For the other sites, the study team continued to use the assessment criteria to develop 

summary pros and cons and made recommendations based on this information. The 

study team also ranked the narrowed list of sites based on which sites illustrated the 

greatest opportunity to see quantified benefits. 
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Based on this process, the study team chose two additional sites—one in Texas and one 

in Michigan. The recommended sites are those where construction showed significant 

potential to have a measurable impact on traffic conditions, creating a situation where 

ITS could be used to reduce this impact. The study team chose the fifth site in the 

District of Columbia because the study team and local agency representatives expected 

significant construction impacts, especially due to the urban setting and high demand for 

the network. 

Timing of the Evaluations 

Planning for the evaluations often required long lead time ahead of data collection and 

analysis. For each site, the study team spent several months gathering and documenting 

information from stakeholders for use in developing the evaluation plans. The study 

team began by contacting stakeholders to determine system status, plans, goals and 

objectives, and progress on the deployment, followed by evaluation planning, data 

collection and analysis, and reporting. While the time for each site evaluation varied in 

length, the following bullets highlight the timeframe in which the study team performed 

data collection and analysis for each site. 

• Arkansas – Spring/Summer 2004. 

• North Carolina – Summer 2004. 

• Michigan – Fall 2004. 

• Texas – Summer 2006. 

• Washington, DC – Summer 2007. 

The original length of the overall study was less than 1 year. However, due to several 

issues, the overall study spanned a period of several years. The issues that hindered the 

evaluation included the initial difficulty in finding sites that met the selection criteria 

(e.g., there was an absence of clear goals and objectives for some systems from which 

measures could be developed), construction delays, and ITS deployment delays. 
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Common Measures and Metrics for Work Zone ITS 

Evaluations 

The initial project plan for this study included a long list of potential measures and 

metrics for use at each site. Early evaluations included several metrics, but some proved 

difficult to quantify due to issues such as limited or incomplete data and difficulties 

determining whether the metric was positively influenced by the ITS deployment. Latter 

site evaluations included a smaller set of the most promising metrics. For example, rate 

of diversion was the primary metric for the Texas site, where the main objective of using 

the system was to divert traffic around the work zone during congested periods. 

The study team sought to quantify benefits at a number of sites for comparative results. 

The study team designed this approach to avoid drawing conclusions from one site or one 

system. This approach limited the resources that went toward any one site but allowed 

the study team to focus on the most logical metrics that directly related to the goals and 

objectives for the deployment. The study team focused most resources per site on the 

primary goals and objectives. 

The following paragraphs outline common measures and metrics and their application 

across some of the sites. 

Mobility

Deploying agencies cited improved mobility as a main goal for the ITS deployment at 

each site. Within mobility, more specific measures included delay, travel time, and 

reduced demand. However, many of the systems had limited detector coverage and none 

of the deployments had enhanced travel time data such as through license plate 

recognition technology. While improved mobility was a key goal cited at all of the sites, 

system design and layout often made it difficult to specifically measure. 

For the Arkansas site, the study team measured mobility impacts through user surveys. 

For the Texas and DC sites, the study team measured improvements in mobility by 

collecting data on diversion rates that would reduce demand on the mainline and thereby 

improve mainline mobility. One limitation of this approach involved data collection on 

the alternate routes, in that it was too costly to collect alternate route data and difficult to 

design data collection plans since it was impossible to know in advance when the traffic 

conditions would trigger the systems to recommend alternate routes. 

Safety

Agencies also cited safety benefits as a main goal for several of the deployments, 

although agencies were reluctant to cite specific safety measures such as reduced crash 

rates when referring to goals and objectives for the system. Additionally, it is very 

difficult to draw conclusive findings from safety performance measures such as number 

of crashes and crash rates since data quality and quantity are often limited, and 

researchers face a significant challenge in determining whether a crash was specifically 
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caused by the work zone (i.e., whether or not it would have still happened had the work 

zone not been in place). 

For the Michigan site, the main objective was to reduce aggressive maneuvers at the lane 

drop. Therefore, safety was a primary metric, and the study team quantified the reduction 

in observed aggressive maneuvers and forced merges as a surrogate measure for safety 

performance. At the early sites, the study team investigated crash analysis but it was 

difficult to draw a meaningful conclusion due to the limited timeframe for collecting data 

and the several month long lags in reporting crash data. Crash and crash rate analyses did 

not produce significant findings at the sites due to common reporting issues and the need 

for long periods of time during which to collect data. 

Effectiveness of Work Zone Information Dissemination

The objective of ITS can often be to provide real-time information on work zone 

conditions in the field. Deploying agencies often take this idea one step further and 

develop a plan for ensuring the information was not only real-time but was also useful to 

motorists in helping them plan their trip. For example, posting “work zone ahead expect 

delays” is not as specific as “30 minute delays ahead.” The more specific the message, 

the better motorists can make information decisions about which route to take. 

At the Arkansas site, the study team used two metrics to determine the effectiveness of 

the system. These metrics included “Travelers will use the work zone ITS” and “The use 

of ITS in the work zone will improve trip planning.” While the main focus of this study 

was to quantify the benefits of each system, the study team analyzed the effectiveness of 

the information where practical. For the DC and Texas sites, travelers avoided mainline 

congestion but may have experienced some congestion in some cases on the alternate 

routes. 

System Performance 

This metric is less about quantifying the benefits of a system, and more about evaluating 

how well a system performed in the field. Data analysis at each site proved useful in 

helping the study team determine how well the system performed. Additionally, error 

logs and missing data often gave indications of the overall performance. System 

algorithms are often proprietary, making it challenging to determine with confidence how 

well the system performed based on its design. 

Other metrics such as productivity, worker exposure to hazards, and construction 

efficiency proved more difficult to measure and were not analyzed at most sites (except 

Arkansas) due to burdensome data collection needs and challenges with determining the 

specific cause of a benefit. Additionally, the systems may have indirectly affected 

measures such as productivity because measuring the direct, quantified impact proved 

difficult. The other work zone ITS studies analyzed as part of this project focused mainly 

on direct traffic impacts. For the Arkansas site, the study team evaluated user 

perspectives on system performance, functionality, and benefits to motorists. 
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The following sections highlight in detail the measures and metrics analyzed at each site, 

along with the results of each site evaluation. The sites are presented in reverse 

chronological order with the most recent site first. 
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DC-295 Washington, DC 

In 2006, the District of Columbia Department of Transportation (DDOT) deployed an 

ITS system on Highway 295 in Washington, DC. The system covers an approximately 7 

mile stretch of DC-295, with some components on adjacent routes. DDOT designed and 

procured the system to help alleviate congestion and provide real-time information to 

motorists in the field and via a Web site. DDOT’s main goals for the ITS system were to 

monitor conditions and improve mobility and safety through the work zone. The location 

and system layout are shown in Figure 1. 

 

Figure 1. DC-295 Work Zone Area and ITS Layout 

Construction Area 
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Based on predetermined delay and speed thresholds, the system provided real-time delay 

and speed information and, as needed, recommended alternate routes via dynamic 

message signs (DMS) for high congestion periods. The main goal of the system was to 

monitor conditions and manage traffic during lane closures due to their potential to 

produce abnormally large traffic backups and create potential for crashes outside the 

work zone. 

The main objectives of the system were to: 

 Reduce work zone-related congestion through a heavily traveled urban corridor. 

 Provide delay and speed information to warn motorists of slowed traffic ahead. 

 Provide information to commuters and DOT personnel via a Web site. 

 Build public confidence in real-time traveler information. 

The main objective of this evaluation was to determine the effect of the system on traffic 

conditions and quantify the benefits of the system. 

Study Site Work Zone 

DDOT incorporated a special provision for the Real-Time Work Zone System (RTWS) 

for both the northbound and southbound directions of Kenilworth Avenue (DC-295) from 

Foote Street to Lane Place Bridge over Nannie Helen Burroughs Avenue, in Northeast 

Washington DC. 

Kenilworth Avenue is a barrier separated, six-lane freeway and serves as a major 

highway link between other major routes within the District, including I-395, and the 

Baltimore-Washington Parkway. DC-295 is a heavily traveled commuter route, carrying 

over 100,000 vehicles daily between Maryland and Washington, DC. 

DDOT issued the Notice to Proceed for construction on April 2, 2007. The project 

consisted of the widening of Kenilworth Avenue to include improved shoulders and the 

realignment of the Nannie Helen Burroughs Avenue intersection with Kenilworth Terrace 

and Kenilworth Avenue on and off ramps. Improvements were also made to the 

intersections of Lane Place, 42nd Street, Jay Street, and Hayes Street with the collectordistributor road of Southbound Kenilworth Avenue. The Kenilworth Avenue bridge 

section over Nannie Helen Burroughs Avenue was replaced by a new two-span steel 

multi-girder superstructure. Several other bridges were reconstructed utilizing steel 

multi-beam superstructures and widened to provide semi-integral abutments. Other work 

included installation of traffic signals, lighting, and signing. 

ITS Description 

DDOT designed the ITS system to monitor traffic conditions within and in advance of the 

work area from each direction. The system components included: 

• A central base station equipped with processing software and wireless 

communications to link the system components.
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• 13 portable DMS remotely controlled via the field station.

• 8 portable speed sensors.

• 2 portable Remote Traffic Microwave Sensors (RTMS).

• 3 pages to provide notification to designated personnel when congested 

conditions occur or when devices malfunction.

• 2 video cameras to provide live video feeds of the work zone area.

DDOT moved some of the components and added several new components to allow the 

system to account for an additional ongoing Maryland DOT construction project. 

Measures and Metrics 

The system vendor collected and archived traffic data from November 1, 2006, through 

August 15, 2007, resulting in more than 1 million data records. Since the system 

detectors covered a large area, the data collection plan for this site relied solely on system 

detector data for analysis. The data archives allowed the study team to establish a 

baseline prior to ITS implementation (without ITS) for comparison with the period when 

the system was active (with ITS). 

The study team developed a database tool to catalogue and display data from the nearly 1 

million records provided by the system vendor. Due to its limited use in comparison of 

construction-related traffic patterns, baseline data collected prior to the construction start 

date of April 2, 2007, was used as back up information. The system was turned on to 

traffic on April 13, 2007. Data for 11 days prior to system start were available for 

comparison with data archived between April 14, 2007 and August 15, 2007 (when the 

ITS was actively deployed). 

The study team developed two key hypotheses based on the goals for the system. The 

hypotheses and associated measures and data sources for testing each are shown in Table 

1 below. 

Table 1. Hypotheses and Measures for Evaluation 

Hypothesis Measures of Effectiveness Data Sources 

The use of ITS in work zones 

will divert travelers to 

alternate routes during times 

of work zone congestion 

Demand patterns on mainline 

and alternate routes 

Sensor data 

The use of ITS in work zones 

will reduce congestion 

Demand patterns on mainline 

and alternate routes, queue 

lengths 

Direct observations, 

sensor data 

Findings 

The archived data for this site showed some general trends, especially in the level of 

recurring congestion for this area. The study team observed the distinct commute pattern 

into the District in the morning (southbound) and out of the District in the afternoon 

(northbound) from the data. DDOT anticipated that adding in capacity restrictions from 
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the work zone would add non-recurring congestion to this daily pattern. Therefore, the 

system covered the corridor along a stretch of approximately 10 miles. 

The data suggests higher levels of recurring congestion for the area than non-recurring 

congestion caused by the work zone. This may be in part due to the early phases of work 

– construction is scheduled to continue into 2008, and additional activities in the future 

may impact traffic to a greater extent than observed within the timeframe of this study. 

However, several findings indicate positive benefits of the system during the 2007 

construction season. 

Construction Activity Information 

To assess the level of impact from construction activities, the study team obtained 

construction log information and capacity reduction information from the DDOT 

construction management consultant. Construction inspectors and field engineers 

recorded information in activity logs for each day that work occurred as shown in Tables 

2 and 3. Time periods of interest included those in which lane closures were in place and 

those in which incidents occurred. The recorders made notes on incidents within the 

work zone and at the approaches, maximum queue lengths, and specific activities that 

occurred. The study team parsed applicable notes for the days of interest during the 

periods both “without ITS” and “with ITS.” While crashes likely occurred along the 

corridor during construction, the DDOT construction management consultant cited no 

documented work zone-related crashes during the data collection time period. 

Table 2. Construction and Lane Closure Information 

Date 

Time of Day 

(Beginning) 

Time of 

Day 

(End) 

Crashes

Observed

Maximum 

Observed 

Queue 

Length Activity Notes 

4/5/2007 10:00 AM 3:30 PM -- 1200 feet Closed northbound outside lane on 

Kenilworth Avenue (clear and grub) 

4/6/2007 10:00 AM 2:00 PM -- 200 feet Closed lane on northwest service 

road (clear and grub) 

4/9/2007 10:00 AM 3:30 PM -- 200 feet Closed southbound lane near bridge 

48 for deck demolition 

4/10/2007 10:00 AM 3:30 PM -- 200 feet Closed southbound lane near bridge 

48 for deck demolition 

4/10/2007 10:00 AM 3:30 PM -- 200 feet Phase 1 – early maintenance of 

traffic plan implementation 

4/11/2007 10:00 AM 3:30 PM -- 200 feet Closed southbound lane near bridge 

48 for deck demolition 

4/12/2007 10:00 AM 3:30 PM -- 1200 feet Closed lane on southbound 

Kenilworth Avenue (demolition) 

All lane closures occurred during off-peak hours. Of the “without ITS” days where lane 

closures were in place, the data for the southbound direction showed recurring congestion 
19

trends from approximately 7:00 a.m. until approximately 10:00 a.m. Data for one day 

showed recurring congestion from approximately 3 p.m. until approximately 6 p.m. 

Table 3. Construction and Lane Closure Information 

Date

Time of Day 

(Beginning)

Time of Day

(End)

Crashes 

Observed

Maximum 

Observed 

Queue 

Length Activity Notes

4/13/2007 10:00 AM 3:30 PM -- 1200 feet Closed southbound lane for MOT 

Pavement Marking 

4/14/2007 10:00 AM 3:30 PM -- 200 feet Closed southbound lane for 

Phase I – Early MOT 

4/16/2007 10:00 AM 3:00 PM -- 1200 feet Closed southbound lane to place 

portable concrete barrier 

4/17/2007 10:00 AM 3:00 PM -- 200 feet Closed southbound lane to place 

portable concrete barrier 

4/18/2007 10:00 AM 3:30 PM -- 200 feet 

Closed southbound lane for 

pavement marking and to place 

portable concrete barrier 

4/19/2007 10:00 AM 3:30 PM -- 1200 feet Closed northbound lane for 

Phase I – MOT 

4/20/2007 10:00 AM 3:30 PM -- 1200 feet Closed northbound lane for 

Phase I – MOT 

4/24/2007 10:00 AM 3:30 PM -- 1200 feet Closed southbound lane to install 

storm water catch basin 

4/25/2007 10:00 AM 3:30 PM -- 1200 feet Closed southbound lane to install 

storm water catch basin 

4/28/2007 10:00 AM 3:00 PM -- 1200 feet Closed southbound lane for MOT 

pavement marking 

5/14/2007 10:00 AM 2:00 PM -- 1200 feet Closed southbound lane for MOT 

pavement marking 

5/15/2007 10:00 AM 3:30 PM -- 1200 feet Closed southbound lane for MOT 

pavement marking 

5/16/2007 10:00 AM 3:30 PM -- 1200 feet Closed southbound lane to place 

portable concrete barrier 

5/17/2007 10:00 AM 3:00 PM -- 1200 feet Closed southbound lane to place 

portable concrete barrier 

5/18/2007 10:00 AM 3:30 PM -- 1200 feet Closed southbound lane to place 

portable concrete barrier 

6/2/2007 4:00 AM 2:00 PM -- 1200 feet Closed northbound lane for MOT 

pavement marking 

6/4/2007 10:00 AM 3:30 PM -- 1200 feet Closed northbound lane for MOT 

pavement marking 

6/5/2007 10:00 AM 3:30 PM -- 1200 feet Closed northbound lane to place 
20

Date

Time of Day 

(Beginning)

Time of Day

(End)

Crashes 

Observed

Maximum 

Observed 

Queue 

Length Activity Notes

portable concrete barrier 

6/7/2007-

6/14/2007 10:00 AM 3:30 PM -- 1200 feet 

Closed northbound and 

southbound lanes to demolish 

median (daily) 

6/18/2007-

6/30/2007 10:00 AM 3:30 PM -- 1200 feet 

Closed northbound and 

southbound lanes to demolish 

median (daily) 

Project managers documented similar information for July and August to assist with the 

analysis. In some cases, the data showed queues that were longer than those documented 

by project personnel (likely recurring queues not caused by the work zone directly). In 

other cases, sensor data did not show any congestion on some of the days where project 

managers documented some work zone related queuing. Consequently, documented 

queues were relatively short and non-recurring congestion appeared to be managed to a 

minimum extent as part of the maintenance of traffic plans (i.e. off-peak lane closures, 

etc.). 

Traffic Queue Analysis 

The study team began the analysis by sorting traffic data from system detectors for 

preliminary inspection to determine the potential for use in the analysis. The archived 

traffic data consisted of more than 1 million records covering a time period from 

November 2006 through August 2007. The data set was very complete and inspection 

showed reasonable patterns of traffic volumes, speeds, and associated DMS messages. 

Data were not available for a small number of days and other short time periods due to 

communication interrupts and archiving issues. 

The study team performed an analysis to compare queues documented by construction 

managers with those observed by the system. Since the system covered a large area with 

multiple detector locations (this site had a very large number of detectors compared with 

most of the other sites), the potential for determining queues was high. Documented 

queues extended to a maximum of approximately 1/4 of a mile, while queues from 

system detector data reached nearly 2 miles in some instances. The study team calculated 

queues using detector spacing for time periods where speeds dropped below 30 miles per 

hour (mph). Figure 2 shows average southbound speed by time of day for April 13, 

2007, the first day the DMSs were turned on to traffic. The resulting queue was 

approximately 1 mile compared with the 1/4 mile estimate. The longer queue length 

could be caused by recurring congestion or an incident outside of the work zone area. 

Due to the large difference between estimated and observed queue lengths on nearly all 

of the data collection days, the analysis of queues before and after implementation proved 

inconclusive. The wide gap between observed queue and system detected queue may 

have been caused by the determination of what constitutes a queue. The 30 mph 

threshold is common for a rolling queue and is easier to determine from data as opposed 
21

to field observations, but the sensitivity to observed speed may differ due to the level of 

recurring congestion normally seen in urban areas such as Washington, DC. 

0

10

20

30

40

50

60

70

12 AM 3 AM 6 AM 8 AM 11 AM 1 PM 4 PM 6 PM 9 PM

Time of Day

Speed (mph)

Sensor 19 Sensor 18 Sensor 17 Sensor 16 RTMS 21

Figure 2. Average Speed by Time of Day – April 13, 2007 

Based on the data shown in Figure 2, the system posted messages showing 55 to 60 

minute delays on DC-295 and recommended, on DMSs located on a perpendicular route, 

that motorists seek an alternate to DC-295. 

Traffic Volumes and Diversion Patterns 

The study team also analyzed volume levels for days with and without ITS that 

experienced similar impacts from construction or had similar levels of congestion. Since 

most “without ITS” days showed mostly recurring congestion during peak hours and 

showed no congestion during lane closure time periods, the study team compared some of 

the “without ITS” days to “with ITS” days to see if the volumes changed when messages 

recommended alternate routes. The study team also compared some days within the 

“with ITS” period to see if volume levels showed interesting trends. 

For two similar Tuesdays (April 10 and May 15), the volume levels were almost exactly 

the same except from approximately 10 a.m. until 1 p.m., a time period where the system 

posted delay information and recommended that motorists seek an alternate route to 

southbound DC-295 (see Figure 3). During this time period, as much as a nearly 90 

percent less volume was observed on May 15 compared with April 15. As shown in 

Table 4, the data showed 3 to 89 percent lower observed mainline volumes, with an 

average of 52 percent over these nine observations. This shows that the system likely 

reduced delay substantially for motorists by providing them with information to better 

enable them to choose an alternate route. It should be noted that based on the data 

available, it is not possible to determine what portion of the lower mainline volume was 

due to diversion versus demand reduction versus congestion. 
22

0

500

1000

1500

2000

2500

0:00 4:00 08:00 12:00 16:00

Time of Day

30 Minute Volumes

10-Apr-07

15-May-07

Figure 3. Volume Levels by Time of Day 

Table 4. Percent Change in Volume by Time Period 

Time Period Observed 

Volumes for 

April 10, 2007 

Observed 

Volumes for 

May 15, 2007 

Difference Percentage 

Difference 

10am – 10:30am 912 435 477 52% 

10:30am – 11am 723 151 572 79% 

11am – 11:30am 886 168 718 81% 

12pm – 12:30pm 890 98 792 89% 

12:30pm – 1pm 831 148 683 82% 

1pm – 1:30pm 679 452 227 33% 

1:30pm – 2pm 862 742 120 14% 

2:30pm – 3pm 908 574 334 37% 

3:30pm – 4pm 921 890 31 3% 

During periods of congestion, volume counts are impacted because queuing and 

congestion allow fewer vehicles to cross in front of the sensor due to lower speeds. An 

exact measure of demand involves estimating the number of vehicles in the queue—these 

vehicle estimates should be added to the volume counts to get a true demand value. Due 

to the sporadic nature of speeds below the queue threshold and the absence of expected 

patterns (the study team often observed queues at two sensors but free flow conditions at 

a sensor in between the two), the data proved inconclusive. This limitation is inherent in 

many studies, as the data collection plan would need to account for field observations and 

normally is too costly and difficult to plan for. It is important to understand the effects of 

congestion on throughput; however, the very large change in volume shows that, by 

alerting motorists on another route to avoid DC-295, the system likely had a positive 

impact on travel through the corridor. 
23

For the northbound direction, the study team compared one day “without ITS” to one day 

“with ITS.” These two dates were April 6 and April 20, respectively. No clear trend was 

apparent from the data, although the study team observed similar large percentage 

differences in volumes for some time periods. On April 20, the system recommended 

that motorists seek an alternate route from 2:22 p.m. until 4:10 p.m.—a timeframe that 

showed lower volumes during the “without ITS” period, as seen in Figure 4. The posted 

messages showed the delay and recommended that motorists seek an alternate. The 

difference was that the delay was lower in this case than the previous case—posted 

delays did not exceed 15 minutes on April 20. 

0

500

1000

1500

2000

2500

07:32 12:35 17:32 22:40

Time of Day

30 Minute Volumes

April 6, 2007

April 20, 2007

Figure 4. Volume Levels by Time of Day 

The data displayed above shows the best examples, from all the data, of how motorists 

were impacted. While the system alleviated congestion on the mainline, alternate routes 

should also be monitored to the extent feasible to avoid shifting congestion to another 

route or corridor. For this study, the study team was unable to observe the alternate 

routes due to cost. 

DMS Messages 

Throughout the deployment, the system posted 85 different types of messages at different 

times. The system often posted delay, speed ahead, and other caution messages warning 

motorists of the construction activities ahead. 
24

The system used several preprogrammed messages, and operators had the ability to 

override the system and post messages manually as needed. Examples of the types of 

messages and variations are shown below. 

Messages Showing Delay 

• X MINUTE DELAY AHEAD PLEASE USE CAUTION. 

Messages Showing Speed Ahead 

 X MPH SPEED AHEAD SLOW DOWN. 

 X MPH SPEED AHEAD PREPARE TO STOP. 

 X MPH SPEED DC-295 SLOW DOWN. 

 X MPH SPEED DC-295 PREPARE TO STOP. 

Example Test Message 

 MESSAGE MESSAGE MESSAGE TEST TEST TEST. 

Messages Encouraging or Requiring Diversion 

 X MIN DELAY AHEAD SEED ALT. ROUTE. 

 X MIN DELAY ON 295-S SEEK ALT. ROUTE. 

 X MIN DELAY DC-295N SEEK ALT. ROUTE. 

 X MIN DELAY ON DC-295S SEEK ALT. ROUTE. 

 X MIN DELAY ON DC-295 SEEK ALT. ROUTE. 

 S CAP ST BRIDGE CLOSED TRUCK & VEHICLE TRAFFIC. 

 S CAP ST BRIDGE CLOSED VIRGINIA TRAFFIC USE 295S. 

 S CAP ST BRIDGE CLOSED USE NEW YORK AVENUE. 

Messages Showing General Traffic Conditions 

 BRIDGES FREEZE BEFORE ROADWAY DRIVE W/CAUTION. 

 S CAP ST BRIDGE CLOSED TRUCK & VEHICLE TRAFFIC. 

 WORK ZONE DC-295 PLEASE USE CAUTION. 

 WORK ZONE AHEAD. 

 WORK ZONE AHEAD PLEASE USE CAUTION. 

Other Messages 

 CLICK IT OR TICKET. 

 SOCCER GAME AT RFK THURSDAY 5PM-9PM. 

 DRIVE WITH CARE. 

DDOT added sensors and message boards on June 29, 2007, to account for a construction 

project in nearby Maryland. DDOT purchased two additional sensor trailers and one 

additional message board for the Maryland project. The additional sensor trailers 

allowed DDOT to detect congestion due to the Maryland project and to alert motorists 

approaching that project within the DC project area. The system combined delays from 

the two projects as appropriate to determine the total delay. Also, DDOT used the 

additional message board to expand motorist information south to the South Capitol 

Street Bridge, which allowed messages relating dates and times of the bridge closing to 
25

be conveyed to travelers. The system also posted South Capitol Street Bridge status 

messages on the Baltimore-Washington Parkway in Maryland and before the exits to 

Route 50 and New York Avenue. 

Overall, the real-time information system deployed on DC-295 in Washington, DC 

appeared to effectively divert traffic to unsigned, unspecified alternate routes during 

times of significant congestion. There was an average of 52% lower mainline volume 

observed (combination of diversion, demand reduction, and congestion). It should be 

noted that the results include potential reduced throughput due to queues and congested 

conditions (likely significant for the higher end of the range). However, even considering 

the congestion impacts on throughput, these results show that the system likely reduced 

delay substantially for motorists by providing them with information to better enable 

them to choose an alternate route. It should also be noted that this is an urban area with 

a large number of commuter trips. Based on the data available, it is not possible to 

determine what portion of the lower mainline volume was due to diversion versus 

demand reduction versus congestion. 

Tips and Lessons Learned 

Deployment Tips and Lessons Learned 

Coordinate with neighboring States and local agencies. DDOT coordinated with other 

local agencies in addition to coordination with the Maryland State Highway 

Administration on the neighboring construction project. When the South Capitol Street 

Bridge was closed, DDOT coordinated with the local jurisdictions to divert over 72,000 

vehicles for a 2-month period while the construction was ongoing. The coordination 

process helped DDOT plan for outreach to the media to help motorists avoid the already 

congested DC-295 corridor while it was under construction. 

Flexibility in system configuration is important. DDOT successfully modified the 

original system layout to account for impacts from a separate construction project in a 

neighboring state. 

Allow time for obtaining right of way use permits for equipment installation. The 

vendor used by DDOT noted that time was required to get approval of these permits 

before they could place the equipment in the field. 

Secondary benefits of managing recurring congestion along heavily traveled urban 

corridors may also be achieved. DDOT successfully used the system to manage 

recurring congestion along the heavily traveled DC-295 corridor. 

Evaluation and Research Tips and Lessons Learned 

A successful evaluation of a work zone ITS deployment relies heavily on the 

cooperation of each entity involved. As the final evaluation performed under this study, 

the study team reaffirmed many of the previous evaluation and research lessons learned 

from the other sites. For this study all parties were helpful in obtaining necessary 

information. 
26

Need to be able to verify conditions in the field as they occur. Often, with archived data, 

evaluators are unable to validate data and findings as conditions occur in the field. A 

measure in addition to volume is commonly needed to measure the level of congestion 

and congestion impacts on throughput. 
27

I-35 Hillsboro, Texas 

In October 2006, The Texas Department of Transportation (TXDOT) implemented an 

ITS system in a construction work zone in Hillsboro, Texas. The purpose of the system 

was to monitor conditions and improve mobility and safety through the work zone along 

I-35, 35W, and 35E in Hillsboro County. TXDOT designed the system to provide 

motorists with real-time information on downstream conditions and to provide alternate 

route guidance during times of heavy mainline congestion. TXDOT sought to warn 

motorists of speed variability issues and to lessen traffic delays caused by capacity 

reductions and rubber-necking in the work zone. 

TXDOT designed an ITS system for a work zone on Interstate 35 south of Waco in 

Hillsboro County, as shown in Figure 5. 

Figure 5. I-35 Work Zone and Signed Alternate Routes (Taken from TXDOT’s Web 

Site) 

Based on predetermined speed and occupancy thresholds, the system provided real-time 

delay information and recommended alternate routes via dynamic message signs (DMS). 
28

TXDOT operators also monitored traffic conditions in the work zone through the use of 

three wireless closed circuit video cameras. 

The main objectives of the system were to: 

 Reduce demand and congestion (by actively diverting traffic approaching the 

work zone). 

 Provide delay information and route guidance to motorists enroute to warn them 

of slowed traffic ahead. 

 Provide trip planning information to commuters and system management 

information to DOT personnel via a Web site. 

The main objectives of the evaluation were to: 

 Determine traveler response to the work zone information. 

 Determine the effect of traveler response on traffic conditions. 

 Determine whether the system detected congestion as it occurred and posted the 

appropriate messages. 

Study Site Work Zone 

TXDOT installed the work zone between milepost (MP) 364 and MP 374, north of Waco. 

As shown in Figure 17, I-35 splits north of Waco into I-35E leading to Dallas and I-35W 

leading to Fort Worth. All three highways have similar characteristics and are four-lane 

divided freeway facilities. TXDOT set up lane closures in each direction in order to 

reconstruct the main interchange and rehabilitate and reconstruct pavement and structures 

along the route. 

The contractor began construction in July 2006 with an estimate for completion of mid2008. Two separate construction projects were planned for the general area. Lane 

closures on the south end of the corridor near exit 364 occurred from October 2006 

through February 2007. For the second project, the contractor restricted capacity by 

closing one lane in each direction during late 2006 and early 2007. The latter project is 

located on I-35 at the I-35E / I-35W interchange near milepost 371. Work will continue 

through 2008. 

TXDOT expected long queues and delays, especially on I-35W southbound near the split. 

For northbound I-35, the existing geometry is such that each lane directs traffic to either 

I-35E or I-35W. That is, the two lane section splits into one lane for I-35E traffic and 

another separated lane for I-35W traffic. I-35 branches off into two directions to the 

north and becomes I-35E and I-35W. A large portion of the traffic along the corridor is 

commuter traffic, as many of the exits along the work zone area serve farm land and 

provide access from rural roads. Major attractors that might impact traffic patterns were 

not prevalent along the corridor, especially around exits that are in close proximity to the 

work zone. 
29

ITS Description 

The TXDOT deployment work zone ITS was made up of three individual systems meant 

to alleviate non-recurring congestion along the I-35 corridor. Since the I-35 roadway 

configuration consisted of three different approaches to the work zone, three independent 

traffic monitoring systems were used. Alternate routes were signed for each of the three 

traffic flows. While one vendor provided the entire system, it acted as three independent 

closed loop systems, one for each approach to the work zone. While this document may 

reference the “system,” it refers to the entire vendor-provided solution made up of three 

components. 

The primary goal of the system was to monitor this project’s work zones and 

automatically provide alternate route advisory information to the traveling public based 

on significant travel times through the work zone. A secondary goal of the system was 

congestion management of non-recurring traffic conditions because of high traffic 

volumes, weather, and incidents. 

The system consisted of the following components: 

• Six solar powered portable side-fire microwave detection trailers 

• Six solar-powered portable changeable message signs 

• Three portable video (camera) trailers 

• A system server, Web host, and associated communication equipment and software 

• A Web site for use by TXDOT and the general public. 

For each approach to the work area, two sensors monitored traffic and sent messages to 

two PCMS based on pre-determined speed and occupancy thresholds, as shown in Table 

5. 

Table 5. Example Queue Thresholds - 35W Southbound 

Normal 

Traffic Flow 

through Work 

Zone 

>=55MPH 

Speed 

Average 

40<x>55MPH 

@5min 

Lane 

Occ>20% 

Speed 

Average 

25<x>40MPH 

@5min 

Lane 

Occ>30% 

Speed 

Average 

10<x>25MPH 

@5min 

Lane 

Occ>40% 

Speed Below 

10MPH 

@5min 

Lane 

Occ>50% 

 

WORKZONE WORKZONE WORKZONE WORKZONE WORKZONE 

AHEAD AHEAD AHEAD AHEAD TRAFFIC 

2 MILES 2 MILES 2 MILES 2 MILES STOPPED 

 

NO MODERATE EXPECT LONG USE 

DELAYS DELAYS DELAYS DELAYS ALT 

-x:xxPM- -x:xxPM- -x:xxPM- -x:xxPM- ROUTE 

TXDOT dynamically adjusted queue thresholds, had message pre-emption capabilities, 

and had notification capability to alert appropriate personnel of problems. In addition to 

the vehicle count, speed, and classification data, streaming video was made available 
30

from three portable camera trailers. TXDOT also implemented a public Web site to allow 

access to current system operational status and to view existing traffic conditions. 

TXDOT procured the system through the prime construction contractor. 

Measures and Metrics 

The study team focused traffic data collection efforts on measuring diversion rates at 

freeway exit ramps to test driver response to the system. To supplement the system 

detector data, the study team collected data through three additional queue trailers with 

side-fire radar at three key diversion locations along the corridor that provided access to 

the signed alternate routes. The study team installed sensors upstream of the work zone 

and system detectors downstream of the PCMS to collect mainline and ramp volume, 

speed, and occupancy at each location. Original plans included travel time runs on the 

mainline and alternate routes. However, data collection in this regard proved too costly 

and difficult to properly capture conditions during impact periods. 

The study team compared baseline data prior to ITS implementation (without ITS) with 

the period when the system was active (with ITS). The study team collected data from 

the three supplemental detectors from October 3, 2006, until February 4, 2007, and the 

vendor archived system detector data beginning October 4, 2006 and message logs 

beginning October 23, 2006. The system was turned on to traffic on October 26, 2006. 

Figure 6 shows the location of the three supplemental data collection queue detectors 

(labeled Q1, Q2, and Q3). 
31

Figure 6. Modified Corridor Map Showing Data Collection Sensor Locations 

The success of the evaluation hinged upon the accuracy and completeness of several key 

data elements, including: 

 Traffic volumes and average speed and occupancy measurements at each sensor 

location. 

 Message logs showing the times and dates that the pre-determined messages were 

activated. 

 Time-specific information on construction activities and delay observations as 

noted by inspectors in DOT construction logs. 

The study team developed several hypotheses based on the goals for the system. The key 

hypothesis, associated measures, and data sources for testing each are shown in the 

following table. 
32

 Table 6. Key Hypothesis, Measures, and Data Sources for Evaluation 

Hypothesis Measures of Effectiveness Data Sources 

The use of ITS in work zones will 

divert travelers to alternate 

routes during times of work zone 

congestion 

Diversion rates at exit ramps with 

and without the system and with 

construction; diversion rates during 

construction or an incident 

compared with normal patterns 

System detector 

data, supplemental 

data from three 

additional queue 

detectors 

Findings 

The study team mainly focused data collection efforts on testing the level of diversion 

around the work zone during periods of congestion. The site showed that, during times 

of very heavy congestion, motorists will follow the diversion guidance posted on 

message boards. Large percentages of traffic diverted on several occasions when the 

system recommended the alternate route. 

For this site, the study team designed the data collection plan to help answer several key 

questions including: 

Question: Did the system detect the congestion as it occurred? 

Findings: It appears that the system detected congestion and displayed appropriate 

messages, although the minimum diversion message post time was likely too short in 

some cases. 

Question: Did the system post appropriate messages when it detected congestion? 

Findings: The system posted travel times for conditions at or near free flow travel times, 

“Slow Traffic Ahead” and similar messages when speeds dropped, and diversion 

messages when occupancy met the appropriate threshold. 

Question: Did motorists respond to the diversion messages—and how? 

Findings: When the system posted messages recommending the signed alternate routes, 

large percentages of traffic diverted. Major incidents during heavy traffic periods (such 

as holiday weekends) were a main cause for active diversion, more so than typical 

construction activity and lane closures. During major incidents or high construction 

impact periods combined with high demand, the system diverted an average of 10 percent 

of mainline traffic to alternate routes. Diversion was as high as 28 percent during the 

study observation period. 

The key hypothesis was found to be true for this deployment based on observations. The 

system diverted large amounts of traffic during incident and construction impact periods 

compared with normal conditions. 

The following sections provide additional detail from the analysis. 
33

Construction Activity Information 

TXDOT provided construction activity information from inspector logs and from a 

template provided by the study team. The study team matched the information provided 

with the data patterns and trends from the data collection period. Tables 7 and 8 highlight 

the initial information provided by TXDOT. 

Table 7. Construction and Lane Closure Information (October 2006) 

Date 

Time of Day 

(Beginning) 

Time of 

Day 

(End) 

Crashes 

Observed 

Mile Marker 

Location/ 

Description Activity Notes 

10/3/2006 8:30 AM 9:00 AM Yes 35W SB mm1 Three separate 

crashes – lanes open 

10/3/2006 9:00 AM 9:40 AM Yes I-35 SB mm 370 Two vehicle crash – 

lanes open 

10/3/2006 8:15 AM 8:45 AM Yes I-35 SB mm 369 One vehicle crash – 

lanes open 

10/12/2006 6:30 PM 1:30 AM -- I-35 SB at exit 

368B 

Inside lane closed for 

construction 

Table 8. Construction and Lane Closure Information (November-December 2006) 

Date 

Time of Day 

(Beginning) 

Time of 

Day 

(End) 

Crashes 

Observed 

Mile Marker 

Location/ 

Description Activity Notes 

11/14/2006 9:00 AM 9:45 AM Yes I-35 NB mm368 One vehicle involved 

11/20/2006 7:00 PM 10:00 PM -- I-35 SB 

mm368B to 370 

Lane closed for 

pothole repair 

12/13/2006 4:30 AM 11:15 AM Yes 35E SB mm372 

Lane closed due to 

crash and barrier rail 

repair 

12/13/2006 4:00 AM 5:00 AM -- 35W SB mm2 to 

mm5 

Lane closed for crack 

seal work 

12/13/2006 7:00 PM 10:00 PM -- 35W NB Lane closed for 

construction activities 

12/14/2006 3:15 PM 3:50 PM Yes 35W NB at split Two vehicle crash – 

lanes open 

12/14/2006 3:30 PM 4:00 PM Yes I-35 NB US77 

Exit Ramp 

Three vehicle crash – 

lanes open 

The study team noted any days where the detectors captured traffic impact periods (any 

condition other than free flow) but field condition information was not available. TXDOT 

reviewed its logs and incident database and provided additional information as available. 

Information was not available for several time periods where traffic data showed delays 

and queuing. 
34

Several significant incidents and crashes occurred November 23-26, 2006, over the 

heavily-traveled Thanksgiving Holiday weekend. The traffic data showed significant 

delay and queuing and heavier than normal volumes. During this time period, the system 

activated several times to divert traffic. Since the work zone was not active with lane 

closures and construction activity over the holiday weekend and observations by 

inspectors were not captured, the study team does not have many of the specific details 

on the extent of the traffic impacts from the crashes. However, as shown in the following 

sections, several data points were useful in the analysis. 

System Detector Traffic Data 

The study team sorted and analyzed traffic data from system detectors and the 

supplemental data collection detectors to quantify the impacts from construction and to 

identify periods of impact where additional information would be useful. The archived 

traffic data from each detector consisted of more than 500,000 records covering a time 

period from October 2006 through February 2007. Each message consisted of a volume 

count, an average speed value, and an average occupancy value by lane for both lanes in 

each direction along I-35, I-35E, and I-35W. The data set for each sensor appeared to be 

very complete and the data appeared reasonable. 

The study team observed one incident during construction and prior to system 

deployment. A lane closure was in place on October 12 and 13, 2006, on northbound I35. Figure 7 highlights consistent volume patterns for this baseline time period. The 

green line (ramp counts) shows no distinct spike in volume based on the conditions. 

While the study team only had limited observations to analyze during the “without ITS” 

period, one can logically conclude that motorists (especially through trips) would not be 

comfortable diverting to an unfamiliar roadway without knowledge of the impact to their 

trip. 
35

Volumes

0

10

20

30

40

50

60

70

4:00:00 PM

4:26:00 PM

4:51:00 PM

5:16:00 PM

5:41:00 PM

6:06:00 PM

6:31:00 PM

6:56:00 PM

7:21:00 PM

7:46:00 PM

8:11:00 PM

8:36:00 PM

9:01:00 PM

9:26:00 PM

9:51:00 PM

10:17:00 PM

10:47:00 PM

11:11:00 PM

11:36:00 PM

Ramp Right Lane Left Lane

Figure 7. Volume Patterns (Q3: 35E SB) – October 12 Lane Closure (Without ITS) 

Figure 8 shows high occupancy values at the system detector location within the work 

zone between 9 p.m. and 11 p.m. These values showed enough impact to warrant 

diversion (50 percent occupancy) of traffic during this time period. However, a large 

percentage of traffic did not divert to the signed alternate routes. 
36

0

10

20

30

40

50

60

4:00:00 PM4:21:00 PM4:41:00 PM5:01:00 PM5:21:00 PM5:41:00 PM6:00:00 PM6:21:00 PM6:41:00 PM7:00:00 PM7:21:00 PM7:42:00 PM8:00:00 PM8:21:00 PM8:41:00 PM9:00:00 PM9:21:00 PM9:41:00 PM

10:00:00 PM10:21:00 PM10:41:00 PM11:00:00 PM11:21:00 PM11:42:00 PM

Right Lane Left Lane

Figure 8. Occupancy Values (System Q4: 35E SB) – October 12 Lane Closure 

(Without ITS) 

The study team also analyzed traffic data during construction and with ITS, mainly 

focusing on days where the system actively diverted traffic. For a major crash on 

November 26, 2006, involving a tractor trailer, the data showed higher than normal ramp 

volumes during a nearly 5 hour period where the system actively diverted traffic. Figure 

9 shows high occupancy values detected by the system. The incident likely included 

traffic shifts and lane closures, but validation based on specific information proved 

difficult due to the limited availability of such information. 
37

Figure 9. Occupancy Values (System Q1: I-35 NB) – November 26 Incident (With ITS) 

Figure 10 shows trends in ramp volumes during the same period on November 26, 2006. 

The general trend shows that motorists used the guidance provided by the system and 

diverted around the impact area. 

0

10

20

30

40

50

60

70

80

12:00:00 PM

12:26:00 PM

12:51:00 PM

1:16:00 PM

1:41:00 PM

2:06:00 PM2:31:00 PM

2:57:00 PM

3:22:00 PM3:47:00 PM

4:12:00 PM4:38:00 PM5:01:00 PM

5:26:00 PM5:51:00 PM

6:16:00 PM

6:41:00 PM7:07:00 PM7:32:00 PM

7:59:00 PM8:22:00 PM

8:47:00 PM

Right Lane Left Lane
38

Figure 10. Volumes (Q2: I-35 NB) – November 26 Incident (With ITS) 

The study team also analyzed actual diversion levels based on the percentage of traffic 

using the ramp at each diversion point compared with similar days during the same 

month. The following table highlights the percentage of traffic that diverted for another 

incident that occurred on November 23, 2006. While the total volumes varied, the 

percentage of total volume using the ramp changed significantly when the system advised 

motorists to divert. 

Volumes

0

20

40

60

80

100

120

12:00:00 PM12:26:00 PM12:51:00 PM

1:16:00 PM1:41:00 PM2:06:00 PM2:32:00 PM2:56:00 PM3:22:00 PM3:46:00 PM4:11:00 PM4:36:00 PM5:01:00 PM5:26:00 PM5:51:00 PM6:17:00 PM6:41:00 PM7:06:00 PM7:31:00 PM7:56:00 PM8:21:00 PM8:46:00 PM

Ramp Right Lane Left Lane
39

Table 9. Diversion Rates for November 23rd Incident Compared with Other 

Thursdays in November 

Volumes 

Date Detector Ramp Total

Percent 

Diversion

Number 

of 

Records

Active Diversion Time 

Period 

q01 70 1479 4.7% 68 From 10:10 AM to 11:51 AM 

11/9/2006 q02 35 1409 2.5% 100 From 10:23 AM to 12:43 PM 

q03 14 1423 1.0% 96 From 10:20 AM to 11:57 AM 

q01 113 2090 5.4% 98 From 10:10 AM to 11:51 AM 

11/16/2006 q02 61 1926 3.2% 137 From 10:23 AM to 12:43 PM 

q03 15 1305 1.1% 86 From 10:20 AM to 11:57 AM 

q01 985 3596 27.4% 97 From 10:10 AM to 11:51 AM 

q02 934 3356 27.8% 136 From 10:23 AM to 12:43 PM 

11/23/2006 

q03 383 3354 11.4% 96 From 10:20 AM to 11:57 AM 

q01 77 1328 5.8% 96 From 10:10 AM to 11:51 AM 

11/30/2006 q02 72 1463 4.9% 144 From 10:23 AM to 12:43 PM 

q03 17 1138 1.5% 103 From 10:20 AM to 11:57 AM 

 

The Thanksgiving weekend incident showed a similar pattern, as outlined in Table 10. 

Similarly, the total mainline traffic volume was significantly higher, but the diversion 

rates as a percentage of total mainline traffic were also significantly higher. A 27 percent 

difference in ramp to total traffic occurred compared with other similar days of the week 

as a result of the alternate route guidance displayed. 

Table 10. Diversion Rates for November 26th Incident Compared with Other 

Sundays in November 

Volumes 

Date Detector Ramp Total

Percent 

Divert 

Number 

of 

records Time Period 

q01 23 558 4.1% 13 From 5:59 PM to 6:12 PM 

11/5/2006 q02 68 5735 1.2% 294 From 2:13 PM to 7:32 PM 

q03 16 3659 0.4% 157 From 4:12 PM to 6:46 PM 

q01 15 514 2.9% 13 From 5:59 PM to 6:12 PM 

11/12/2006 q02 75 5851 1.3% 295 From 2:13 PM to 7:32 PM 

q03 28 3854 0.7% 157 From 4:12 PM to 6:46 PM 

q01 17 451 3.8% 12 From 5:59 PM to 6:12 PM 

11/19/2006 q02 74 5467 1.4% 298 From 2:13 PM to 7:32 PM 

q03 32 3301 1.0% 158 From 4:12 PM to 6:46 PM 

 

q01 35 482 7.3% 11 From 5:59 PM to 6:12 PM 

11/26/2006 q02 2332 8084 28.8% 314 From 2:13 PM to 7:32 PM 

q03 966 5549 17.4% 166 From 4:12 PM to 6:46 PM 
40

Overall, the study team found 1 to 28 percent reduction in mainline traffic volume (with 

an average of 10 percent reduction) during congested periods, lessening the demand for 

restricted mainline capacity. These results are based on 20 observation periods during 

which the system actively diverted traffic due to congestion from construction or 

incidents. 

No data collection activities occurred on the alternate routes, making it difficult to 

determine the operational performance of the two- and four-lane alternates during 

diversion periods. Additionally, due to the limited number of system detectors (two in 

each direction), the study team was not able to draw meaningful conclusions about how 

well the diversion rates improved mainline conditions and travel times. 

Dynamic Message Sign Data 

The system archived message logs from October 2006 until February 2007. The archives 

included more than 650,000 records. The study team observed some small quantities of 

missing or anomalous information. 

Throughout the deployment, the system posted variations of different messages at 

different times. On occasion, the system posted a message recommending an alternate 

route for very short periods followed by a different message. For each approach, the 

system was consistent in posting a general message on the upstream message board and a 

more specific message, such as recommending the alternate route, downstream. 

The system used several preprogrammed messages, and operators had the ability to 

override the system and post messages manually as needed. Variations of the following 

messages were posted at different times throughout the deployment. 

Messages Showing Delay 

• WORKZONE AHEAD 2 MILES MODERATE DELAYS. 

• WORKZONE AHEAD 2 MILES EXPECT DELAYS. 

• SLOW TRAFFIC AHEAD MODERATE DELAYS. 

• SLOW TRAFFIC AHEAD EXPECT DELAYS. 

• ROAD WORK AHEAD 2 MILES MODERATE DELAYS. 

• ROAD WORK AHEAD 2 MILES LONG DELAYS. 

• ROAD WORK AHEAD 2 MILES EXPECT DELAYS. 

Messages Showing No Delay 

 WORKZONE AHEAD 2 MILES NO DELAYS. 

 TRAVEL TIME X MIN NEXT X MILES. 

 ROAD WORK AHEAD 2 MILES NO DELAYS. 

Messages Encouraging Diversion 

 TRAFFIC STOPPED AHEAD USE ALT IH35 ROUTE. 

 TRAFFIC STOPPED AHEAD ALT RTE EXIT 364A. 

 ROAD WORK TRAFFIC STOPPED USE ALT ROUTE. 
41

 ALT IH35 EXIT NOW 3 FOLLOW ROUTE MARKERS. 

 ALT IH35 EXIT NOW 364A FOLLOW ROUTE MARKERS. 

 ALT IH35 EXIT NOW 374 FOLLOW ROUTE MARKERS. 

Messages Showing General Traffic Conditions 

 SPEED AHEAD X MPH X MIN NEXT X MILES. 

 SPEED AHEAD X MPH REDUCE YOUR SPEED. 

 SPEED AHEAD X MPH REDUCE SPEED NOW. 

 SLOW TRAFFIC AHEAD BE PREPARED TO STOP. 

Other Messages 

 SLOW ICE WARNING. 

 DRIVE SAFELY. 

Overall, the system posted consistent messages and, based on the archived data, appeared 

to function properly. The system provided a benefit to travelers during periods of 

mainline congestion by providing alternate route recommendations and reducing demand 

for the mainline freeway. 

Tips and Lessons Learned 

Deployment Tips and Lessons Learned 

The study team uncovered several lessons learned to the benefit of TXDOT and others 

interested in deploying similar systems. 

Begin work on the deployment at the early concept stages of the planning process. The 

deployment at this site was delayed due to lead time in procuring the system. To achieve 

the maximum benefit, ITS should be operational prior to any lane restrictions. 

In design and implementation of ITS for work zone applications, agencies should 

involve the construction contractor as early as possible and to the fullest extent 

possible. TXDOT experienced unanticipated delays in modifying the contract to include 

the ITS system. Agencies risk not achieving their goals if the system is viewed as a “pass 

through” to a vendor and not the responsibility of the contractor. 

Personnel from the implementing agency should have real-time access to archived 

system data to identify any issues and monitor system functionality. For the TXDOT 

site, a Web site provided real-time information display, but archived data access was 

more time consuming and not easily accessed on short notice. 

Evaluation and Research Tips and Lessons Learned 

Prioritize and focus on a small number of metrics that provide the best opportunity to 

quantify benefits. Diversion patterns at this site proved very useful in assessing the 

response to diversion-based messages.
42

US-131 Kalamazoo, Michigan 

In the summer of 2004, the Michigan Department of Transportation (MDOT) deployed 

ITS technology in a work zone on US-131 in Kalamazoo. MDOT deployed the Dynamic 

Lane Merge (DLM) System in the northbound direction of US-131 just south of the M-43 

freeway. Such systems are deployed to control traffic at merge areas by promoting early 

merge (smoothing flow by creating a no passing zone upstream of the closure) or late 

merge (encouraging motorists to use both lanes to minimize queue spillover). Dynamic 

Early Merge Systems, such as the one deployed at this site, smooth traffic flow at merge 

areas by activating an enforceable no passing zone upstream of the taper. MDOT has 

successfully used this type of system on multiple occasions in the past to mitigate impacts 

caused by work zone capacity reductions. The study team collected data during a twoweek period in September 2004 to evaluate the benefits of the system. 

The main objectives of the system deployment were to: 

 Reduce aggressive driving at the merge point where two lanes were reduced to 

one in each direction. 

 Smooth traffic flow through the merge area. 

 Potentially reduce delay from aggressive passing at the merge area. 

The main objectives of the evaluation were to: 

 Quantify ITS impacts on aggressive driving. 

 Quantify safety and mobility impacts. 

 Verify that the work zone ITS functioned as designed. 

For an early merge DLM system, MDOT previously identified an effectiveness range 

(demand that warrants use of the system) of 2,000 to 3,000 vehicles per hour for two-toone lane drop configurations. The effectiveness range exceeds capacity since queue 

conditions cause aggressive maneuvers and forced merges. While these numbers exceed 

the capacity of one lane on a freeway, the effectiveness range includes the level of 

demand that is needed to improve conditions over what would have been observed 

without the early merge system. As shown in the following figure, a sample set of past 

peak hour volume counts for I-131 fell within this range. 
43

3198

2711

2589

2771

3064

21482195

2547

2104

2494

2336

2486

0

500

1000

1500

2000

2500

3000

3500

7/7/2003 7/8/2003 7/9/2003

Day

Volume (VPH)

Northbound AM

Peak Hour

Northbound PM

Peak Hour

Southbound AM

Peak Hour

Southbound PM

Peak Hour

MDOT Effectiveness 

Range

Figure 11. 2003 Peak Hour Volume Counts on US-131

The system deployment schedule mirrored the construction schedule, leaving little 

opportunity for establishment of baseline conditions (the “without ITS” scenario). Since 

demand levels were similar in both directions, the study team had planned to analyze the 

southbound approach to the merge area as the “without ITS” condition and the 

northbound approach as the “with ITS” condition. While this approach was not exactly 

the same as a true before and after study, it was designed to try to provide a reasonable 

comparison of a traditional merge setup with a dynamic merge setup. From the past 

volume data, the northbound and southbound afternoon peak period showed the most 

similar demand levels. The study team collected data for each afternoon peak period. 

Study Site Work Zone 

US-131 is a four lane divided freeway with a normal speed limit of 70 mph that connects 

Kalamazoo and Grand Rapids, Michigan. The contractor set up the work zone along US131 from north of M-43 (exit number 38) to north of M-89 (exit number 49) in the cities 

of Kalamazoo and Plainwell. MDOT reduced the speed limit through the work zone from 

70 mph to 60 mph. The northbound Annual Average Daily Traffic (AADT) is 

approximately 29,000 and the southbound AADT is approximately 23,000. MDOT 

deployed the system in the northbound direction, although demand levels in both 

directions fell within the range for implementation based on the 2003 traffic counts. The 

work zone was approximately 11 miles in length from beginning sign to end sign. The 

DLM system was deployed in the approximately one mile section of roadway leading up 

to the merge point just south of the lane closure. 

The contractor commenced construction on June 3, 2004, and finished on November 19, 

2004. The construction involved pavement rehabilitation and included concrete and 
44

asphalt overlays. The contractor performed the first and second phases on the 

northbound and southbound sides of the highway, respectively. During the first phase, 

the contractor shifted traffic and set up two-way traffic (one lane in each direction) on the 

northbound side. The contractor used the same traffic control configuration for Phase II, 

but this time transferred all traffic to the southbound side (two way traffic, one lane in 

each direction). Concrete barriers separated traffic during each phase. 

ITS Description 

MDOT designed the DLM System to require traffic to merge early to smooth traffic flow 

and reduce aggressive driving at the merge point. MDOT installed five trailers 1500 feet 

apart prior to the merge point, each equipped with lighted “Left Lane Do Not Pass When 

Flashing” signs. The trailer closest to the merge was always flashing. MDOT equipped 

each trailer with a Remote Traffic Microwave Sensor (RTMS) unit, with the exception of 

the trailer furthest from the work zone. MDOT procured the system through a vendor 

subcontract through the prime construction contract. 

The closed loop system operated based on traffic occupancy. For example, when sensor 

#1 detected the threshold occupancy, sensor #1 sent a message to sensor #2 alerting it to 

activate the flashing lights. The occupancy thresholds for sensors 1, 2, 3, and 4 were 5 

percent, 7 percent, 9 percent, and 11 percent, respectively. Each sensor had a 5-minute 

minimum activation period. 

The Dynamic Lane Merge System was comprised of the following components: 

 4 sets of traffic sensors. 

 5 trailers with a flasher, solar power equipment and batteries. 

 Message signs. 

 Communication devices. 
45

The layout for the system is shown in the following figure. 

Figure 12. DLM Layout Along Northbound US-131 

Measures and Metrics 

The study team developed a set of hypotheses and associated measures of effectiveness 

(MOEs) around the key goals for the system, as shown in Table 11. 

Table 11. Measures and Metrics for the Michigan DLM deployment 

Hypothesis Measures of Effectiveness Data sources 

The use of ITS in work zones will 

enhance the safety performance of 

the highway 

Crashes, incidents, aggressive 

maneuvers, citations issued 

Crash data, direct 

observations, citation 

logs 

The use of ITS in work zones will 

reduce traveler delay 

Travel times through the merge area, 

average speeds, and average and 

maximum queue lengths 

Direct observations, 

system data, travel time 

runs 

While the study team originally intended to use the southbound side (without ITS) as the 

comparison site, congestion was not an issue on the southbound side, which meant that it 

would not be a good comparison. Therefore, the study team compared the time periods 

when the system was flashing (i.e. activated) with the time periods when the system was 

not flashing (i.e., not activated—trailers upstream of trailer 1 were not flashing), all for 

the northbound direction of travel instead of comparing northbound to southbound. 

The study team collected data for a 2-week period from September 20 through October 1, 

2004. During this period, study team members performed travel time runs, using Global 

Positioning System (GPS)-equipped vehicles, in each direction from 3:30 p.m. until 
46

6 p.m. each weekday. The study team also collected traffic count data along two 

mainline areas and seven ramp areas to determine demand at different locations with the 

merge areas. A modem was installed on one trailer and MDOT archived sensor data for 

August, September, and October for use in the evaluation. 

Findings 

Hypothesis 1: The Use of ITS in Work Zones Will Enhance the Safety 

Performance of the Highway 

Since one of the main deployment objectives was to reduce aggressive maneuvers, the 

study team collected data on several different types of aggressive driving behavior for 

analysis. During each travel time run, a passenger in each vehicle observed driver 

behavior within both the northbound and southbound merge areas. Notes were recorded 

based on the following categories. 

• Lane straddling by tractor-trailers or other vehicles to block vehicle passing. 

• Motorists illegally passing in the northbound US-131 passing lane when the 

dynamic lane merge signs are flashing “Do Not Pass.” 

• Dangerous merges, or forced early merges (people slamming brakes to merge, 

forcing vehicle into other traffic lane, people responding to flashing “Do Not 

Pass” signs improperly, etc.) 

• Forced merges at/near the lane drop. 

Study team members also noted observations that describe the environment at each of six 

specified areas shown in Figure 13. The study team observed conditions to: 

• Document which of the five dynamic merge signs were flashing in the northbound 

travel direction during each pass through the area 

• Document an enforcement presence or lack thereof for each run along with any 

incidents that may have affected the traffic flow during the travel time run (crash, 

construction vehicles, stalled vehicle, etc.). 

Figure 13. DLM System Setup

Tables 12 and 13 show the aggregate daily observations within each area for the twoweek period. The information in the tables classifies the aggressive maneuvers into 

separate categories based on type, and also shows whether the study team observed the 

I-94

5 4 3 2 1

Trailers 

Location 1 2 3 4 5 6 

N
47

system flashing (at least one trailer except the first since it was always flashing) and 

whether police were present. Study team members noted only one instance of queuing in 

the southbound direction and there were no forced merges observed at the lane drop. 

While conducting the travel time runs, the study team made observations as noted in the 

tables for metrics such as whether the system was activated; whether lane straddling, 

illegal passing maneuvers, or dangerous merge maneuvers occurred; whether police 

officers were present; whether there were incidents; whether there were forced merges; 

and whether queues were present. 

Table 12. Aggregate Aggressive Driving Observation Classifications by Date 

(Northbound) 

Date # of 

Runs 

On 

Flash? 

Lane 

Straddling

Illegal 

Passing

Dangerous 

Merge Police Incident Forced Merge Queue

09-20-04 15 0 0 28 8 0 2 4 0 

09-21-04 12 0 0 22 3 0 1 2 0 

09-22-04 13 0 0 25 1 4 3 2 1 

09-23-04 13 0 0 39 4 0 0 1 0 

09-24-04 13 52 16 70 5 0 0 0 16 

09-27-04 12 0 0 26 0 3 8 0 1 

09-28-04 13 0 1 27 2 0 0 2 0 

09-29-04 13 0 0 39 0 0 0 5 0 

09-30-04 13 0 0 30 1 0 0 0 0 

10-01-04 13 18 2 58 1 0 0 2 2 

Total 130 70 19 364 25 7 14 18 20 

Table 13. Aggregate Aggressive Driving Observation Classifications by Date 

(Southbound) 

Date # of Runs Lane 

Straddling 

Illegal 

Passing 

Dangerou

s Merge Police Incident Forced Merge Queue 

9-20-04 12 0 0 5 0 0 0 0 

9-21-04 13 0 0 20 0 0 0 0 

9-22-04 12 0 0 18 0 0 0 0 

9-23-04 11 0 0 12 1 0 0 0 

9-24-04 12 0 0 15 0 0 0 0 

9-27-04 12 0 0 19 0 0 0 0 

9-28-04 12 0 0 26 1 0 0 0 

9-29-04 12 0 0 15 0 0 0 0 

9-30-04 12 0 0 22 0 0 0 0 

10-1-04 10 0 0 22 3 0 0 1 

Total 118 0 0 174 5 0 0 1 
48

Figure 14 highlights the significant differences in observed dangerous merge maneuvers 

for similar time periods at both approaches to the work zone. Since the probe vehicles 

were moving during data collection, an accurate exposure value or dangerous merge rate 

was unknown. While the southbound direction did not experience oversaturated 

conditions making quantitative comparisons difficult, the study team generally noted 

much higher total daily dangerous merge observations even with lower volumes in the 

southbound direction. The percentage of higher northbound traffic is also shown to 

highlight the fact that, even though traffic was lower in the southbound direction, more 

forced merges occurred. 

8

3 1

4 5

0

2

0 1 1

5

20 18

12

15

19

26

15

22 22

9/20/2004

9/21/2004

9/22/2004

9/23/2004

9/24/2004

9/27/2004

9/28/2004

9/29/2004

9/30/2004

10/1/2004

Date

Number of Observations During 

Travel Time Runs

Northbound

Southbound

+16% +30% +33% +29% +14% +29% +33% +31% +34% +21%

Percent Higher NB 

Volumes During Runs

Figure 14. Dangerous Merge Maneuvers by Approach 

 

On the northbound approach, several days included traffic conditions that were sufficient 

enough to activate the DLM “Do Not Pass” flashers. Other days included lighter traffic 

(the flashers remained off). The study team compared traffic changes on the northbound 

approach when the flashers were on and off. This approach has the advantage of 

comparing the traffic and run conditions that existed on the northbound, but it does not 

constitute a true “without ITS” condition because the flashers on the trailer closer to the 

taper were always flashing. The flashers on Trailers 2, 3, 4, and 5, which cover locations 

5, 4, 3, and 2, respectively, were on 2 out of the 10 days during data collection. Also, the 

study team noted police presence 2 of the 8 days the flashers were off. The study team 

excluded data from the days where police were present to avoid issues with traffic 

behavior and pattern changes due to police presence. 

The 2 days that the flashers were on were compared with the 6 remaining days that the 

flashers were off (see Table 14). Comparisons were made on a “per-run” basis, 

addressing the issue of unequal number of runs between the two groups. 
49

Table 14. Statistics for 2 Days Flashers Were On and 6 Days They Were Off 

System Status # of runs Lane Straddling Dangerous Merges Forced Merges Queue

Trailer Flashes Off 79 1 (0.01/run) 18 (0.23/run) 14 (0.18/run) 0

Trailer Flashes On 26 18 (0.69/run) 6 (0.23/run) 2 (0.08/run) 18

The results of the comparisons show that there was a significant reduction in the number 

of forced merges when flashers were on, potentially reducing the risk of collisions near 

the merge taper. Queues were present on the days the flashers were on, indicating that 

vehicles likely merged in advance of the taper to avoid forced merges at Location 6. 

Lane straddling was significantly higher on the days that the flashers were on, indicating 

that some larger vehicles, including trucks, wanted to discourage illegal passing when the 

flashers were on. As shown in the table, the number of dangerous merges and forced 

merges were affected by the flashers. 

Traffic citation information and crash data were also analyzed for both work zone 

approach areas. From July 1, 2004 through October 31, 2004, there were 67 warnings 

and 135 citations issued for violations of the northbound no passing zone. From June 15, 

2004, through October 31, 2004, there were 23 crashes at the northbound work zone 

approach. 

From June 1, 2004, through November 30, 2004, law enforcement officers documented 

14 crashes at the southbound work zone approach. The time period for this data 

collection was longer due to additional activity at the north end of the construction area. 

Sorting data to a less aggregated level would have posed a burden on Sheriff’s Office 

representatives. Therefore, no further analysis was performed. 

Based on the effect of “Do Not Pass” flashers in the work zone, the study team concluded 

that the DLM system enhanced safety by reducing the number of forced merges at the 

lane drop, thus the hypothesis, “The use of ITS enhanced the safety performance of the 

highway during construction,” is valid. The study team was unable to use crash and 

citation statistics to further prove the hypothesis. 

Hypothesis 2: The Use of ITS in Work Zones Will Reduce Traveler Delay 

MDOT also anticipated positive impacts to traveler delay through use of the system. 

Changes in travel times, average speeds, and queue lengths were the main data sources 

sought in the evaluation. The system detectors collected volume, speed, and occupancy 

data in two to three minute time increments. The probe vehicles recorded second by 

second speed data while traversing the corridor. The study team designed the data 

collection plans to use the system detector data to estimate average and maximum queue 

lengths. 

The study team compared travel time data for the northbound and southbound directions 

to determine traveler delay, and analyzed travel time data for the 6 days that the flashers 

were off compared to travel times on the southbound approach. The data indicate that the 

travel times were significantly different even though the traffic volumes were similar. 
50

This result indicates that there were factors other than ITS that influenced the travel times 

in the northbound and/or southbound directions. The differences in road and traffic 

characteristics on northbound and southbound, as well as the length of the probe vehicle 

run necessary to traverse the corridor in each direction, may have affected the travel 

times. 

Therefore, the study team used the same approach used in Hypothesis 1 to compare travel 

times on the northbound approach. The study team compared travel time data for 2 days 

when “Do Not Pass” lights were flashing with data from the 6 days when the lights were 

not flashing. A t-test showed no significant volume count difference between the two 

groups (Pvalue = 0.55). 

The study team found that the travel time when lights were flashing was significantly 

higher than when lights were not flashing (Pvalue < 0.001). This increase in travel time 

(nearly doubled at times from a baseline travel time of 4 to 5 minutes) is expected when 

drivers obey the “Do Not Pass” sign as vehicles potentially reduce speed and merge at 

locations further away from the taper, forming an organized queue of vehicles with 

smoother flow through the bottleneck. Vehicles lining up in the open lane earlier than 

without the flashers increased the distance drivers traveled on the single lane, thus 

increasing the lane density and reducing the speed. Lining up vehicles in the open lane, 

even though slightly increasing the travel time, is a more sound traffic management 

technique than allowing traffic flow breakdown due to forced merges or dangerous 

maneuvers. From these results, the study team deems the second hypothesis, “The use of 

ITS in work zones will reduce traveler delay,” inconclusive. The DLM system, such as 

was used in Michigan, may help reduce traveler delay when traffic is high enough to 

warrant additional activation time.

Analysis of RTMS Sensor Data 

As mentioned previously, the system archived RTMS data at the second, third, fourth, 

and fifth trailers. Traffic demand levels through several of the locations are the same 

because no ramps are present. Figure 15 shows daily vehicle counts from a representative 

RTMS sensor and manual detectors on US 131 between Stadium Rd and route M-43. 

The study team compared RTMS and tube count data for 9 of the 10 days during data 

collection. Data from September the 28, 2004, was discarded because of missing data. A 

paired t-test showed that average RTMS daily counts were 10 percent higher than daily 

northbound tube counts (Pvalue = 0.01). The study team is not able to draw additional 

conclusions from the data other than lessons learned and actions that may enhance the 

quality of data archived. 

MDOT effectively deployed the DLM system on I-94 and, due in part to effective 

enforcement (a qualitative MDOT observation), realized benefits from use of the system. 

As noted from the reduction in aggressive maneuvers, the system positively impacted 

driver behavior and smoothed traffic flow at the work zone taper. One of the two 

hypotheses was proven valid during this evaluation. 
51

Daily Count Totals 

0

5000

10000

15000

20000

25000

9/20/20049/21/20049/22/20049/23/20049/24/20049/25/20049/26/20049/27/2004

9/28/20049/29/20049/30/2004

10/1/2004

Date

Volume

Northbound US 131 (RTMS) Southbound US 131 (Tube Counts) Northbound US 131 (Tube Counts)

missing data 

0630 to 0930 

1530 to 2000 

Figure 15. Daily Traffic Counts by Approach and Detection System 

Tips and Lessons Learned 

Deployment Tips and Lessons Learned 

Educating the police enforcement community about the system when it is first deployed

is extremely beneficial MDOT held meetings with the local police agencies to ensure 

adequate understanding of the system, thereby maximizing the benefits of enforcement. 

Police presence is an important aspect of this type of deployment, as motorists may be 

less likely to violate the no passing zone when police are present. 

Implementing agencies should use the media to the fullest extent possible to help 

educate the public on the deployment. In Michigan, the DOT often invites the media to 

the job site to learn about the system, why it is being used, and how it works. MDOT 

stated that media representatives were a very important stakeholder in the process of 

deploying the lane merge system in Kalamazoo. 

Evaluation and Research Tips and Lessons Learned 

The reliability of the archived data collected was lower than expected. During this 

evaluation, the study team relied on archived data for some of the analysis. The 

reliability was lower than expected potentially due to some communication interruptions 

as detectors sent data back to a main computer. 

Evaluators should observe field conditions to the fullest extent possible and feasible. 

This helps to adequately monitor and validate archived data. 
52

I-30 Little Rock to Benton, Arkansas 

In 1999, Arkansas decided to undertake the rehabilitation of over 50 percent of their 

Interstate highway infrastructure. As a result, in 2000 the Arkansas Highway and 

Transportation Department (AHTD) began rehabilitation and re-construction on more 

than 350 miles of roadway. The AHTD also looked at tools to help mitigate the potential 

impacts from construction. 

Most relevant to the 

study of ITS in 

work zones are the 

three work zones 

that utilized ITS to 

improve traffic 

safety and mobility 

during the time of 

construction. 

Specifically, one of 

the three Arkansas 

projects using ITS 

included the 

widening of 

approximately 17 

miles of I-30 from 

Sevier Street in 

Benton (mile 

marker 115) to 

Geyer Springs 

Road in Little Rock (mile marker 133). A key portion of the work zone is shown in 

Figure 16. The primary objective for using ITS in this location was to improve the safety 

of travelers by providing advance warning of slowed traffic or congested downstream 

conditions. 

Study Site Work Zone 

Prior to the beginning of construction, this 17-mile section of I-30 had an Annual 

Average Daily Traffic (AADT) of 63,000 vehicles. In 2001, as documented by the 

Highway Performance Monitoring System, sections of this stretch of I-30 experienced 

greater than 20 percent truck traffic. According to personnel at AHTD, there is an 

average of approximately 40 percent truck traffic during the day, which increases to 75 

percent at night. The large volumes of truck traffic created the potential for large work 

zone impacts due to their size and impact on mobility. 

The AHTD administered construction in this area for seven projects including widening 

the Interstate to six lanes, removing and replacing the concrete roadway, reconstructing 

nine interchanges, installing a concrete barrier wall in the median, and converting all of 

Figure 16. Arkansas I-30 Work Zone Location 
53

the frontage roads to one-way. The seven projects that made up this extensive work zone 

were as follows: 

1. I-30 from Sevier St. to West of Alcoa Road (from mile mark 115.7 to 119.6) - 

This project included widening the roadway to six lanes, removal and replacement 

of the existing concrete, installation of a concrete barrier wall in the median, and 

conversion of frontage roads to a one-way direction. Completed: Winter 2004.

2. I-30 at the Hwy. 5 Crossover – This project included bridge work at the 

crossover. Completed: March 2003.

3. I-30 at the Alcoa Road Interchange (at mile mark 120.7) - This project 

included removing and replacing the existing interchange. Completed: Spring 

2003.

4. I-30 west of Alcoa Rd. to west of Pulaski Co. line (from mile mark 119.6 to 

125.6) - This project included concrete reconstruction and widening to six lanes, 

modification of the Bryant/Reynolds Road interchange, ramp relocations, 

installation of a concrete barrier wall in the median, and conversion of frontage 

roads to a one-way direction. Completed: Spring 2005.

5. I-30 at the Mabelvale West Interchange (at mile mark 128) – This project 

included removing and replacing the existing interchange. Completed: Summer 

2003.

6. I-30 from west of the Pulaski Co. line to I-430 (from mile mark 125.6 to 

129.7) - This project included concrete reconstruction and widening to six lanes, 

modification of the Alexander interchange, ramp relocations, installation of a 

concrete barrier wall in the median, and conversion of frontage roads to a oneway direction. Completed: Summer 2005. 

7. I-30 between I-430 and Geyer Springs Road (from mile mark 129.7 to 133) – 

This project included concrete reconstruction and widening to six lanes, 

modification of Baseline Road, Mabelvale Pike and University Ave. interchanges, 

ramp relocations, installation of a concrete barrier wall in the median, and 

conversion of frontage roads to a one-way direction. Completed: Winter 2005.

ITS Description 

To improve the safety of travelers, the AHTD installed an Automated Work Zone 

Information System (AWIS) covering the entire I-30 Little Rock to Benton work zone 

corridor. AHTD procured the system from a vendor through the construction contract and 

leased the system for the duration of its use. 

The complete system of monitoring equipment for the I-30 smart work zone included 47 

vehicle detector sensors, 4 radio transmitters, 15 dynamic message signs (DMS), and 8 

stationary video cameras mounted on trailers in and around the work zone. Figure 17 

illustrates the location of the various work zone sensors and message signs. Equipment on 

Highway 5 and Interstate 430 also served to inform motorists when they were 
54

approaching a construction area. After detecting a change in Interstate traffic speeds, the 

AWIS system evaluated its own accuracy by performing a system check of other sensors. 

Within approximately 5 minutes, computers determined whether one of nine levels of 

severity warranted communication with the message boards and radios to report the 

situation. When the sensor system detected significant delays, flashing beacons on HAR 

alert signs advised motorists entering the broadcast area that the message was “Urgent 

When Flashing, Tune To 1490 AM.” 

While the roadside message boards and radios required the 5-minute relay time, sensorrecorded traffic speeds transmitted almost instantaneously to the Web site 

(www.arkansasinterstates.com). Web site visitors were able to see a complete view of 

traffic conditions throughout the work zone (see Figure 17). Color-coded roadway 

segments (green, yellow, red) between sensors indicated whether traffic was flowing, 

slowed, or stopped. Hovering the mouse over any of the equipment icons called up a live 

video image or displayed the text and audio messages motorists were receiving on the 

road. 

 
 55

Signs Radios Cameras 

Normal Traffic Slowing Traffic Stopping Traffic 

 

Figure 17. Overview of I-30, Little Rock to Benton, Arkansas Work Zone1 2

 

1 Map depicting work zone layout courtesy AHTD.

2

 U.S. Geological Survey, from “The National Atlas of the United States of America. General Reference,” 2001. Map courtesy of 

the Perry-Castañeda Library Map Collection at The University of Texas at Austin, 

<http://www.lib.utexas.edu/maps/us_2001/arkansas_ref_2001.jpg> (August 1, 2005).

Overview of ITS in I-30 Work Zone
 56

Measures and Metrics 

The main areas of evaluation for this work zone encompassed the following: safety, user 

perspectives, mobility, and productivity. 

To evaluate these primary areas of interest, the study team developed the following 11 

hypotheses: 

1. The use of ITS in the work zone will reduce travelers’ exposure to hazard. 

2. The use of ITS in the work zone will enhance the safety performance of the highway. 

3. Travelers will use the work zone ITS. 

4. The use of ITS in the work zone will improve trip planning. 

5. The use of ITS in the work zone will improve traveler tolerance of work zone delays. 

6. The use of ITS in the work zone will improve the confidence of travelers driving in the 

work zone. 

7. The ITS information will be readily understood by users. 

8. The use of ITS in the work zone will improve incident response and clearance times. 

9. The use of ITS in the work zone will divert travelers to alternate routes during times of 

work zone congestion. 

10. The use of ITS will improve the productivity of contractors and travelers. 

11. The ITS will be reliable and accurate. 

The study team used the following information sources to assess the hypotheses: 

• Private vehicle driver surveys (a copy of the survey is provided in Appendix A). 

• Commercial vehicle driver surveys (a copy of the survey is provided in Appendix B). 

• State Police personnel interviews. 

• Construction manager interviews. 

• Traffic counts (using tube data and Remote Traffic Microwave Sensor data). 

• System detector data. 

• Personal experience from the study team site visits. 

• Crash data were reviewed but were not feasible to use for this study, as explained in 

the relevant hypothesis below. 

The study team used the driver surveys to asses 8 of the 11 hypotheses. A description of how the 

surveys were administered is provided in Appendix C. The survey responses were coded in a 

database and checked for consistency using statistical analysis software. 

A total of 297 commercial vehicle drivers (CVD) and 319 private vehicle drivers (PVD) 

participated in the surveys. Of these, 286 CVD and 306 PVD surveys were suitable for further 
 57

analysis. The 24 surveys that were not used were discarded due to incomplete responses 

pertaining directly to the ITS devices. The following section presents the findings of the 

analyses pertaining to each hypothesis. Appendix D includes statistical test summaries for each 

of the survey questions. 

Findings 

Hypothesis 1: The Use of ITS in The Work Zone Will Reduce Travelers’ 

Exposure To Hazard 

The objective of the study team was to study this hypothesis using a combination of data 

obtained from a review of crash records, and from surveys of police personnel, private drivers, 

and commercial drivers. 

To answer this hypothesis using crash data, the study team contacted the Arkansas State Police 

(ASP) to obtain crash records for I-30 from two time frames: after the establishment of the work 

zone but before the ITS and after the establishment of the work zone and with the ITS. The 

objective of the study team was to determine if there was a statistically significant reduction in 

the number of crashes from the period with the work zone and no ITS to the period with the work 

zone and with the ITS – indicating a decrease in travelers’ exposure to hazard. Unfortunately, 

crash data were only available in the originally recorded hard copy accident data collection 

forms. Furthermore, in developing an analysis approach based on the crash records, it was 

determined that the complexity of the work zone phasing and configuration would throw any 

results into question. Hence, based on the high cost associated with converting and analyzing 

these data, coupled with the multiple compounding factors noted at this work zone, this means of 

analysis was infeasible. The following list summarizes the major compounding factors 

encountered that may have impacted the potential to develop a sound safety analysis: 

• Prior to implementing the work zone on I-30 in Arkansas, the frontage/service roads were 

two-way frontage roads. These would possibly impact any safety analysis, as I-30 exits 

directly to the frontage road in many instances. 

• Following implementation of the work zone but prior to the ITS, the first stage of 

construction was the rendering of two-way frontage roads into one-way frontage roads. 

This may have skewed the data because it may have contributed to accidents by confused 

drivers. 

• Following the conversion of the frontage roads, the full work zone was put in place along 

with the ITS. The layout of the work zone included two lanes of traffic bounded by 

concrete Jersey barriers with minimal to no shoulders, potentially also impacting the 

safety performance of the work zones. 

• Throughout the frontage road conversion process and the design and re-design of the 

work zone over the various phases of construction, the on- and off-ramp configurations 

changed repeatedly. In some instances, a full stop was required before entering the 

highway; in others, just a yield. In many cases, there was limited roadway length for 

acceleration. 
 58

• The work zone included multiple pavement cuts. In some instances, steel plates covered 

the pavement cuts resulting in possible safety degradation due to an uneven roadway 

surface. 

• The concrete Jersey barriers did not have adequate drainage. According to AHTD 

personnel, heavy rains caused water to channel between the barriers and accumulate on 

the roadways, thus potentially impacting safety during weather events. 

Consequently, the study team addressed this hypothesis using the survey responses to questions 

aimed at gauging whether the drivers felt safer and whether they were better prepared to react to 

hazards or delays. To determine this, two survey questions about the DMS were asked of the 

private and CVDs on I-30. See Appendices A and B for the survey questions and the scale for 

responses used in the survey. 

In total, 292 PVDs and 263 CVDs responded to the question “Because of the info on the signs I 

am better prepared to react to slow or stopped traffic.” The average rating for PVDs was 1.76, 

and for CVDs was 1.68 (where 1 is completely agree and 2 is somewhat agree). These numbers 

indicate that with the electronic messages the drivers felt better prepared to react to slower 

traffic. In fact, 82 percent of the PVDs and CVDs combined (457 drivers) agreed with this 

statement. A single sample one-tailed t-test with 95 percent confidence showed that the drivers 

do agree that the electronic message signs better prepared them to react to slow or stopped traffic 

(see Tables in Appendix D for statistical summaries for each question).

The second question, which asked the driver to indicate whether or not the DMS makes them 

feel safer in the construction zone, had positive responses, but not at the same level as the first 

question. The 292 PVDs and 263 CVDs that answered the second question had an average rating 

of 2.80, which is slightly more agreeable than neutral (neutral equaling 3). The average rating for 

the PVDs alone was 2.81 and for the CVDs alone was 2.78, which indicates similarity in the two 

populations. As illustrated in Figure 3, 49 percent (274) of the 564 drivers that used the DMS 

indicated that the DMS made them feel safer in the construction zone, 17 percent were neutral, 

32 percent disagreed, and 2 percent did not answer this question (See Figure 18). A t-test 

showed that the drivers do agree that the DMS made them feel safer traveling through this 

construction zone. 

These results may indicate that the DMS are indeed reducing driver exposure to hazard by 

making 82 percent of roadway users feel better prepared to react to slow or stopped traffic. This 

result should, however, be carefully considered in light of the finding that about half of the 

respondents (49 percent) actually feel safer as a result of the DMS. 
 59

Agree, 274, 49%

Neutral, 98, 17%

Disagree, 183, 

32%

No Answer, 9, 2%

 

Figure 18. Distribution of Driver’s Opinions on the Statement “DMS Makes Drivers Feel 

Safer in the Construction Zone” (Private & CVDs) 

Hypothesis 2: The Use of ITS in the Work Zone Will Enhance the Safety 

Performance of the Highway 

Initially, the study team planned to use crash records to quantify the safety performance of I-30 

with and without ITS. However, as indicated in Hypothesis 1, the crash data remained in the 

originally recorded hard copy accident data collection forms and was not cost effective to collect, 

organize, and use for this research. 

To answer this hypothesis, interviews with State police personnel and construction project 

management personnel were conducted to determine whether those people most closely tied with 

the work zone felt that the ITS was improving safety. The following are their responses to the 

given questions regarding the safety level of the work zone with the ITS. 

Interview Conducted with Arkansas State Police Personnel 9/27/04 

On September 27, 2004 the Site Coordinator for this project conducted an interview with a 

Captain in the Arkansas State Police who is familiar with the work site. 

1. In your opinion, has the ITS on I-30 improved your incident response capabilities? 

• Yes.

1a. Explain 

• At times, CCTV (closed circuit television) can be used to view the work zone. Also DMS 

is a big help in diverting traffic during an incident. It is better than a patrol car.

1b. Please provide examples: 

• Faster response time - If traffic couldn’t be diverted with the DMS, the only way the 

responding officer could access the incidents on the I-30 work zone was to use the 

frontage road to get close, then climb over the New Jersey barrier to get to the scene. 
 60

• Faster clearance time – Since the traffic is already diverted, startup after clearance is 

quicker. 

Interview Conducted with Project Management Personnel 

In June 2004, the study team conducted an interview with the project management personnel in 

charge of overall activities of the construction project. 

1. Do you feel the ITS had an impact on the safety of the construction workers (in the work 

zone)? 

− Yes.

2. If so, how? 

− Gives early warning to motorists about lane shifts. 

3. Could you provide examples? 

− They had to shift traffic onto the frontage roads three times in a short period and the 

message boards helped them control the traffic. 

4. Do you feel that the ITS affected the number of crashes in the work zone? 

− Yes, it helped slow down traffic. 

5. Do you feel that the ITS affected the severity of crashes? 

− Yes, it helped slow down traffic. 

6. Do you think the ITS helped the authorities in their ability to respond to these incidents? 

− No, I do not think the police used the information from the CCTVs. 

From these interviews, it is evident that the people working within the construction zone feel that 

the ITS has improved the safety of both the workers and the travelers. Some components of ITS, 

such as CCTV, can be further utilized for incident management in work zones. It is interesting 

to note that the police directly stated that the CCTV was useful, while the contracting personnel 

did not believe that the police were using that technology. This may indicate the need for better 

communication between work zone stakeholders. 

Hypothesis 3: Travelers Will Use the Work Zone ITS 

This third hypothesis addresses whether or not the travelers on I-30 used the available work zone 

ITS. For this particular work zone, three primary ITS components helped users determine if they 

should use I-30 or an alternate route. These were as follows: Arkansas’ Pave the Way Web site 

(www.arkansasinterstates.com), DMS throughout the work zone, and the highway advisory radio 

(HAR) station. The surveys asked participants if they had used/seen/heard each of the ITS 

components. The following question was used to obtain ITS usage rates for this section of 

interstate: “Do you use any of the following sources to get information about traffic conditions 
 61

on this section of I-30?” Some of these sources, such as CB radio, local radio, and television, 

were not part of the ITS. 

As shown in Figure 19, drivers of both private and commercial vehicles used DMS most often, 

followed by the sources of information that are not considered ITS, such as television, local 

radio, and CB radio. A great majority of respondents (~95 percent) used the DMS in the work 

zone. This is explained by the fact that the signs are on display throughout the work zone and the 

user does not have to invest any time to locate or use the DMS. Approximately one quarter (24 

percent) of the drivers on I-30 have used the HAR, and about half of those drivers felt that the 

broadcast quality was too poor to hear properly, which could indicate why the usage is so low. 

0%

20%

40%

60%

80%

100%

website DMS HAR CB Television Local radio other

Information Source

% of drivers that used information 

source

CVO

Private

 Figure 19. Distribution of Sources Used to Get Information about Traffic Conditions on I30 

Approximately 7 percent of private drivers and 3 percent of CVDs reported that they had used 

the ITS Web site. Of these people (23 respondents in total), 38 percent had only used the site 

once (usually out of curiosity). Despite this low usage rate it is interesting to note that of all the 

people surveyed (592 combined PVDs and CVDs), 24 percent of the drivers (142 respondents) 

reported that they had heard about the Web site. This indicates that 80 percent of the people that 

had heard about it had not used it. The most common responses as to why the person did not use 

the Web site were: they did not care, did not have the time, or were “too lazy.” 

The study team examined the characteristics of the drivers who visited the Web site. The average 

age of this group was similar to the average age of the non-Web users (80 percent falling 

between the ages of 26-55 with the largest single category being those drivers aged between 36 

and 45). The study team did not perform additional statistical analysis due to the small number of 

drivers who visited the Web site. 
 62

In addition to the survey results, the activity of the arkansasinterstates.com Web server was 

analyzed to determine the extent of usage. The Web site activity is stored in two servers operated 

by AIM Hosting Services; the first server records the non-camera image contents, while the 

second is dedicated to the camera image content. The period of time for which the information 

from both servers was available was August 16, 2004, to September 15, 2004. On average, 200 

users visited the Web site 350 times each day as illustrated in Figure 20. About 68 percent of the 

visitors used the Web page only once per day. On average, 40 people per day visited the camera 

contents. As a whole, these 40 users loaded about 100 pages (each page being an image at a 

certain location) on a daily basis. 

0

100

200

300

400

500

600

700

8/16/2005

8/19/20058/22/2005

8/25/2005

8/28/2005

8/31/2005

9/3/2005

9/6/2005

9/9/2005

9/12/2005

9/15/2005

Time frame

Number of Visits per day

Camera related contents

Non-camera related contents

Figure 20. Activity in Work Zone Webpage Servers (8/16/2005 was a Tuesday) 

The average visit length during the analysis period was about 30 minutes, indicating that users 

likely had some interest in the Web page content. The most active hours on the Web site were 

from 8 a.m. to 9 a.m. and from 5 p.m. to 6 p.m.—showing interest in work zone traffic appeared 

during peak periods. 

The servers also contained data related to the location of the visitors. About 36 percent of the site 

visits identified in the U.S. originated from Arkansas, followed by visits from the states of 

Virginia (32 percent) and Texas (5 percent). The remaining visits included a distribution across 

all other states and unidentified locations. 

These findings help support the hypothesis “Travelers will use the work zone ITS.” The findings 

indicate that DMS are heavily used, HAR is moderately used, and a minimal number of the 

surveyed drivers use the Web site. 
 63

Hypothesis 4: The Use of ITS in the Work Zone will Improve Trip Planning 

This hypothesis addresses the trip planning benefits that users may experience as a result of the 

ITS. The study team examined the hypothesis by analyzing the responses to survey questions 

pertaining specifically to each of the three ITS components (Web site, DMS, and HAR). The 

questions differed by ITS component, as did the findings. 

Web Site 

The two survey questions used to determine if the Web site improved trip planning were: “For 

what reasons do you use the I-30 Web site?” and “The info on the Web site improves my ability 

to avoid delay on this section of I-30.” 

In response to the first question, out of all of the drivers included in this study (592), six drivers 

(1 percent) said that they do use the Web site to plan the route they would take, and two drivers 

(0.3 percent) said they use the Web site to plan the time they would start the trip. Note that this 

percentage is consistent with the statistics garnered from the Web site servers. Given the AADT 

of 63,000 and the average number of Web users (200), the usage percentage comes out 

comparable at .3 percent. Narrowing the scope of the analysis to the 26 drivers who use the Web 

site, 7 were CVDs and 19 were PVDs. Out of the 7 CVDs and the 19 PVDs, 2 CVDs (29 

percent) and 4 PVDs (21 percent) answered that they used the Web site to plan the route they 

will take, and 2 private drivers (11 percent) said they use the Web site to plan the time they 

would start the trip. 

From these 26 drivers, 23 also responded to the second question involving the Web site’s ability 

to improve trip planning. On average, drivers responded with an average level agreement of 2 (2 

indicating that they somewhat agree). A t-test with 95 percent confidence level showed that the 

23 drivers agree that the Web site was able to improve trip planning. From these two survey 

questions, one can infer that the Web site had a low usage, but its few users believed the Web 

site helped them in trip planning. 

DMS 

To determine if users readily understood the DMS, the study team studied the responses to the 

following three questions: 

• “Has the information on the signs ever caused you to exit this section of I-30 to find an 

alternate route?” 

• “The messages are detailed enough to help me make decisions about my route.” 

• “The signs are located in the right places to help me make decisions about my route.” 

Two hundred fifteen CVDs and 239 private drivers responded to the first question. Of these 

respondents, 20 percent (44) of the CVDs and 50 percent (120) of the PVDs said that the signs 

have caused them to change their route. The low number of CVDs that responded positively is 

most likely due to the fact that truck drivers do not have very many alternate routes, as heavy 

vehicles are only allowed on certain roads. During the interviews, the CVDs made it clear that in 
 64

most cases, once they had taken a route, it was too late to change it regardless of the traffic. A 

PVD can take any exit available. 

In response to the other two questions, on average, both CVDs and private drivers indicated that 

they somewhat agree that the signs are detailed enough and are located in the correct places for a 

different route to be taken if there is significant delay. Using a t-test with 95 percent confidence, 

drivers indicated that they agree that the DMS contain enough detail and are located in the 

correct places. 

Considering the agreement of drivers in response to these questions, and the fact that 50 percent 

of the private drivers who answered the first question said that they have used the DMS for 

advisories as to whether to stay on I-30, there is some indication that DMS in the work zone 

assisted in providing drivers with the information required to make routing decisions. The 

effectiveness of DMS on trip planning depends on how far upstream the messages are delivered. 

This is especially true for commercial vehicle travel. 

HAR 

The study team used the responses from two questions to assess the utility of HAR. These two 

questions are: “Have the highway advisory radio messages ever caused you to exit this section of 

I-30 to take an alternate route?” and “The messages are detailed enough to help me make 

decisions about my route.” 

For the first question, 17 CVDs out of 286 (6 percent) and 30 private drivers out of 306 (10 

percent) said that they had taken an alternate route due to the HAR. Similar to the responses 

related to the DMS benefits, a lower percentage of CVDs used the HAR to make decisions about 

their route. 

The average rating for the second question was 1.93, indicating that the drivers agreed (1 is 

completely agree; 2 is somewhat agree) that the messages were detailed enough to help them 

make decisions about the routes. The same trend described in the previous question holds in this 

case, where more private than commercial drivers agree that messages are detailed enough to 

make decisions about their route. However, with the low number of users, it is difficult to say 

whether the HAR is improving trip planning. 

Hypothesis 5: The Use of ITS in The Work Zone Will Improve Traveler 

Tolerance of Work Zone Delays 

To answer this hypothesis, responses were reviewed from the following survey question: “Just 

having the information makes me feel less bothered by the delays in the construction zone.” 

This question applied to two components of the ITS: the DMS and the Web site. For the DMS, 

both PVDs and CVDs were asked to rank their agreement with the stated question. For the Web 

site, only private drivers were asked. For both the Web site and the DMS, responses averaged a 

“neutral” or “somewhat disagree” level of agreement with the given statement. Figure 21 shows 

the distribution of responses for the DMS. Figure 22 presents the distribution of the responses 

from the private drivers for the Web site. 
 65

 

257 CVO and 286 PVDs 

Average = 3.05

(5) Completely 

disagree

30%

(3) Neutral

23%

(2) Somewhat 

agree

18%

(1) Completely 

agree

21%

(4) Somewhat 

disagree

8%

Figure 21. Distribution of Responses to the Statement, “Just Having The DMS 

Information Makes Me Feel Less Bothered By The Delays In The Construction Zone.” 

18 Private Drivers 

Average = 3.28

(5) Completely 

disagree

39%

(4) Somewhat 

disagree

17%

(3) Neutral

11%

(1) Completely 

agree

33%

Figure 22. Distribution Of Responses To The Statement, “Just Having The Web site 

Information Makes Me Feel Less Bothered By The Delays In The Construction Zone.” 

Although the average rating for the participants was neutral, about 39 percent of drivers (215 

drivers) agreed that having the information on DMS made them feel less bothered in driving 

through the construction zone. The DMS messages were general in terms of traveler/delay 

information (e.g. specific travel times were not posted) and changed based on speed thresholds. 

They also posted specific mile-marker information. For the Web site, 6 of the 18 drivers (~33 

percent) agreed that the information on the Web site made them feel less bothered in driving 

through the construction zone. 

Hypothesis 6: The Use of the ITS in the Work Zone Will Improve the Confidence 

of Travelers Driving in The Work Zone 

To determine if ITS improves traveler confidence, the responses to the following questions were 

used: “Because of the info on the signs, I am better prepared to react to slow or stopped traffic” 

and “I feel safer traveling through this construction zone because of the electronic messages.” 

Both CVDs and private drivers received these questions, but the questions pertained only to 

DMS (not the Web site or HAR). DMS was the focus of this question because once in the midst 

of the work zone, DMS is the only form of ITS immediately accessible; it does not require 

DMS 

Web site 
 66

internet or a radio. These questions also served to partially answer Hypothesis 1 (the use of ITS 

in the work zone will reduce traveler’s exposure to hazard) because drivers’ confidence and 

drivers’ exposure to hazard are closely related. As discussed in Hypothesis 1, a t-test with 95 

percent confidence showed that the drivers agreed that the DMS better prepared them to react to 

slow or stopped traffic and made them feel safer traveling through the construction zone. 

Assuming that drivers feel more confident when they are better prepared to stop or slow down, 

the evidence presented here supports the hypothesis under investigation. 

Hypothesis 7: The ITS Information Will Be Readily Understood By Users 

Survey questions for each of the three components of ITS (Web site, DMS, and HAR) served to 

answer the given hypothesis for drivers of both private and commercial vehicles on I-30. The 

two questions differed for the different components of ITS, as did the findings. Each of the 

components will be discussed separately to answer this hypothesis. 

Web Site 

The responses the drivers gave to the question requesting level of agreement with the statement 

“The Web site is easy to use” served in the study of whether drivers readily understood the Web 

information. Twenty-four drivers answered this question, and twenty-three of them agreed that 

the Web site was easy to use. The 24th driver (a CVD) gave a neutral answer to this question, 

which may be due to the driver only visiting the Web site once. With overwhelming agreement 

of the few Web site users surveyed (24), one can conclude that the Web site is easy to use. 

DMS 

The responses to two questions served to address the seventh hypothesis pertaining to DMS. 

These two questions requested a ranking of agreement with the statements “The messages are 

easy to understand” and “The messages are detailed enough to help me make decisions about my 

route.” 

About 94 percent of CVDs (269 drivers) and 96 percent of PVDs (295 drivers) said “yes,” they 

had used the DMS. Of these respondents, 261 CVDs and 287 private drivers responded to both 

questions. The drivers who responded to both questions strongly agreed the messages were easy 

to understand. They gave an average rating of 1.26, where 1 means completely agree and 2 

means somewhat agree. They also agreed that the messages were detailed enough to help them 

make decisions about their route. The average rating for this question was 1.78. Both of these 

findings were significant at a 95 percent level. These findings indicate that the DMS messages 

were easy to understand and that the DMS were detailed enough to help drivers to make 

decisions about their routes. 

HAR 

The responses to the following two questions facilitated the study of Hypothesis 7 pertaining to 

HAR. These two questions requested ratings of the statements: “The radio broadcast quality is 

too poor to hear properly” and, “The messages are detailed enough to help me make decisions 

about my route.” 
 67

About 24 percent of CVDs (69 drivers) and 24 percent of PVDs (74 drivers) said “yes,” that they 

had used the HAR. Of these respondents, 60 CVDs and 64 private drivers responded to both 

questions. Of these combined 124 drivers, the average response to the quality of the broadcast 

was 2.57 (where 2 means somewhat agree and 3 means neutral). However, the drivers did agree 

that the messages were detailed enough to help them make decisions about their route. The 

average rating for this question was 1.93. Both these findings were significant at a 95 percent 

level. From this, one can conclude that about half of the people who would like to use the HAR 

can hear the broadcast clearly. When they could hear it, the broadcast was understood and 

detailed enough on average. Perhaps the proper course of action would be to increase the signal 

strength so more people who would like to use the HAR are able. 

Hypothesis 8: The Use of ITS in The Work Zone Will Improve Incident Response 

and Clearance Times 

Incident response and clearance times with and without ITS in the work zone could not be used 

for comparison because the data were unavailable. To answer this hypothesis, an interview with 

police personnel was used to determine if the police department felt that the incident response 

and clearance times improved due to the ITS. The following are the interview responses. 

Interview Conducted With a Captain and a Dispatcher at the Arkansas State Police 

The Captain indicated that the ITS on I-30 improved their incident response capabilities. He 

explained that at times, CCTV could be used to view the work zone. He also noted that the DMS 

is a big help in diverting traffic during incidents; it was better than a patrol car. The Captain 

provided the following examples: 

• Faster response time - If traffic couldn’t be diverted, the only way the responding officer 

could access the incidents on the I-30 work zone was to use the frontage road to get 

close, and then climb over the New Jersey barrier to get to the scene. 

• Faster clearance time – Since the traffic is already diverted, startup after clearance is 

quicker. 

The interviewer also spoke with a radio dispatcher working with the state police who suggested 

some improvements to the ITS. The interviewer summed up the dispatcher’s comments with the 

following statement: 

The dispatcher preferred to see live images of the work zones. The dispatcher 

had to “refresh” the image anytime she needed to see what was going on. This 

occurred whenever a cell phone call reporting an incident was received. Work 

zone images were of limited value because the actual crash site was not always 

in the image. The dispatcher would have preferred to have more cameras or to 

have pan, tilt, zoom (PTZ) abilities so they can focus on the crash site. 

It was also said that the CCTV could help determine what emergency vehicles 

needed to respond to incidents. However, given the camera image quality and 

standard operating procedures, the police said a trooper had to actually be on the 
 68

scene to make this determination. They may believe this because they do not 

have PTZ ability that would allow them to most effectively use the CCTV. 

These were some suggestions to further improve the ITS utility to the state police. From these 

responses, it can be seen that the State police department does feel that the ITS in the work zone 

somewhat improves response and clearance times; however, effective and efficient response 

could be greatly improved by the addition of greater camera functionality. 

Hypothesis 9: The Use of ITS in the Work Zone Will Divert Travelers to Alternate 

Routes During Times of Work Zone Congestion 

To answer this hypothesis vehicle counts were taken at six exit ramps, DMS message records 

were collected for 15 message boards, and mainline volume counts were collected for I-30 at 

each of the off ramp locations (see Figure 23 and Table 15). The study team collected these data 

over a 4 day time span between Monday, May 17, and Thursday, May 20, 2004. The goal was to 

correlate the off-ramp volumes and mainline volume data with the messages displayed on the 

upstream DMS. 

Figure 23. Location of Ramps Used for Hypothesis No. 93

 

3

 Map courtesy of the Arkansas Highway and Transportation Department Map Planning Section 

(http://www.ahtd.state.ar.us/maps/2004%20state%20highway%20map/statehwymap3-8-04_state.pdf). 

Exit 123 (EB Ramp)

Exit 126 (EB & WB Ramps)

Exit 128 (EB Ramp)

Exit 129 (WB Ramp)

Exits 130 & 131 

 (WB Ramps) 
 69

Table 15. Location of DMS Used for Hypothesis No. 9 

 

Message Board ID Highway Direction Mile Marker

S01 I-30 EB 111

S02 I-30 EB 114

S03 I-30 EB 116

S04 I-30 EB 118

S05 I-30 EB 122

S06 I-30 EB 126

S07 I-30 EB 128

S08 I-30 WB 136

S09 I-30 WB 128

S10 I-30 WB 126

S11 I-30 WB 123

S12 H-5 EB

S13 H-5 EB

S14 H-5 WB near 430

S15 I-430 EB

Unfortunately, the data sets contained large gaps in the data and much of the message board and 

exit ramp data was unusable because the DMS were too far from the ramps to assume that the 

drivers reading the boards would exit at the given ramp. After combining the useable data, the 

only data left was from four off ramps (eastbound exits 123, 126, and 128; westbound exit 126), 

each with an average of 2 days of consecutive data, including one upstream DMS and the 

corresponding mainline volume counts. Over the full useable data set, there were 12 separate 

instances when ramp volumes were available and the DMS (at eastbound exits 123, 126, and 

128; westbound exit 126) displayed “Delays Possible” messages. Seven of the 12 cases happened 

during the peak a.m. or late afternoon, and the other five cases occurred during the night (when 

there were lower volume counts). 

From this data there was not enough evidence to suggest a relationship between the DMS 

messages and diverting traffic. For example, on May 17, 2004, the DMS upstream of the 

eastbound ramp at exit 128 displayed delay messages for short periods of time, while volumes on 

ramp fluctuated from 10 to 36 vehicles in a 15-minute period. While on May 17 the DMS 

message remained the same, the ramp volume fluctuated by a factor of three. On May 18 and 

May 19, ramp volume fluctuated with a similar magnitude but no delay messages were 

displayed. Thus, the data did not indicate a clear association between ramp traffic volume and 

the display message. 

In examining the peak a.m. cases, large volumes of traffic exited I-30 at the same time the DMS 

were displaying “Delays Possible.” It would seem that the messages were, indeed, diverting 

traffic. However, these diversions could easily be due to normal trip planning; the exiting 

travelers may have been planning on getting off at the given exit regardless of the traffic 

conditions. Given these confounding factors, more data is needed to answer the hypothesis “The 

use of ITS in work zones will divert travelers to alternate routes during times of work zone 

congestion.” 
 70

Hypothesis 10: The Use of ITS Will Improve the Productivity of Contractors and 

Travelers (Both Private and Commercial) 

This hypothesis includes two sections: improving productivity for contractors and improving 

productivity for travelers. To address the section on travelers the survey data were used. The 

survey questions used for this hypothesis were the same as Hypothesis 4 and, consequently, 

results for these two hypotheses were the same. The following are the conclusions from 

Hypothesis 4: 

• Web site – It has the potential to improve the productivity of travelers. Even though the 

servers show a stable number of daily visits, the Web site usage among the surveyed 

drivers was very low. 

• DMS –They appear to be improving the productivity of travelers. 

• HAR – It appears to be improving productivity for those drivers who use it. 

To answer the question of improving productivity for contractors, a separate questionnaire was 

developed. The work zone project contract manager responded to this questionnaire during an 

in-person interview. The questionnaire contained four questions applicable to this hypothesis; 

two of these were direct questions and two were indirect. 

The two indirect questions were “Do you feel the ITS had an impact on the safety of the 

construction workers (in the work zone)?” and “Do you feel the ITS helped you or your 

subcontractors to carry out the construction?” 

For the first question the response was: “Yes... Gives early warning to motorists about lane 

shifts. They had to shift traffic onto the frontage roads three times in a short period and the 

message boards helped them control the traffic.” For the second question, the interviewee 

agreed that the ITS helped carry out the construction for planning and implementing lane 

closures, and planning and implementing alternate routes, but not for planning for and changing 

on-and off-ramp configurations. These questions add insight to the situation but do not answer 

the question posed. 

The two direct questions were, “Did the ITS have a negative impact on any of your operations?” 

and, “Do you feel that the ITS improved your productivity (or your subcontractor’s productivity) 

by helping you complete the work?” 

For the first question the answer was yes, there were negative impacts caused by the ITS. The 

interviewee stated, “The portable CCTV got in the way of construction operations and the 

contractor had to have them moved.” For the second question the answer was no, the ITS did not 

improve productivity. He commented, “The message boards were spread out too far to be a big 

help.” The results indicated that ITS in the work zone may not directly improve a contractor’s 

productivity but may help them indirectly to manage the work zone better. 

Hypothesis 11: The ITS Will Be Reliable and Accurate 

The study team relied on two data sources to answer this hypothesis: 1) traffic volume data 

collected by the ITS were compared to AHTD maintained RTMS traffic volume data to verify 
 71

the ITS accuracy, and 2) survey data were used to determine if drivers found the ITS reliable and 

accurate. 

To verify the accuracy of the ITS traffic volume counts, AHTD collected the traffic volume data 

for the period from May 21 to June 20, 2004, which was compared to corresponding data 

archived by the ITS. Each of the two databases had some missing sections of data. Days with 

missing data were removed to prevent a biased selection of hours (night or day hours). In all, the 

data used represented 10 full days between June 2 and June 16. A total of 240 hourly volume 

pairs were analyzed for both eastbound and westbound volume counts along I-30. Figure 13 

shows the detector location at Raymar Rd. 

The study team compared volumes from detectors number 62 and 26 (from ITS) to the I-30 

volumes AHTD collected at Raymar Rd. overpass (Figure 24). Note that the distance between 

the overpass and location of the ITS sensors was not substantial and no point of exit occurred 

within that distance. For the 10-day period, the ITS-counted eastbound traffic volume (detector 

26) was 543,606 and the AHTD-counted volume was 407,046 vehicles. For the same period, the 

ITS-counted westbound traffic volume (detector 62) was 604,242, and the AHTD-counted 

volume was 437,026 vehicles. The ITS-counted volumes were 34 percent higher for eastbound 

traffic and 38 percent higher for westbound traffic than the AHTD volumes. The ITS eastbound 

and westbound volumes combined were 36 percent higher than the combined AHTD volume. A 

t-test showed that the combined volume from the ITS detectors was significantly different with a 

95 percent confidence level. These findings suggest that the westbound ITS detector was tallying 

additional traffic (perhaps part of the eastbound traffic) and the eastbound ITS detector was 

tallying additional traffic (perhaps part of the westbound traffic) at these locations. 

Figure 24. Locations of Detectors Used for Hypothesis 114

Additionally, a comparison was made between the data from the ITS detectors (numbers 63 and 

25) neighboring the detectors in question and the AHTD data at the Raymar Rd. overpass. 

Results showed an average underestimation of 64 percent for eastbound volumes and 

overestimation of 65 percent for westbound volumes by the ITS detectors. However, the ITS 

eastbound and westbound volumes combined were less than 1 percent lower than the AHTD 

data. A t-test showed that the combined volume from the ITS detectors was not different than the 

AHTD data with a 95 percent confidence level. 

 

4 Note: occupancy in this case is a measure of vehicle density in the lane. 

N 

E

I-30 To Bryant. 

I-30 To Little Rock 

Raymar Rd. 
 72

The data collected by AHTD served as the reference volume because the eastbound and 

westbound daily volumes and the volumes over the whole study period were similar. The 

volumes on both directions are expected to be similar at this location because the work zone is 

located within a populated area where local drivers travel in both the eastbound and westbound 

directions. In addition, intercity drivers would use I-30 in both directions without a significant 

bias toward one direction. 

To determine the impact of this calibration on the messages that users would see, a study of the 

corresponding DMS data was undertaken. The study team also compared messages displayed on 

DMS located on the eastbound at mile post 122 (called S05) to the speed, volume, and 

occupancy data collected at ITS detectors 25 and 26 to determine if there was a correlation. The 

comparison showed that the displayed messages did not match the data from detector 25, but 

there was some correspondence between the messages and the data from detector 26. For 

example, when the vehicle count at detector 26 was about 3300 vph and the average speed 

dropped below 40 mph, the sign displayed the message: “slowing traffic ahead, at mile marker 

123, delays possible.” It is reasonable to expect similar volumes at detectors 25 and 26 due to 

their proximity. Thus, the traffic conditions at detector 25 should similarly correspond to the 

displayed messages. However, the vehicle counts at detector 25 never exceeded 1338 vph in the 

10-day-period and so did not trigger the above mentioned messages. 

Similarly, the study team compared messages displayed on the DMS located on the westbound at 

mile post 126 (called S10) to the speed, volume, and occupancy data collected at ITS detectors 

62 and 63. The data showed that the displayed messages did not correspond to the data from the 

detectors. Detectors 62 and 63 indicated significant changes in traffic conditions, with 

fluctuations on vehicle counts from 1000 vph to 4000 vph and average speeds from 55 mph to 40 

mph. But, the displayed message on the DMS during the whole 10-day period was: “Buckle Up, 

Drive Safely, Caution Trucks Entering And Leaving The Roadway.” 

Based on these comparisons, the study team concluded that while the combined volume from 

ITS detectors 25 and 63 was similar to the volume from AHTD, the directional volumes were 

significantly different. For ITS detectors 26 and 62, the combined volume was significantly 

higher than the AHTD volume. As a result, it seems that the ITS detectors were not counting the 

directional volumes accurately at these locations during the analysis period. Whether the 

detectors were working accurately at other time periods or the detectors at other locations were 

working properly is not known because no reliable reference data is available for comparison. It 

should also be noted here that the configuration of the work zone was very complex and the ITS 

sensors were often operating in areas with minimal room for adjustment. As a result, the sensors 

could “cross-shoot” lanes if not properly readjusted to the work zone layout. 

To perform additional analysis regarding the perceived accuracy of the system, survey questions 

for each of the three types of ITS (Web site, DMS, and HAR) were asked of the PVDs and 

CVDs on I-30. All of the questions were “rate-your-agreement”-style questions. The questions 

differed for the different components of ITS, as did the findings. Each of the components will be 

discussed to answer this hypothesis. 
 73

Web Site 

The response to the following question requesting a level of agreement with the statement “The 

info on the Web site is accurate” served to determine if the Web site was giving accurate 

information as perceived by the users. The average rating of the 24 drivers who answered this 

question was a 1.7. This value falls between completely agree (1) and somewhat agree (2). 

Using a t-test with 95 percent confidence, the drivers agreed that the Web site was giving 

accurate information. 

DMS 

The responses to the following question requesting the ranking of agreement to the statement 

“The messages are accurate” served to assess the accuracy of the messages given by DMS. 

Ninety-four percent (269) of CVDs and 96 percent (295) of private drivers responded “yes” to 

using DMS. Of these respondents, 256 CVDs and 287 private drivers responded to the question 

regarding the accuracy of the signs. The average rating of these combined 543 drivers to the 

DMS message was 1.75. Performing a t-test for the responses shows that the drivers found the 

DMS messages accurate at a 95 percent significance level. These findings support the conclusion 

that participants feel the DMS were giving accurate messages. 

HAR 

The responses from three questions were used to assess the utility of HAR. These three 

questions requested participants to rank their level of agreement with the following statements, 

“The messages are useful,” “The messages are accurate,” and “The messages are updated 

frequently enough.” 

Twenty-four percent (69 drivers) of CVDs and 24 percent (74 drivers) of PVDs responded “yes” 

to using HAR. Of these respondents, 60 CVDs and 56 private drivers responded to all the three 

questions stated above. Of these combined 116 drivers, the average response to whether the 

messages were useful was 1.74 (a rating higher than for “somewhat agree”). The average 

response to the accuracy was 2.0, or somewhat agree. The average response for whether or not 

the messages were updated frequently enough was 2.27, or somewhat agree. Using a t-test at 95 

percent significance showed that the drivers agreed that HAR was useful, accurate, and updated 

frequently enough. 

The specific statistical summaries for each set of survey question responses can be found in 

Appendix D. 
 74

Summary of Findings - Arkansas 

The analysis presented in this report represents multiple sources of data, analysis methodologies, 

and outcomes. The following Table presents a summary of the findings for each hypothesis 

including comments on the analysis. 

Table 16. Summary Findings for Each Hypothesis 

Hypothesis Findings Comments 

The use of ITS in 

the work zone will 

reduce traveler’s 

exposure to 

hazard. 

Drivers agree that the ITS in the 

work zone reduced their exposure 

to hazard. 

A large percentage of the surveyed 

drivers (82%) agreed that the ITS 

system improved their ability to 

react to slow or stopped traffic 

A large percentage of surveyed 

drivers (49%) agreed that they felt 

safer traveling through the work 

zone because of the electronic 

messages, 17% were neutral, 32% 

disagreed, and 2% did not answer. 

The use of ITS in 

the work zone will 

enhance the 

safety 

performance of the 

highway. 

The police officer and construction 

manager in the work zone agreed 

with this hypothesis. 

People working within the 

construction zone feel that the ITS 

has improved the safety of both the 

workers and the travelers. 

Travelers will use 

the work zone ITS. 

Travelers used the components of 

the ITS that were most available. 

The highly-used DMS were present 

in the work zone making them 

readily available to drivers to read. 

HAR was used moderately. The 

Web site had a low utilization 

among the surveyed drivers 

DMS was observed by 95% of 

surveyed drivers. 

HAR was used by 24%. 

Web site was used by 5%. 

Web site: Improves trip planning, 

but the usage among the surveyed 

drivers was very low. 

The Web site does improve trip 

planning, but only 5% of surveyed 

drivers used it. On average, 350 

daily visits were registered in the 

Web site from August 16 to 

September 15, 2004. 

DMS: Improves trip planning for 

PVDs, but has a lower impact for 

trucks. 

DMS in the work zone improve trip 

planning for PVDs (50% 

agreement). CVDs have a fixed 

route and DMS are less effective for 

trip planning. 

The use of ITS in 

the work zone will 

improve trip 

planning. 

HAR: Some of the people who used 

it improved their trip planning. 

24% of drivers used the HAR to 

improve their ability to plan their 

routes. 

The use of ITS in 

the work zone will 

improve traveler 

tolerance of work 

zone delays. 

ITS improves tolerance for at least 

some drivers. 

About 1/3 of the drivers said the use 

of ITS make them feel less bothered 

in the construction zone. 
 75

Hypothesis Findings Comments 

The use of the ITS 

in the work zone 

will improve 

traveler 

confidence driving 

in the work zone. 

The DMS improve traveler 

confidence for most drivers. 

Drivers’ confidence is increased 

because their ability to react to slow 

or stopped traffic is increased, and 

they feel safer driving through the 

construction zone. 

Web site: Readily understood. 

With almost unanimous agreement, 

one can conclude that the Web site 

is easy to use or readily understood 

by users. 

DMS: Readily understood. 

Information is easy to use and 

detailed enough for the majority of 

the I-30 users. 

The ITS 

information will be 

readily understood 

by users. 

HAR: Understood by only those 

who could hear the broadcast 

clearly. 

Increase the signal strength so that 

more people can use the HAR. 

The use of ITS in 

work zones will 

improve incident 

response and 

clearance times. 

ITS assists professionals with 

incident response and clearance 

times. 

ITS does help improve incident 

response and clearance times; 

however, it can be improved to 

enhance its utility. 

The use of ITS in 

work zones will 

divert travelers to 

alternate routes 

during times of 

work zone 

congestion. 

Not enough data to state any 

findings. 

Data were collected for 7 off ramps 

and 15 DMS over 4 days; however, 

conclusive findings were not found. 

Contractors: ITS does not improve 

productivity, but ITS does help 

manage the work zone better. 

ITS had some negative impacts on 

construction operations (portable 

closed circuit video unit got in the 

way) and did not improve 

productivity, but using the ITS 

system for traffic management 

helped manage the work zone. 

The ITS will 

improve the 

productivity of 

contractors and 

travelers. 

Travelers: ITS improves motorists’ 

ability to plan their trips. 

The Web site had a low usage (5%), 

but its few users believed the Web 

site helped them in trip planning. 

Drivers felt that the Web site was 

accurate. 

The Web site gives accurate 

information, but its use is very 

limited by surveyed drivers (5%). 

The ITS will be 

reliable and 

accurate. 

DMS are accurate enough for the 

majority of the users. 

Most drivers (79%) felt that the DMS 

messages were accurate. 
 76

Hypothesis Findings Comments 

Drivers felt that HAR was useful, 

accurate, and frequently updated. 

Of the 24% of drivers who use HAR, 

81% said the HAR is useful, 

accurate, and updated frequently. 

Directional volume counts by work 

zone ITS differed significantly from 

data collected by AHTD. 

At one location, traffic volume was 

overestimated by 34% on the 

eastbound and overestimated by 

38% on the westbound direction. A 

second set of detectors revealed an 

underestimation of 64% on the 

eastbound and overestimation of 

65% on the westbound. 

Tips and Lessons Learned 

Deployment Tips and Lessons Learned 

Work zones are highly variable environments. As a result the ITS must be similarly flexible. 

For example, the work zone examined here was large, complex (included 7 separate projects by 

2 contractors), and had a constantly changing configuration. As a result, the calibration of the 

ITS became a major issue requiring one full-time employee working long hours to maintain all 

sensors. 

ITS is only one part of a successful work zone. The aim of outfitting this work zone with ITS 

was to improve safety. While there is some indication that the ITS system reduced travelers’ 

exposure to hazard and made the work zone safer, fatal crashes in the I-30 work zone were not 

fully avoided. ITS can be a valuable part of effective work zone management, but other safety 

and mobility strategies should also be used as part of a coordinated transportation management 

plan (TMP). 

The recognition of system requirements by all parties affiliated with the work zone and ITS 

deployment is key. For example, the emergency dispatchers’ use and requirements for the 

system are very different from those of the contractors. A more detailed study of user 

requirements coupled with revised operating procedures may enhance the system’s capability to 

improve safety and mobility. 

Advertising the Web site to a greater audience in various media is important. This is especially 

true given the high level of satisfaction experienced by the work zone ITS Web site users in 

comparison to the low level of the number of users. 
 77

Evaluation and Research Tips and Lessons Learned 

Obtaining crash records can be more difficult than presumed. The lack of existing electronic 

crash records in a maintained database rendered several of the safety hypotheses infeasible for 

study by any means other than user surveys and interviews. 

Development of a data collection plan should include some forecasting or methodology to 

accommodate data providers or key stakeholder personnel that may be retiring. For example, 

difficulties experienced in obtaining police records were compounded by the retirement of the 

police chief. 

Data collection activities should be coordinated as closely as possible with the construction 

contractors. For example, tubes in place to collect ramp volume data had to be moved before 

the end of the designated collection period due to construction on the selected ramp.
 78

I-40 Winston – Salem, North Carolina

Over the past several years, the North Carolina Department of Transportation (NCDOT) has 

undertaken several construction projects involving the deployment of ITS technologies to help 

mitigate the impacts to traffic. NCDOT sought to alleviate work zone issues such as back-ofqueue crashes and traffic delays caused by capacity reductions and movement of materials and 

trucks to and from work sites via open travel lanes. NCDOT has successfully deployed several 

ITS systems in different work zones across the state. Benefits from those early deployments 

included enhanced real-time information for motorists on downstream conditions, better trip 

planning through information dissemination via Web sites, as well as no fatal crashes. 

In early 2004, NCDOT designed an ITS system for a work zone shown in Figure 25 on Interstate 

40 west of Winston Salem. The goal of the ITS system was to monitor conditions and improve 

mobility and safety through the work zone along I-40 between the NC 801/I-40 interchange in 

Davie County and the SR 1101/I-40 interchange in Forsyth County.

 

Figure 25. I-40 Work Zone and Signed Alternate Routes 

Based on predetermined delay and travel time thresholds, the system provided real-time delay 

information and, if delays exceeded 25 minutes, recommended alternate routes via dynamic 

message signs (DMS). 

The main objectives of the system were to: 

 Reduce demand and congestion (by actively diverting traffic). 

 Provide delay information to warn motorists of slowed traffic ahead. 

Construction Area 
 79

 Provide information to commuters and DOT personnel via a Web site. 

 Build public confidence in real-time traveler information. 

The main objectives of the evaluation were to: 

 Determine traveler response to the work zone information. 

 Determine the effect of traveler response on traffic conditions. 

 Verify that the work zone ITS functioned as designed. 

Study Site Work Zone 

NCDOT installed the work zone between milepost (MP) 180 and MP 184, west of WinstonSalem. This section of I-40 is a four lane divided rural Interstate that has Annual Average Daily 

Traffic (AADT) of 48,000 vehicles per day. NCDOT set up lane closures in each direction in 

order to rehabilitate pavement and replace deteriorating concrete slabs. 

NCDOT began construction on March 23, 2004, with three phases of work. In Phase I, NCDOT 

milled and paved shoulders and set up off-peak lane closures. In Phase II they replaced concrete 

slabs and implemented contract provisions allowing for 72-hour lane closures. In Phase III they 

closed lanes for paving operations and restricted work to nighttime hours. They also planned to 

perform concurrent bridge painting/maintenance work on I-40 approximately 5 miles east of the 

work zone. Due to schedule changes, they performed the work later in the summer after Phase III 

was completed. NCDOT also had to modify the original system configuration to account for the 

bridge painting/maintenance project. 

Generally, the construction contract did not permit lane closures Monday through Friday 

between 6 a.m. and 9 a.m. (eastbound) and between 4 p.m. and 7 p.m. (westbound) as part of a 

strategy to lessen impacts to traffic. However, the contract permitted lane closures during Phase 

II (slab replacement) for up to 72 hours for concrete curing. The contract prohibited lane 

closures during special events or on holidays. 

ITS Description 

NCDOT designed the ITS system to monitor traffic conditions within and in advance of the work 

area from each direction. The system components included: 

• A central base station equipped with processing software and wireless 

communications to link the system components.

• 10 portable DMS remotely controlled via the central computer base station.

• 10 portable traffic sensors linked to the central computer base station.

NCDOT designed the system as shown in Figure 26. They re-mobilized it several times 

throughout the summer, and used an alternate configuration later in the deployment for the 

separate bridge painting project with weekend lane closures. NCDOT procured the system using 

a special provision through the prime construction contract. 
 80

Figure 26. I-40 Smart Work Zone Deployment Near Winston Salem 

NCDOT designed the system to provide real-time operational status of the work zone via the 

central base station computer and via the Internet on a dedicated project Web site. They also 

designed it to notify the appropriate personnel, by pager and email, when a malfunction occurred 

in the system or once the delay through the work zone exceeded 25 minutes. They programmed 

the system to display appropriate messages and alternate route information via the DMS when 

warranted. 

Each traffic sensor communicated with the computer base station to activate the appropriate 

DMS whenever the prevailing traffic speed slowed to 55 mph. Once the system activated, it 

automatically displayed the preprogrammed delay messages in real-time on the DMS. NCDOT 

designed the system to calculate, via simple algorithms, real-time delay for display on the 

portable DMS. The system calculated delay and displayed information on the portable DMS to 

the nearest minute for delays up to 15 minutes after a 5-minute delay was observed. For delays 

exceeding 15 minutes, the system displayed information on the DMS rounded to the nearest 5-

minute increment. The system posted updated delay information every minute. The Web site 

updated delay information simultaneously with the information displayed on the DMS. 

For westbound traffic, the system encouraged motorists to take 421 west from Winston-Salem, 

and then to take either 601 south or I-77 south to rejoin I-40. For eastbound traffic, the system 

encouraged motorists to take 601 north at exit 170, then 421 east to rejoin I-40 at WinstonSalem. NCDOT formally signed these alternate routes prior to construction. Motorists familiar 

with the area may have also deemed US-158 a possible alternate route. However, US-158 is a 
 81

two-lane highway that runs parallel to I-40 and was not a preferred alternate route due to lower 

capacity compared to US-421. The main detour route adds approximately 10 miles to the trip 

compared with the mainline route. 

Measures and Metrics 

The study team collected traffic data throughout the network to supplement the system detector 

data. The study team performed road tube counts at each key alternate route decision point. The 

study team also counted traffic on ramps along with mainline sections after each ramp to 

establish diversion patterns based on the work zone condition information displayed by the 

system, especially for times when the system actively diverted traffic around the work zone. The 

plan established a baseline prior to ITS implementation (without ITS) for comparison with the 

period when the system was active (with ITS). 

The success of the evaluation hinged upon the accuracy and completeness of several key data 

elements, including: 

 Traffic volumes and average speed and occupancy measurements at each sensor location. 

 DMS logs showing the times and dates that the pre-determined messages were activated. 

 Time-specific information on construction activities and delay as well as crash 

observations as noted by inspectors in DOT construction logs. 

 Historical crash data. 

 Supplemental traffic counts around the network and travel times observed through the 

work zone. 

The study team developed several hypotheses based on the goals for the system. Each 

hypothesis and associated measures and data sources for testing each are shown in Table 17. 

Table 17. Hypotheses and Measures for Evaluation 

Hypothesis Measures of Effectiveness Data Sources 

The ITS system will provide 

accurate, timely, and reliable 

information 

Correlation between work zone 

conditions and messages posted, 

system uptime/downtime, field 

observations 

System logs, project 

engineer records, interviews 

The use of ITS in work zones 

will divert travelers to alternate 

routes during times of work 

zone congestion 

Demand patterns on mainline and 

alternate routes 

Sensor data, supplemental 

traffic counts 

The use of ITS in work zones 

will reduce traveler delay 

Travel time, average vehicle speed, 

work zone throughput, alternate route 

travel times 

Direct observations, system 

data, travel times 

The use of ITS in work zones 

will reduce congestion Travel times, queue lengths 

Direct observations, system 

data, continuous count 

station data 
 82

Hypothesis Measures of Effectiveness Data Sources 

The use of ITS in work zones 

will enhance the safety 

performance of the highway 

Crashes, incidents Crash data, work zone 

inspector diaries 

The use of ITS in the work 

zone will reduce traveler 

exposure to hazard 

Demand patterns, travel times, speed 

variability 

Direct observations, system 

data, continuous count 

station data, evaluationspecific devices 

The system archived data to support the evaluation and hypothesis testing. The study team 

collected baseline data (without ITS) from April 18 through May 10, 2004, during Phase II of 

construction. The study team collected all other data (with ITS) between June 14 and June 29, 

2004, during Phase III (data collected on June 14, 2004, fell within Phase II). While the type of 

construction differed during each, both phases were similar in lane closure configuration. 

However, NCDOT restricted lane closures during Phase III to nighttime hours. The system 

detectors archived data from May 22, 2004 until July 16, 2004 

Findings 

The study team made several interesting observations throughout the deployment, one of which 

showed that the ITS system never reached its full potential as it never fully activated to 

encourage diversion. The level of demand was generally lower than the threshold for full 

activation. Several weeks of construction occurred along the corridor prior to full 

implementation of the system. The traffic impacts during the time period prior to deployment 

may have warranted full activation for active diversion. Additionally, local motorists may have 

chosen to take alternate routes during peak period commutes, thereby lowering demand. As a 

result of the system not reaching its full potential, the supplemental traffic count data collected 

for the diversion study were not analyzed. 

Several schedule and data issues hindered the full assessment of each hypothesis; however, an 

assessment of data and other information from the overall deployment uncovered useful insights 

that are outlined in this section and in the lessons learned below. The study team made several 

interesting observations throughout the deployment, one of which showed that the ITS system 

never reached its full potential as it was never fully activated to encourage diversion. The level 

of demand was generally lower than the threshold for full activation. Several weeks of 

construction occurred along the corridor prior to full implementation of the system. The traffic 

impacts during the time period prior to deployment may have warranted full activation for active 

diversion. The deployment process took NCDOT longer than expected and the system was not 

available during the first phases of construction. Based on the analysis, which showed some 

inconsistencies in the data, the study team suspects that there potentially may have been some 

issues with system function or data archiving. Consequently, all hypotheses were inconclusive 

due to limitations in the information available for analysis.

Construction Activity Information 

With the original intent of assessing impacts to traffic, the study team obtained construction 

activity and capacity reduction information. NCDOT construction inspectors and field engineers 
 83

recorded information in activity logs for each day that work occurred as shown in Tables 18 and 

19. Time periods of interest included those in which lane closures were in place. The recorders 

made notes on crashes within the work zone and at the approaches, maximum queue lengths, and 

specific activities that occurred. 

Table 18. Construction and Lane Closure Information (without ITS) 

Date 

Time of Day 

(Beginning) 

Time of 

Day 

(End) 

Crashes

Observed

Maximum 

Observed 

Queue Length 

(WB/EB) Activity Notes 

4/19/2004 9:00 AM 7:30 PM -- 1 mile Closed Eastbound Inside lane, for 

concrete pavement repair 

4/20/2004 6:30 AM 6:30 PM -- 1 mile / 1 mile 

Set lane closure in the 

Westbound Outside lane, and 

Eastbound Inside lanes 

4/21/2004 6:30 AM 6:30 PM -- 1 mile / 1 mile 

Set lane closure in the 

Westbound Outside lane, and 

Eastbound Inside lanes 

4/22/2004 7:00 AM 5:00 PM -- 1 mile / 1 mile 

Set lane closure in the 

Westbound Outside lane, and 

Eastbound Inside lanes 

4/23/2004 7:00 AM 3:00 PM -- 1 mile / 1 mile 

Set lane closure in the 

Westbound Outside lane, and 

Eastbound Inside lanes 

4/27/2004 7:00 AM 6:00 PM -- 1 mile / 1 mile 

Set lane closure in the 

Westbound Inside lane, and 

Eastbound Inside lane 

4/28/2004 6:30 AM 4:00 PM -- 1 mile Set lane closure in the 

Westbound Inside lane 

4/29/2004 6:30 AM 6:30 PM 1 1 mile Set Barrier wall in the Eastbound 

Outside lane, for Slab Removal 

4/30/2004 7:00 AM 3:30 PM -- 1 mile Barrier still in place for concrete to 

cure 

5/1/2004 7:30 AM 3:30 PM 1 1 mile Barrier still in place for concrete to 

cure 

5/2/2004 --- --- -- 1 mile Barrier still in place for concrete to 

cure 

5/3/2004 6:00 AM 4:30 PM -- 1 mile Set Lane Closure Eastbound 

Outside, removing barrier wall 

5/4/2004 7:00 AM 5:00 PM -- 2 miles Extending Lane Closure, 

Westbound Outside Lane 

5/5/2004 7:00 AM 5:00 PM -- 1 mile Set Lane Closure in the 

Westbound Outside 
 84

Date 

Time of Day 

(Beginning) 

Time of 

Day 

(End) 

Crashes

Observed

Maximum 

Observed 

Queue Length 

(WB/EB) Activity Notes 

5/6/2004 7:00 AM 4:00 PM -- 1 mile Extending Lane Closure, 

Westbound Outside Lane 

5/7/2004 6:30 AM 3:30 PM 1 1 mile Set Lane Closure in the 

Eastbound Outside 

5/8/2004 --- --- -- 1 mile Barrier still in place for concrete to 

cure 

5/9/2004 --- --- -- 1 mile Barrier still in place for concrete to 

cure 

5/10/2004 7:00 AM 5:30 PM -- 1 mile Lane Closure set in Eastbound 

Outside lane 

Table 19. Construction and Lane Closure Information (with ITS) 

Date

Time of Day 

(Beginning)

Time of 

Day 

(End)

Crashes

Observed

Maximum 

Observed 

Queue Length Activity Notes

6/14/2004 6:00 AM 7:30 PM -- 2.5 miles 

Set Lane Closure Westbound 

Inside and Eastbound Inside 

lanes 

6/15/2004 6:00 AM 11:30 PM -- 1.5 miles Set Lane Closure Westbound 

Outside 

6/22/2004 7:00 PM 12:00 AM -- 2.5 miles Westbound Outside lane closure 

6/23/2004 12:00 AM 7:30 AM -- 2.5 miles Westbound Outside lane closure 

6/24/2004 5:00 PM 12:00 AM -- 2.5 miles Set Lane Closure Eastbound 

Outside 

6/25/2004 12:00 AM 5:00 AM -- 2.5 miles Set Lane Closure Eastbound 

Outside 

6/28/2004 5:00 PM 12:00 AM -- 2.5 miles Set Lane Closure Eastbound 

Inside 

6/29/2004 12:00 AM 10:30 AM -- 2.5 miles Set Lane Closure Eastbound 

Inside and Westbound Inside 

The study team parsed applicable notes for the days of interest during the periods both “without 

ITS” (Table 18) and “with ITS” (Table 19). Interestingly, field notes highlighted longer 

maximum queue lengths during periods of nighttime construction. The observed maximum 

queue lengths were also shorter without the system in place. Three crashes occurred prior to 

system implementation and no crashes occurred while the system was operational. The system 

may have been useful in alerting motorists to slowed traffic approaching the work zone. 

NCDOT described the early crashes as “back-of-queue-related.” 
 85

System Detector Traffic Data 

The study team sorted and analyzed traffic data from system detectors to identify deficiencies 

and potential for use in the analysis. The archived traffic data from each detector consisted of 

more than 200,000 records covering a time period from May 22 through July 16, 2004. Each 

message consisted of a volume count, an average speed value, and an average occupancy value 

by lane for both lanes in each direction. 

Through analysis of the traffic data, the study team identified limitations that hindered some of 

the original plans for analysis. A key indicator of problems with the traffic data was a large 

variation in daily demand. The study team developed volume summaries for each day from 

system archives, and extremely large variations existed with a sharp increase in late June (as 

shown in Figure 27). The chart shows data from system detector #9 as an example. All other 

detectors showed similar patterns of variation. Detector #9 monitored westbound traffic and was 

the closest detector to the work zone. Based on traffic patterns, a reasonable daily volume per 

direction is 20,000 to 25,000 vehicles per day. Traffic volume data appear to be reasonable for 

several days. 

0

5000

10000

15000

20000

25000

30000

5/22/2004

5/29/2004

6/5/2004

6/12/2004

6/19/2004

6/26/2004

7/3/2004

7/10/2004

Date

Total Directional Daily Demand

Figure 27. Daily Volume Totals Reported by System Detector #9 

The analysis highlighted missing volume data for most days in June along with portions of July 

3-6 and July 10-12. The system did not record data for July 4, 5, and 11. The reason that the 

system log volume data did not match expected, reasonable traffic volumes was unclear. System 

integrators cited a potential problem in the way the system wrote data to logs early in June, a 

problem that was not evident in a clear pattern or trend in the data. Sensor operational issues 

could also be an explanation for the missing data. 
 86

Speed and occupancy data were plotted for each detector for several days when lane closures 

were in place. The system detector data did not show a clear trend in low speeds and high 

occupancy values for any given day that matched the construction inspector logs. However, the 

study team observed apparent gaps in data during each day in which construction activities took 

place. 

With the exception of a small number of data points, the occupancy values recorded by the 

system appeared reasonable. Less than 1 percent of all occupancy values observed were higher 

than 12 percent occupancy—a value where traffic flow borders on unstable operations.5

 

However, some data points may not have been archived. 

The system recorded average speeds for each time period listed, while a large amount of 

observations showed a speed reading of “240” (a default value recorded when an accurate 

average speed measurement could not be determined). Table 20 shows the percentage of 

undetermined average speed observations by sensor and the total number of observations where 

the system made no determination of speed. For some sensors, the system recorded a large 

portion of the total speed measurements as “240.” Additionally, sensors 5 and 7 had much lower 

total observations than the remaining sensors. Clearly, some issues existed with the data set. 

Table 20. Average Speed Values Reported As "240" 

System 

Detector 

Lane 1 

(240) 

Lane 2 

(240) Total (Values) 

Percentage 

Lane 1 (240 to 

Total) 

Percentage 

Lane 2 (240 to 

Total) 

1 3057 10804 24566 12% 44% 

2 19748 4975 23551 84% 21% 

3 8182 7330 25287 32% 29% 

4 7740 10617 25433 30% 42% 

5 4895 6390 15651 31% 41% 

6 15132 2551 22200 68% 11% 

7 2726 1449 6255 44% 23% 

8 7813 2417 23073 34% 10% 

9 3256 1800 23671 14% 8% 

10 4442 1934 25336 18% 8% 

Dynamic Message Sign Data 

The system archived message logs for the same time period as traffic data. The archives 

included more than 100,000 records. The study team observed missing data for the same time 

periods in the message logs as were observed in the traffic data logs. However, the study team 

made some important observations from the message logs. 

Throughout the deployment, the system posted nearly 30 different messages at different times. 

The system often posted delay messages, but the study team did not observe messages showing 

delays other than 15 or 30 minutes. On multiple occasions, the system posted delay messages for 

very short periods followed by a general message showing no delay through the work zone. In 

 

5

 May, Adolf D., “Traffic Flow Fundamentals,” Prentice-Hall, New Jersey, 1990, page 194. 
 87

addition, message boards in sequence along the same approach to the work zone were 

inconsistent. 

The system used several preprogrammed messages, and operators had the ability to override the 

system and post messages manually as needed. In addition to the pre-determined messages listed 

below, some message signs were blank during several time periods, often after the testing period 

was complete. A few messages included a mix of words and random letters and symbols. 

Messages Showing Delay 

• 15 MINUTE DELAY / EXIT 180 TO EXIT 184. 

• 15 MINUTE DELAY / SLOW MOVING TRAFFIC. 

• I-40 15 MIN DELAY / NEAR CLEMMONS EXIT 184. 

• I-40 15 MIN. DELAY / NEAR CLEMMONS EXIT 184. 

Messages Showing No Delay 

 I-40 WORKZONE INFO / NO DELAY EXIT 180 TO 184. 

 I-40 WORKZONE INFO / NO DELAY EXIT 184 TO 180. 

 REALTIMETRAFFIC INFO / NO DELAY NEXT 4 MILES. 

 SPEED LIMIT 65 / DRIVE SAFELY. 

Example Test Message 

 MESSAGE SIGN TEST / DRIVE WITH CAUTION. 

Messages Encouraging or Requiring Diversion 

 30 MIN DELAY AHEAD / USE EXIT 170 AS ALT. 

 I-40 CLOSED AHEAD / TAKE 421 TO I-77. 

 I-40 CLSD AT EXIT 182. 

 I-40 CLSD AT EXIT 182 / EXPECT DELAYS. 

 I-40 CLSD AT EXIT 182 / TAKE 421 TO I-77. 

Messages Showing General Traffic Conditions 

 CAUTION CAUTION CAUTION / LEFT LANE CLOSED / 2 MILES AHEAD. 

 I-40 WORKZONE ALERT / TRAFFIC SLOWING AHEAD. 

 REALTIMETRAFFIC INFO / TRAFFIC SLOWING AHEAD. 

 REDUCED SPEED AHEAD / USE CAUTION. 

 ROAD WORK AHEAD / DRIVE SAFELY. 

 ROAD WORK ON I-40 / EXPECT DELAYS ON I-40. 

 SLOW MOVING TRAFFIC / DRIVE FRIENDLY / EXPECT DELAYS. 

 SLOW TRAFFIC AHEAD. 

Other Messages 

 BUCKLE UP / DRIVE SAFELY. 

 CAUTION CAUTION CAUTION / ONE LANE ROAD AHEAD / PREPARE TO 

STOP. 

 FLAGMAN AHEAD / SHELBY FARMS MUSIC / PREPARE TO STOP AHEAD. 
 88

On several occasions (especially for weekend activities), NCDOT moved message boards to 

different locations. NCDOT remobilized the system during one complete road closure on 

westbound I-40 from Friday June 4, 2004, at 8:53 p.m. until Saturday June 5, 2004, at 

approximately 5:17 p.m. NCDOT moved six of the message boards to different locations and 

posted the following messages: 

 I-40 CLOSED AHEAD / TAKE 421 TO I-77. 

 I-40 CLSD AHEAD / TAKE 421 TO I-77. 

The study team was aware of the planned closure, but decided not to collect supplemental data 

that weekend due to the short duration and limited options for through travelers. Prior to the 

closure, NCDOT provided information to the media on the planned activities and alternate 

routes. A local newspaper article6

 cited delays on I-40 and US-158, the alternate route for local 

traffic and motorists who misunderstood the I-40 message signs. The article referenced a 

message sign that mentioned exit 182 as the last exit prior to the closure. A local reporter 

interviewed motorists who said they were confused and thought they would reach 421 at that 

exit. 

The system also posted the message “30 MIN DELAY AHEAD / USE EXIT 170 AS ALT” 

during the complete closure on June 5, 2004, for 3 minutes at approximately 11:00 a.m. and 7 

minutes at approximately 12:00 p.m. The system used two versions of the message, with the 

difference being the presence of a period after “MIN” in the alternate version of the message 

listed above. The system posted these messages randomly, once on DMS005 and once on 

DMS003, during the complete directional closure. 

Exit 170 is the I-40 off ramp to US-601, which was one of the signed alternate routes. NCDOT 

did not have information on the exact system layout during the weekend closure, although they 

may have moved the boards to locations where they targeted eastbound motorists prior to exit 

170 and the work zone. The two occasions on June 5, 2004, were the only observations from the 

data where the system posted 30 minute delays along with alternate route information—the 

fullest extent to which the system could activate. 

Despite some data inconsistencies, the study team found very useful information from this 

evaluation. Although the deployment did not allow for the quantitative assessment of system 

benefits desired, the study team uncovered several lessons learned to the benefit of NCDOT and 

others interested in deploying similar systems.

Tips and Lessons Learned 

Deployment Tips and Lessons Learned 

The ITS schedule needs to be linked to the construction schedule to maximize use and benefit 

of the system. At this site, the system was deployed after several weeks where significant traffic 

impacts had occurred. To achieve the maximum benefit, ITS should be operational prior to any 

lane restrictions. 

 

6

 Patrick Wilson, “Traffic meets drivers detoured from Interstate 40,” The Winston-Salem Journal, June 6, 2004, 

http://www.journalnow.com. 
 89

Delays occurred not only at lane drops, but also within the work zone due to slow moving 

trucks that deliver materials to the site. NCDOT learned this lesson from past deployments, so 

for this deployment, NCDOT placed extra sensors within the work area. 

In design and implementation of ITS for work zone applications, agencies should involve the 

construction contractor to the fullest extent possible. Local NCDOT representatives cited the 

need to involve the construction contractor to the extent that they are fully aware of goals and 

objectives for the system, even if the contractor is not involved in the procurement of the system. 

ITS deployments for work zone applications require communications and technology experts 

along with traffic engineering experts. A hardware / software / communications expert should 

be in regular (e.g., daily) contact with a traffic engineer to ensure full system functionality and 

that the ultimate goals of the system are achieved. For this deployment, NCDOT engineers 

coordinated with vendor communications experts to deploy the system. 

The vendor and the implementing agency should discuss in sufficient detail the concept of 

operations for the system, reach an understanding of exactly how it will process information, 

and determine what messages to post. Technology can easily become a “black box” where data 

are input and actions result. A champion for the deployment should be familiar with all aspects 

of system functionality and should guide the vendor. 

Implementing agencies should use verification techniques to validate the outputs of the system 

and refine system operating procedures as needed prior to implementation. Agencies should 

perform a dry run using a test data set to simulate traffic condition information to monitor the 

system and verify output. Agencies should also develop performance metrics prior to system 

implementation to establish specific means of monitoring how well the system worked during 

the deployment. For this deployment, observation and analysis of interim data proved difficult 

due to the level of effort needed to access and view preliminary data sets. Therefore, NCDOT 

relied on the vendor to ensure system functionality and accuracy. 

The system should use message board controls to prevent conflicting messages from being 

displayed along the same approach to the work zone area. At this study site, message logs 

showed that motorists observed conflicting messages, including delay warnings followed by free 

flow condition messages. 

Personnel from the implementing agency should have real-time access to archived system data 

to identify any issues and monitor system functionality. A Web site could easily provide 

password protected access to the data being used by the system to make decisions. The Web site 

for this project provided access to real-time data but did not provide access to the data archives. 

Deploying agency representatives should engage personnel responsible for use of 

supplemental components (such as NCDOT’s permanent DMS for use during high delay 

periods) on a regular basis to ensure that everyone is current on the concept of operations and 

their roles and responsibilities. The North Carolina deployment relied on a portable work zone 

system as well as using some components of a permanent traffic management system. 
 90

 

Evaluation and Research Tips and Lessons Learned 

A successful evaluation of a work zone ITS deployment relies heavily on the cooperation of 

each entity involved, including the implementing agency, the vendor, and especially the 

personnel responsible for successful completion of the construction project. For this 

evaluation, all parties were helpful in obtaining necessary information. Priorities must be set as 

the needs of the evaluation can often place a burden on personnel involved with system 

deployment and operation. 

In developing an evaluation plan, evaluators should focus on a prioritized set of metrics that 

will provide the greatest opportunities to test the benefits of the system. In depending on the use 

of a specific data source, evaluators should test a sample data set to identify any irregularities 

and to confirm the format needed for analysis. 

Research into the use of non-intrusive detector data to quantify traffic flow conditions in work 

zones is warranted. This evaluation highlights a greater understanding of detector outputs, but 

additional work is needed to compare actual traffic conditions with data observed through 

microwave sensors. 
 91

Overall Findings 

This study quantified benefits of ITS deployments for work zone applications and also 

documented key lessons learned from these deployments and previous experience. This study 

provides practitioners with information on what to expect when deploying similar systems, and 

also provides key insights into how to design them and tie the design to the objectives for system 

operation. Agencies interested in deploying similar systems can benefit from the findings of this 

study. Interested agencies can also use the lessons learned from the deploying agencies to 

advance their knowledge and to assist with planning, design, and operation of a work zone ITS 

deployment. This study helps progress current implementation and supplements current research 

through findings of a quantitative nature for the effects of mobile traffic monitoring and 

management systems. 

The following sections outline the findings across the sites, provide tips and lessons learned from 

this study, and show how the findings of this study compare with other studies. This chapter 

concludes with some ideas for future work. 

Findings on Key Measures Across Sites 

Several sites in this study (NC, TX, DC) focused on diversion and demand reduction, while one 

(MI) focused on controlling merge conditions. The Arkansas site focused on general work zone 

condition information, where surveys proved most useful in capturing information on benefits. 

This study produced several quantitative benefits and provided information and outcomes similar 

to those anticipated. 

Among the two diversion-based sites with quantitative benefits (TX, DC), the results were 

somewhat different. TXDOT signed the alternate routes and posted messages specifically 

advising motorists to take one alternate route. A large portion of the trips along the mainline 

route were likely through trips. DDOT did not sign specific alternate routes, and posted general 

messages advising motorists to seek an alternate route. A large portion of the trips along the 

mainline route in Washington, DC were likely commuter trips. It should be noted that based on 

the data available, it was not possible to determine what portion of the lower mainline volume 

observed at the DC site was due to diversion versus demand reduction versus congestion. Some 

of the lower observed mainline volumes in the District of Columbia were likely due to the high 

percentage of local trips to total trips, since local drivers are more likely to be aware of the work 

zone and able to divert to another familiar route to avoid the area. The main trip type is 

important in determining how to design the diversion plans. The findings from the sites with 

active diversion noticeably expand the body of knowledge regarding work zone ITS, as 

quantitative information on diversion rates was not abundant prior to this study. 

The Michigan site showed quantitative benefits in smoothing traffic at the merge point. The 

dynamic lane merge site showed results similar to that of previous studies, while expanding on 

comparisons between time periods with activation and no activation. The Arkansas site provided 

information on the opinions and reactions of drivers as stated directly in survey responses and 

showed benefits based on user surveys that indicated the system helped motorists better plan for 

and make trips. 
 92

Overall, the benefits from this quantitative study were positive. The results of the key measures 

used in this study are summarized in Table 21. 

Table 21. Comparison of Key Measures by Site 

Location

Type of 

System 

Used 

System 

Objectives 

Key 

Performance 

Measures 

Benefits Based on Relative 

Change in Measures 

District of 

Columbia 

Real Time 

Information 

System 

Provide delay 

and travel speed 

information and 

reduce 

congestion by 

actively diverting 

traffic 

Traffic 

Diversion, 

Queue Lengths 

3% to 90% lower observed 

mainline volumes (with an 

average of 52%) over 9 

observation periods by warning 

motorists prior to entering the 

mainline, compared with similar 

days of the week* 

Texas 

Delay 

Monitoring 

System 

Provide delay 

information and 

reduce demand 

and congestion 

by actively 

diverting traffic 

Traffic Diversion 

1% to 28% reduction in mainline 

traffic volume (with an average of 

10% reduction) over 20 

observation periods where the 

system actively diverted traffic 

during congested periods, 

lessening the demand for 

restricted mainline capacity 

Reduce 

aggressive 

driving, smooth 

traffic flow and 

reduce delay at 

merge point 

Aggressive 

Maneuvers 

Significant reduction in forced 

and dangerous merges when 

flashers were on (by a factor of 

seven for forced merges, and a 

factor of 3 for dangerous 

merges), potentially reducing the 

risk of rear-end and side-swipe 

collisions near the merge taper 

Michigan 

Dynamic 

Merge 

System 

Reduce delay 

from aggressive 

passing at the 

merge area 

Travel Times 

Increase in travel times (from an 

average of 4 minutes to 7 

minutes) when lights were 

flashing due to slightly longer 

queues prior to merge 

Arkansas 

Work Zone 

Information 

System 

Improve traveler 

safety by 

providing realtime information 

to motorists 

Survey 

Response to 

Safety-Related 

Questions 

82% of surveyed drivers felt that 

the ITS system improved their 

ability to react to stopped or slow 

traffic. 

49% of surveyed drivers agreed 

that they felt safer traveling 

through the work zone because 

of the electronic messages, 17% 

were neutral, 32% disagreed, 

and 2% did not answer. 

North 

Carolina 

Delay 

Monitoring 

System 

Provide delay 

information and 

reduce demand 

and congestion 

by actively 

diverting traffic 

Traffic Diversion N/A – system did not fully 

activate 

*Combination of diversion, demand reduction, and congestion 
 93

Cross-Cutting Tips and Lessons Learned 

The study team observed several common keys to success and lessons learned across agencies 

when deploying work zone ITS applications. 

A critical element to using work zone ITS successfully is for agencies to map out a decisionmaking process when planning for ITS for work zone traffic management. The process should 

involve setting goals and objectives for what the owner-agency wants the system to do. 

Agencies should consult vendors and inquire about specific solutions, but the solution should 

match the overall goals and objectives for the deployment that are established by the agency. 

The goals and objectives should be kept current as the deployment progresses, and agencies 

should monitor how well the system is meeting the intended goals. 

Based on this study, several key considerations are identified that should be considered for every 

ITS deployment: 

• The intensity of construction activities and anticipated traffic mobility and safety impacts. 

• The level of demand for the area under construction. 

• Availability and adequacy of alternate routes, especially when diversion is planned. 

• Needed enhancements to ensure that alternate routes operate efficiently during construction 

(signal timing changes, minor improvement projects prior to mainline construction, etc.). 

• Access to and availability of other mode choices during the construction period. 

Assessing these considerations during system design and development is important to help 

ensure that the ITS is needed and can be used effectively, both of which are key to knowing if an 

ITS deployment in a particular work zone is likely to be a good investment. 

In each site studied, a champion was active in selling the concept and ensuring momentum for 

the deployment continued at an appropriate pace to lead to the successful deployment of the 

system. Additionally, each site had the appropriate leadership from a group of individuals within 

the agency to ensure appropriate levels of communication across different groups with the 

transportation agency and external to the agency with groups such as law enforcement, 

contractors, and vendors. 

The owner-agencies typically hired a vendor who in turn directly provided or procured the 

services of a local firm to provide hardware, communications, and on-site maintenance and 

support. However, in some cases, the construction contractor hired the vendor. Irrespective of 

the arrangement, proper communication channels should remain open between the owneragency, the construction contractor, the design consultant (if applicable), and the vendor to 

ensure system success. 

In addition to these overall tips and lessons learned, the study team made some observations that 

apply to specific aspects of system development and deployment, as outlined in the sections 

below. 
 94

Planning 

• Agencies should develop goals for the system based on systematic consideration of the 

potential impacts to traffic from the planned construction activities so that the system 

design is appropriate for the conditions. 

• Goals and objectives for the system should be as specific and detailed as possible (e.g., to 

reduce aggressive maneuvers at the work zone taper) to maximize benefits from 

appropriate system design. 

• The system concept should be designed around the detailed goals and objectives to 

ensure adequate mitigation of expected impacts. 

• Demand levels and capacity restrictions from construction should be studied early on to 

identify the potential impacts from construction and validate the need for a portable 

traffic management system. 

• If the agency is also implementing other countermeasures to mitigate traffic impacts 

(such as night work only), the agency needs to consider how much this will lessen the 

impact/usage of the ITS system and factor that into its decision on whether to deploy ITS 

for the given work zone. 

• The construction contractor should be involved to the greatest extent possible in system 

deployment to allow for proper timing in deployment, and to ensure that the contractor 

understands the importance of the system and the placement of the system components. 

This may help ensure that the system is active within the appropriate time periods and 

locations during construction. 

• The system deployment schedule should be tied to the construction activity schedule to 

ensure that the system is deployed at the right time to maximize the effectiveness of the 

investment. 

• Adequate time should be allotted for system procurement, installation, and testing so that 

the deployment covers early construction impact periods. 

• Right–of-way use permits may be required prior to equipment installation, may take extra 

time to complete, and should be accounted for to ensure the deployment covers the early 

construction impact periods. 

• All stakeholders should be involved early in system planning and throughout design to 

ensure roles and responsibilities are adequately communicated. 

• Educating stakeholders who may not be familiar with work zone ITS, such as the media, 

the public, and law enforcement, is important in ensuring the cooperation needed for 

system success. 
 95

Design 

• Agencies should design work zone ITS systems with flexibility in mind since work zones 

are highly variable environments and system adjustments may be needed during 

deployment. 

• Adequate communication must occur between communications experts (ITS vendors) 

and traffic and construction engineers (owner-agency) to effectively plan, design, 

operate, and maintain the system. 

• Vendors can assist agencies with determining the best design for a deployment by 

gaining a solid understanding of the owner-agency’s goals for alleviating impacts from 

the work zone. 

• The system design should include proper evaluation of detector spacing and coverage to 

obtain the accuracy and precision of data needed for the system, particularly if system 

goals include displaying real-time travel time information. 

• Agencies should consider effects on local streets from diverting traffic around the work 

zone. 

Operation and Maintenance 

• Agencies can benefit from hiring a software/system vendor that has a local partner 

company that supplies hardware, message boards, and can be more readily available to 

perform routine inspection and maintenance of the system. 

• Leasing system components from a vendor or local hardware company can save on longterm maintenance and replacement costs. 

• Agency personnel should validate system detector data through various means, such as 

observation of field volumes compared with data archived from the same time period, as 

a check that the system is functioning as intended. 

Prior to starting this study, the study team assumed that work zone ITS systems would be “offthe-shelf,” tested, proven solutions. This proved to not be the case in several instances. While 

the hardware, software, and communications technology may be tested and may operate 

correctly, these systems must be planned and designed from scratch for each work area to have 

the maximum effectiveness. Sensor location, message board location, types of information 

posted, and algorithms for calculating the metrics upon which the system will activate could 

benefit from standardization or guidance. Vendors have proprietary solutions that likely differ in 

process. Uniform guidance on planning and designing the systems would likely prove useful for 

agencies. 
 96

Comparisons with Results of Other Studies 

The findings of this study are comparable to previous research for several of the sites, and go 

beyond previously available knowledge on benefits for others. The following sections outline 

some of the previous research and show how the findings of this study compare with other 

studies. 

Two system types are identified for comparison. The first is the type of system that physically 

controls traffic conditions such as the Michigan Dynamic Lane Merge System. The second is 

more of a monitoring and information dissemination system that provides motorists with realtime information so that they can make informed route choice decisions, such as those deployed 

in Arkansas, North Carolina, and Texas. Both have an element of controlling traffic to improve 

the operational performance of the work zone. 

Previous lane merge studies showed significant reductions in aggressive maneuvers at the work 

zone taper similar to the findings of this study. For sites with the potential for longer queues, 

agencies have implemented and studied the late merge system, which also showed direct 

benefits. The traffic monitoring systems have proven more difficult for measuring quantified 

benefits, as the benefits are typically indirect in that these systems generally provide enhanced 

information to motorists. The systems that display alternate route guidance have been 

implemented to a greater degree recently, including those studied for this project. 

Enforceable Merge Systems 

Michigan DOT undertook several studies in the recent past to evaluate the effectiveness of the 

Dynamic Lane Merge System. The system merges traffic early in locations where queue 

spillback is at acceptable levels. MDOT cited an effectiveness range of 3,000 to 3,500 vehicles 

per hour for the three-to-two merge situation, and 2,000 to 3,000 vehicles per hour for the twoto-one merge situation. Queuing will occur in both situations and is needed to warrant use of the 

system since queue conditions create a potential for forced merges. For the I-94 deployment7

(three-to-two merge), the average number of aggressive maneuvers during the peak hour 

decreased from 2.88 to 0.55. For a two-to-one deployment on M-53 in Grand Rapids, Michigan, 

the average number of aggressive maneuvers decreased from 68.0 to 32.0 during the morning 

peak period, and decreased from 38.0 to 9.0 during the afternoon peak period. The percent 

reduction in aggressive maneuvers for the Michigan site in this study was higher than previous 

studies; however, the total number of observed aggressive maneuvers was lower. 

For higher traffic locations, agencies have successfully used the Late Merge System to smooth 

merges at the work zone taper. The Late Merge System allows traffic to use both lanes on one 

approach and advises motorists via dynamic message signs to take turns merging from each lane. 

Minnesota DOT found that discontinuous lane usage increased to 60 percent at one sensor 

location on I-494.8 While MnDOT was not able to perform a true before and after comparison 

 

7 Development And Evaluation of an Advanced Dynamic Lane Merge Traffic Control System For 3 to 2 Lane 

Transition Areas in Work Zones. Michigan Department of Transportation, 2004. 

8 Evaluation of 2004 Dynamic Late Merge System. Minnesota Department of Transportation, 2004. 
 97

(temporary traffic control conditions both with and without ITS), evaluators observed minimal 

queues during the course of the study. Research has shown that the late merge system is better 

for higher traffic levels and where the availability of queue storage is low, while the early merge 

system is a tool for lower demand, higher queue storage locations. However, a system of 

message signs and sensors that can adjust automatically between the early merge and late merge 

concept may be most beneficial to owner-agencies. This type of active merge system has been 

used in Minnesota. 

Traffic Information Systems 

Some agencies have tested and used mobile traffic monitoring and management systems to 

provide real-time information to motorists. These systems display information about work zone 

conditions, but can also play an important role in alleviating traffic congestion due to incidents. 

It is often more difficult to evaluate the benefits of these types of systems in a quantifiable way, 

especially for metrics such as safety. For example, a system may provide advance warning of 

queued conditions to reduce speed variability and the potential for rear end collisions. But, with 

many common limitations in evaluating crash records for safety performance, agencies may find 

it difficult to quantify the benefits. Such benefits are needed to build support from decision 

makers to continue use of such systems. 

Some systems are also designed to provide information but with one direct outcome in mind, 

such as to reduce speed at a work zone to improve the safety performance of the work zone. A 

Midwest Smart Work Zone Initiative Study of a speed monitoring and display system found a 

significant reduction in speed (5 mph) near the work zone taper. Three other deployments along 

I-80 near Lincoln showed similar results. The study team observed a 3 to 4 mph reduction in 

mean speed, a 2 to 7 mph reduction in 85th percentile speed, and about 20 to 40 percent increase 

in vehicles complying with the speed limit.9

 

Some studies have tested diversion around work zones based on real-time information. Some 

systems actively divert traffic by providing guidance to motorists, while others provide general 

delay information and allow motorists to make route decisions. The limitation of the latter 

concept is that likely only motorists familiar to the area will divert without the direct guidance to 

do so. For areas with mainly through traffic, this concept should be considered in the design 

stages to ensure the intended outcome is realized. A study of the effectiveness of an Automated 

Work Zone Information System on Interstate 5 in California showed diversion rates of 9 percent 

to 12 percent based on condition information.10 Similar studies in Nebraska and Kentucky 

showed very little diversion based on general condition information. While the traffic makeup is 

unknown for the sites mentioned (commuter versus through trips), specific guidance for 

motorists on when to divert to alternate routes will, under the appropriate conditions, have a 

better result. For example, a study of a North Carolina Smart Work Zone deployment found that, 

“...alternate route usage is increased in the range of 10 to 15 percent with the presence of a 

 

9

 McCoy, Patrick and Geza Pesti. Smart Work Zone Technology Evaluations: Speed Monitoring Displays and 

Condition-Responsive, Real-Time Travel Information Systems. Midwest Smart Work Zone Deployment Initiative, 

2000. 

10 Chu, Kim, Chung, and Recker. “Evaluation of Effectiveness of Automated Work Zone Information Systems.” 

TRB 2005 Annual Meeting Compendium. 
 98

Smart Work Zone that provides specific information about delays and alternate routes.”11 In 

general, practitioners in North Carolina have observed, “...some increase in usage of alternate 

routes,” across their various deployments of work zone ITS.12

Additional Comparative Data 

A recent FHWA review of work zone ITS benefits13 produced the following documented results: 

• Between 50 percent and 85 percent of drivers surveyed said that they changed their route 

at least sometimes in response to travel time, delay, or alternate route messages provided 

by work zone ITS. 

• Reductions in queue lengths from 56 percent to 60 percent are possible, with simulations 

indicating system-wide reductions in total delay may range from 41 percent to 75 percent. 

• Speed monitoring displays (SMD) reduce speeds in work zones by 4-6 mph. One study 

found a 20-40 percent reduction in vehicles traveling 10 mph or more over the speed limit 

when SMD were used. 

The results of this study are comparable to the other studies referenced herein, with some 

additional insights into deployment and assessment of ITS for work zone applications. The 

results from this study for the lane merge system is comparable to that of past evaluation projects 

such as those performed by Minnesota DOT and Michigan DOT, while the benefits of providing 

alternate route information are further substantiated through this study. Some previous studies 

focused more on changes in performance measures and statistical analyses related to metrics 

such as speed. Additionally, this study provides further evidence of the general benefits of 

properly planned and design work zone ITS deployments. 

 

11 Bushman, R. and Berthelot, C. Effect of Intelligent Transportation Systems in Work Zones – Evaluation of North 

Carolina Smart Work Zones Final Report. Transportation Research Center, University of Saskatchewan, 2004. 12 Kite, S. “North Carolina’s Smart Work Zone Experience.” Presented at the ITS Virginia Meeting, 2004. 

13 FHWA, Intelligent Transportation Systems for Work Zones: Deployment Benefits and Lessons Learned. 

http://www.its.dot.gov/jpodocs/repts_te/14320.htm 
 99

Suggested Future Work 

This report highlights benefits from five deployments of ITS for work zone traffic management. 

Some benefits from these deployments were qualitative, such as enhanced coordination within 

and outside of an agency for work zone impact mitigation and greater public satisfaction with the 

work zone. Other benefits were quantitative such as a percentage reduction in traffic during 

congested periods, lower delay, and increased safety from automated traffic management. The 

sites showed benefits resulting from trying new techniques such as ITS to help mitigate the 

overall impacts caused by work zones. Agencies interested in new tools to combat work zone 

congestion and safety issues will benefit from the results included in this report. 

Several areas can benefit from additional research and investigation. These areas for action are 

highlighted in the following list. 

• Investigate the impacts on alternate routes – Many ITS applications focus on using corridor 

level capacity to alleviate mainline congestion. Studies are often limited to data collection on 

the mainline only due to increased cost and difficulty in determining when to collect data 

(such as travel times using probe vehicles) on alternates. Quantifying corridor-level impacts 

will be useful for practitioners. 

• Investigate the potential for traffic simulation for ITS – Some models could be used to 

estimate potential benefits from ITS designs, similar to modeling alternative traffic control 

plans. Further investigation into this as a tool would be useful. 

• Research thresholds for system activation – Different systems operate based on unique 

parameters. Further research into appropriate system activation metrics and thresholds, along 

with guidance for vendors and practitioners on how to set thresholds, will be useful for this 

industry. 

• Develop training for planning and deployment of ITS for work zones – A training course 

would be useful to practitioners who are interested in deployment but don’t know where to 

start. The course should cover all aspects and provide practitioners with an opportunity to 

perform exercises in planning for a deployment. 
 100

APPENDIX A 

ARKANSAS – PRIVATE DRIVER SURVEY
101

I-30 Little Rock to Benton Construction Zone Survey 

1. HOW OFTEN do you travel on this section of I-30?

 Almost every day 

 1 – 4 times per week 

 A few times a month 

 Once a month or less 

 This is my first time 

2. For WHICH REASON do you most often travel this section of I-30?

 Commuting to/from school or work 

 Local delivery 

 Errands 

 Traveling through on vacation 

 Traveling through on business 

 Other (please specify) ______________________________________

3. Have you heard of Arkansas’ Pave the Way Web site

(www.arkansasinterstates.com)? 

 Yes; Where did you hear about it? 

________________________________________ 

 No (skip to Question 4) 

3a. Have you visited the portion of the Web site that provides info about the I-30 

construction zone?

 Yes 

 No; Why not? 

 I don’t think the Web site would be helpful (skip to Question 4) 

 I don’t have convenient access to the Web when I would need it (skip to 

Question 4) 

 Other ______________________________________________ (skip to 

Question 4) 

3b. HOW OFTEN do you visit the portion of the Web site that provides info about the I-30 

construction zone? 

 Almost every day 

 1 – 4 times per week 

 A few times a month 

 Once a month or less 

 Only visited once 

3c. For WHAT REASONS do you use the I-30 Web site? (Please mark all that apply.) 

 To check the status of traffic conditions 

 To find out what is causing a delay 

 To plan the route I will take 

 To plan what time to start my trip 

 Other, (please specify)___________________________________ 
102

3d. Rate your level of agreement/disagreement with the following statements about the I-30 

Web site: 

Completely 

Agree 

1 

Somewhat 

Agree 

2 

Neutral 

3 

Somewhat 

Disagree 

4 

Completely 

Disagree 

5 

Not 

Sure 

The Web site is EASY to use      

The info on the Web site is 

ACCURATE      

The info on the Web site improves 

my ability to avoid delay on this 

section of I-30 

     

Just having the information on the 

Web site makes me feel less 

bothered by delays in the 

construction zone 

     

4. Have you ever read the electronic message signs in this section of I-30?

 No; Why not? _____________________ (Skip to question 5) 

 Yes 

4a. Has the information on the signs ever caused you to exit this section of I-30 to take an 

alternate route? 

(Please mark all that apply.) 

 No, Nothing about the electronic message signs causes me to change my route 

 No, I have no alternate route 

 Yes, When the signs read “Traffic Slowing Ahead, Delays Possible” 

 Yes, When the signs read “Traffic Stopped Ahead, Expect Delays” 

 Other (please specify) 

___________________________________________________________ 

4b. Rate your level of agreement/disagreement with the following statements about the 

electronic message signs: 

Completely 

Agree 

1 

Somewhat 

Agree 

2 

Neutral 

3 

Somewhat 

Disagree 

4 

Completely 

Disagree 

5 

Not 

Sure 

The messages are EASY to understand      

The messages are ACCURATE      

The messages are DETAILED enough to 

help me make decisions about my route      

The signs are located in the right places to 

help me make decisions about my route      

Because of the info on the signs, I am 

better prepared to react to slow or stopped 

traffic 

     

I feel safer traveling through this 

construction zone because of the 

information on the signs 

     

Just having the information makes me feel 

less bothered by the delays in the 

construction zone 

     
103

5. Have you ever tuned into the highway advisory radio on this section of I-30?

 No; Why not?_______________________________ (skip to question 6) 

 Yes 

5a. Have the highway advisory radio messages ever caused you to exit this section of I-30 

to take an alternate route? (Please mark all that apply.) 

 No, Nothing about the highway advisory radio system causes me to change my 

route 

 No, I have no alternate route 

 Yes, When it states that there is a delay 

 Yes, When it states that there is a lane closure 

 Other (please specify) 

________________________________________________________________ 

5b. Rate your level of agreement/disagreement with the following statements about 

highway advisory radio: 

Completely 

Agree 

1 

Somewhat 

Agree 

2 

Neutral 

3 

Somewhat 

Disagree 

4 

Completely 

Disagree 

5 

Not 

Sure 

The radio broadcast quality is too poor to 

hear properly      

The messages are USEFUL      

The messages are ACCURATE      

The messages are updated frequently 

enough      

The messages are DETAILED enough to 

help me make decisions about my route      

6. Do you use any of the following sources to get information about traffic conditions on 

this section of I-30? (Please mark all that apply and please circle the one you rely on 

the most)

 Pave the Way Web site – www.arkansasinterstates.com 

 Electronic message signs 

 Highway advisory radio 

 CB radio 

 Local radio station (please specify) _____________________________ 

 Local television station (please specify) __________________________ 

 Other (please specify) ________________________________________ 

7. Please stop me when I read the category that contains your age 

 16 - 25 

 26 - 35 

 36 - 45 

 46 - 55 

 Over 55

Gender: M F 

Date: Time: Interview Conducted By: 
104

 APPENDIX B 

ARKANSAS – COMMERCIAL VEHICLE DRIVER SURVEY 
105

I-30 Little Rock to Benton Construction Zone Survey 

1. HOW OFTEN do you travel on this section of I-30?

□ Almost every day 

□ 1 – 4 times per week 

□ A few times a month 

 Once a month or less 

 This is my first time

2. Considering the trip that took you through this section of I-30 today, 

what was your ORIGIN? __________________________________

what is your DESTINATION? ______________________________

3. Why did you CHOOSE to travel on this section of I-30 today? (Please mark all that apply and please 

circle the most important reason)

 Part of a fixed dispatch route 

□ Shortest distance 

□ Thought it would be the quickest 

□ Roadside amenities (i.e. good restaurants, cheap gas, etc) 

□ No other feasible route 

□ Other (please specify) ______________________________________

4. In general, what must you do to TAKE AN ALTERNATE ROUTE? (Please mark all that apply)

□ Nothing, I can reroute at will 

□ Call my Dispatcher

□ Call my Customer

□ I am not allowed to take alternate routes

□ Other (please specify) ______________________________________

5. Have you heard of Arkansas’ Pave the Way Web site (www.arkansasinterstates.com)? 

 Yes; Where did you hear about it? ________________________________________ 

 No (skip to question 6) 

5a. Have you personally used the portion of the Web site that provides info on the I-30 

construction zone?

 Yes 

 No; Why not? 

 I don’t think the Web site would be helpful (skip to Question 6) 

 I don’t have convenient access when I would need it (skip to Question 6) 

 Other _____________________________________ (skip to Question 6) 

5b. HOW OFTEN do you use the I-30 Web site? 

 Almost every day 

 1 – 4 times per week 

 A few times a month 

 Once a month or less 

 Only visited once 

5c. Before entering the construction zone, WHEN do you usually access the I-30 Web site? 

 6 hours or less before 

 6 – 12 hours before 

 12 – 24 hours before 

 More than one day before 
106

5d. FROM WHERE do you access the I-30 Web site? 

 At home/terminal before starting trip 

 En route via wireless internet 

 En route at fixed internet access point (i.e. truck stop) 

 Other (please specify) ___________________________ 

5e. For WHAT REASONS do you use the I-30 Web site? (Please mark all that apply.) 

 To check the status of traffic conditions 

 To find out what is causing a delay

 To plan the route I will take 

 To plan the time I will start my trip 

 Other (please specify)___________________________________ 

5f. Rate your level of agreement/disagreement with the following statements about the I-30 

Web site: 

Completely 

Agree 

1 

Somewhat 

Agree 

2 

Neutral 

3 

Somewhat 

Disagree 

4 

Completely 

Disagree 

5 

Not 

Sure 

The Web site is EASY to use      

The info on the Web site is ACCURATE      

The info on the Web site improves my 

ability to avoid delay on this section of I-30      

Using the info on the Web site improves 

my ability to provide an on-time delivery      

5. Does your dispatcher use Arkansas’ Pave the Way Web site (www.arkansasinterstates.com)?

 No (skip to question 7) 

□ Yes 

□ Unsure 

5a. May we have your dispatcher’s contact info (optional)? 

Name:_____________________ Phone Number:______________

6. Have you ever read the electronic message signs in this section of I-30?

 No; Why not? ______________________________ (Skip to question 7) 

 Yes

6a. Have the electronic message signs ever caused you to exit this section of I-30 to find an 

alternate route? 

(Please mark all that apply) 

 No, nothing about the electronic message signs has caused me to change my route 

 No, I have no alternate route 

 Yes, when the signs have read “Traffic Slowing Ahead, delays possible” 

 Yes, when the signs have read “Traffic Stopped Ahead, expect delays” 

 Other (please specify) 

_______________________________________________________________ 
107

6b. Rate your level of agreement/disagreement with the following statements about the 

electronic message signs: 

Completely 

Agree 

1 

Somewhat 

Agree 

2 

Neutral 

3 

Somewhat 

Disagree 

4 

Completely 

Disagree 

5 

Not 

Sure 

The messages are EASY to understand      

The messages are ACCURATE      

The messages are DETAILED enough to 

help me make decisions about my route      

The signs are located in the right places to 

help me make decisions about my route      

Because of the info on the signs, I am 

better prepared to react to slow or stopped 

traffic 

     

I feel safer traveling through this 

construction zone because of the electronic 

messages 

     

Just having the information makes me feel 

less bothered by the delays in the 

construction zone 

     

Using the info on the electronic messages 

improves my ability to provide on-time 

delivery 

     

7. Have you ever tuned into the highway advisory radio on this section of I-30?

 No; Why not? ________________________________ (Skip to question 8) 

 Yes 

7a. Have the highway advisory radio messages ever caused you to exit this section of I-30 to 

take an alternate route? (Please mark all that apply.) 

 No, Nothing about the highway advisory radio system causes me to change my 

route 

 No, I have no alternate route 

 Yes, When it states that there is a delay 

 Yes, When it states that there is a lane closure 

 Other (please specify) 

________________________________________________________________ 
108

7b. Rate your level of agreement/disagreement with the following statements about highway advisory 

radio: 

Completely 

Agree 

1 

Somewhat 

Agree 

2 

Neutral 

3 

Somewhat 

Disagree 

4 

Completely 

Disagree 

5 

Not 

Sure 

The radio broadcast quality is too poor 

to hear properly      

The messages are USEFUL      

The messages are ACCURATE      

The messages are updated frequently 

enough      

The messages are DETAILED enough 

to make decisions about my route      

8. Do you use any of the following sources to get information about traffic conditions on this section of I30? (Please mark all that apply and please circle the one you rely on the most)

 Pave the Way Web site – www.arkansasinterstates.com 

 Electronic message signs 

 Highway advisory radio 

 CB radio 

 Local radio station (please specify) __________________________________ 

 Other (please specify) ____________________________________________ 

9. Please stop me when I read the category that contains your age

 18 - 25 

 26 - 35 

 36 - 45 

 46 – 55 

 Over 55 

10. How long have you been driving commercial vehicles?

 Less than 1 year 

 1 – 5 years 

 5 – 10 years 

 10 – 20 years 

 Over 20 years 

Gender: M F

Date: Time: Interview Conducted By: 
109

APPENDIX C 

ARKANSAS – DESCRIPTION OF SURVEY 

ADMINISTRATION 
110

The surveys administered as part of this project were performed as “intercept surveys.” 

Four personnel were utilized to administer the surveys. These personnel intercepted both 

private and commercial drivers at four different service stations in and around the I-30 

work zone. The service stations used as part of this study are described in detail here. 

1) Pilot Travel Center – I-30 Exit 121 – 

(Alcoa Exit) – This location served as 

an interview site for westbound 

commuters and CVDs. It has low 

prices, 8 pumps, a Subway franchise, 

and a lot of business. It is located at an 

exit used by nearby subdivision 

dwellers. 

2) JJ’s Truck Stop and Restaurant – I-30 Exit 106 

(Military Road Exit) –This location was used to 

interview westbound commercial drivers. It is a 

moderately large truck stop with a busy adjacent 

restaurant that caters to truck drivers. The 

restaurant has a lot of truck driver business and 

was used to conduct the interviews. 

3) Conoco – I-30 Exit 123 (Hwy 183 Exit) – This 

location was used to interview eastbound 

commuters in both the a.m. and p.m. peak 

periods. It was not particularly busy, but was the 

best location for eastbound traffic. 

4) Petro Truck Stop – I-40 East of Little Rock – Exit 161 

(Galloway) – This truck stop served as a great 

location to interview eastbound commercial drivers 

who had gone through the I-30 work zone. Given the 

location of this truck stop on I-40, some preliminary 

questions were asked to screen eastbound I-30 drivers 

from those whose routes that did not include the 

subject work zone. 
111

At each location the survey personnel were instructed to follow the script presented here. 

“Good Morning/Afternoon/Evening, 

I am working for the United States Department of Transportation to assist them in 

understanding the benefits of using technology during roadway construction projects. 

One such project is on I-30 between Little Rock and Benton. Have you ever traveled in 

any portion of that work zone? 

[If “no,” say thank you and end the conversation; if “yes,” continue.] 

Would you be willing to participate in a short survey (~5 minutes) regarding the 

technologies installed in the I-30 work zone? 

[If “no,” say thank you and end the conversation; if “yes,” continue.] 

For your reference, during this survey, whenever I say, “this section of I-30” I am 

referring to the section of I-30 that is under construction running from Little Rock to 

Benton. 

Let’s begin the survey.” 
112

APPENDIX D 

ARKANSAS STATISTICAL SUMMARIES 
113

The following tables highlight statistical results for the Arkansas survey data. In each 

table, the number of respondents to the question is shown by n (e.g., n=555). 

Table 22 presents the statistical test results of whether drivers agreed that because of the 

info on the electronic message signs, they were better prepared to react to slow or stopped 

traffic. A single sample one-tailed t-test with 95 percent confidence showed that the 

drivers agreed that the electronic message signs better prepared them to react to slow or 

stopped traffic. 

Table 22. Drivers’ Agreement with the Statement That DMSs Better Prepare Them 

To React to Stopped or Slow Traffic 

Dataset (n = 555) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs combined – drivers 

were better prepared to react to slower traffic 

with the DMS 

1.72 ± 0.05 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -25.60 

Tabulated t-value (p=0.05) -1.645 

Outcome Reject Null hypothesis at p=0.05 

Table 23 presents the statistical test results for drivers’ agreement with the statement that 

DMS makes them feel safer. A t-test showed that the drivers did agree that the DMS 

made them feel safer traveling through this construction zone. 

Table 23. Driver’s Agreement with the Statement That DMS Makes Them Feel 

Safer 

Dataset (n = 555) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs combined – DMS 

makes drivers feel safer in the construction 

zone 

2.80 ± 0.07 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -2.86 

Tabulated t-value (p=0.05) -1.645 

Outcome Reject Null hypothesis at p=0.05 
114

Table 24 presents the statistical test results for drivers’ agreement that the Web site 

improved trip planning. A t-test with 95 percent confidence level showed that the 23 

drivers who used the Web site agreed that the Web site was able to improve trip planning. 

Table 24. Drivers Agree The Web Site Improved Trip Planning 

Dataset (n = 23) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs - The info on the Web site 

improves my ability to avoid delay on this section 

of I-30 

2.00 ± 0.29 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -3.45 

Tabulated t-value (p=0.05) -1.717 

Outcome Reject Null hypothesis at p=0.05 

Tables 25 and 26 present the statistical test results for drivers’ agreement that the DMS 

messages contained enough detail and that the signs were located in the right places. 

Using a t-test with 95 percent confidence, drivers indicated that they agreed that the DMS 

contained enough detail and were located in the correct places 

Table 25. Drivers Agree DMS Contain Enough Detail 

Dataset (n = 552) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs Combined - DMS 

messages are detailed enough to help me 

make decision about my route 

1.78 ± 0.05 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -24.40 

Tabulated t-value (p=0.05) -1.645 

Outcome Reject Null hypothesis at p=0.05 

Table 26. Drivers Agree DMS Are Located in the Right Places 

Dataset (n = 542) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs Combined – DMS are 

located in the right places to help me make 

decisions about my route 

2.10 ± 0.06 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -15.00 

Tabulated t-value (p=0.05) -1.645 

Outcome Reject Null hypothesis at p=0.05 
115

Table 27 presents the statistical test results for drivers’ agreement that the HAR messages 

were detailed enough to help them make decisions. The average rating for this question 

was 1.93, indicating that the drivers agreed (1 is completely agree; 2 is somewhat agree) 

that the HAR messages were detailed enough to help them make decisions about their 

routes. 

Table 27. Drivers Agree HAR Messages are Detailed Enough to Help Them Make 

Decisions 

Dataset (n = 121) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs - HAR messages are 

detailed enough to help me make decisions 

about my route 

1.93 ± 0.11 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -9.73 

Tabulated t-value (p=0.05) -1.658 

Outcome Reject Null hypothesis at p=0.05 

Tables 28 and 29 present the statistical test results for whether drivers agreed that the 

dynamic message signs were easy to understand and detailed enough to help them make 

decisions. At a 95 percent confidence level, results were significant when drivers were 

asked if the DMS are detailed enough and easy to understand. 

Table 28. Driver Response to Statement that DMS are Easy to Understand 

Dataset (n = 548) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs - DMS messages are 

easy to understand (only drivers that also 

answered “The messages are detailed enough 

to help me make decisions about my route.” 

1.26 ± 0.03 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -58.00 

Tabulated t-value (p=0.05) -1.645 

Outcome Reject Null hypothesis at p=0.05 
116

Table 29. Driver Response to the Statement that DMS are Detailed Enough to Help 

Me Make Decisions 

Dataset (n = 548) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs - DMS messages are 

detailed enough to help me make decisions 

about my route (only drivers that also 

answered “The messages are easy to 

understand.”) 

1.78 ± 0.05 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -24.40 

Tabulated t-value (p=0.05) -1.645 

Outcome Reject Null hypothesis at p=0.05 

Tables 30 and 31 present the statistical test results for whether drivers felt that the HAR 

broadcast quality was too poor to hear, and whether the messages were detailed enough 

to help them make decisions. The findings on whether HAR broadcasts were too poor to 

hear was significant at a 95 percent confidence level. However, drivers agreed that the 

messages were detailed enough to allow them to make better decisions about their routes. 

Table 30. Drivers Response to Statement that HAR Broadcast Quality is Too Poor 

to Hear 

Dataset (n = 124) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs - Radio broadcast 

quality is too poor to hear properly (only 

drivers that also answered (“HAR messages 

are detailed enough to help me make 

decisions about my route.”) 

2.57 ± 0.14 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -3.07 

Tabulated t-value (p=0.05) -1.658 

Outcome Reject Null hypothesis at p=0.05 
117

Table 31. Drivers’ Response to Statement that HAR Messages are Detailed Enough 

to Help Make Decisions 

Dataset (n = 120) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs - HAR messages are 

detailed enough to help me make decisions 

about my route (only drivers that also 

answered “Radio broadcast quality is too poor 

to hear properly.”) 

1.93 ± 0.11 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -9.73 

Tabulated t-value (p=0.05) -1.658 

Outcome Reject Null hypothesis at p=0.05 

Table 32 provides the statistical test results for whether drivers agree that the information 

on the Web site is accurate. The average rating of the 23 drivers who answered the 

question on whether the Web site is accurate was a 1.7. This value falls between 

completely agree (1) and somewhat agree (2). Using a t-test with 95 percent confidence, 

the drivers agreed that the Web site was giving accurate information. 

Table 32. Drivers Agree the Information on the Web Site is Accurate 

Dataset (n = 23) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs – The info on the Web 

site is accurate 1.70 ± 0.25 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -5.20 

Tabulated t-value (p=0.05) -1.717 

Outcome Reject Null hypothesis at p=0.05 

Table 33 presents the statistical results for whether drivers found the DMS messages to 

be accurate. Performing a t-test for the responses shows that the drivers found the DMS 

messages accurate at a 95 percent significance level. These findings support the 

conclusion that participants feel the DMS were giving accurate messages. 
118

Table 33. Drivers Find the DMS Messages To Be Accurate 

Dataset (n = 543) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs – DMS messages are 

accurate 1.75 ± 0.05 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -25.00 

Tabulated t-value (p=0.05) -1.645 

Outcome Reject Null hypothesis at p=0.05 

Tables 34, 35, and 36 provide the statistical test results for whether drivers found the 

HAR messages to be useful, accurate, and updated frequently enough. Using a t-test at 

95 percent significance showed that the drivers agreed that HAR was useful, accurate, 

and updated frequently enough. The scale included completely agree (1), somewhat 

agree (2), neutral (3), somewhat disagree (4), completely disagree (5), and not sure. 

Table 34. Drivers Find HAR Messages To Be Useful 

Dataset (n = 115) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs – HAR messages are 

useful (only drivers that also answered “HAR 

messages are accurate,” and “HAR messages 

are updated frequently enough.”) 

1.74 ± 0.10 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -12.6 

Tabulated t-value (p=0.05) -1.658 

Outcome Reject Null hypothesis at p=0.05 

Table 35. Drivers Find HAR Messages to Be Accurate 

Dataset (n = 114) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs – HAR messages are 

accurate (only drivers that also answered 

“HAR messages are useful,” and “HAR 

messages are updated frequently enough.”) 

2.00 ± 0.11 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -9.09 

Tabulated t-value (p=0.05) -1.658 

Outcome Reject Null hypothesis at p=0.05 
119

Table 36. Drivers Find HAR Messages To Be Updated Frequently Enough 

Dataset (n = 98) Level of agreement 

(Mean ± Standard Error) 

Private drivers & CVDs – HAR messages are 

updated frequently enough (only drivers that 

also answered “HAR messages are useful,” 

and “HAR messages are accurate.”) 

2.27 ± 0.14 

Statistical Comparison Results 

(Null Hypothesis: Mean of the dataset is equal to or greater than 3; 

Alternative Hypothesis: Mean of the dataset is less than 3) 

Calculated t-value -5.21 

Tabulated t-value (p=0.05) -1.658 

Outcome Reject Null hypothesis at p=0.05 

Note: Of the 616 surveys, only two PVDs and three CVDs did not provide gender 

information, 7 PVDs and 13 CVDs did not give age information, and four CVDs did not 

give their driving experience. 

Table 37 presents the statistical test results for the question of whether the combined 

volume from the ITS detectors was significantly higher than the AHTD Tube data. A ttest showed that the combined volume from the ITS detectors was significantly different 

– higher - with a 95 percent confidence level. 

Table 37. Combined Volume From The ITS Detectors (62 and 26) Was Significantly 

Higher Than The AHTD Tube Data 

Dataset (n = 240) 

Hourly volume difference between tube data 

and ITS detectors (in percentage) 

(Mean ± Standard Error) 

May 21 – Jun 20, 2004. Detectors No 62 & 26 

(RTMS), and data from I-30 & Raymar Rd 

(Tube data) 

-42.4 ± 2.1 

Statistical Comparison Results 

(Null Hypothesis: Mean of the differences equals 0; Alternative Hypothesis: 

Mean of the differences does not equal 0) 

Calculated t-value -20.19 

Tabulated t-value (p=0.05) 1.960 

Outcome Reject the null hypothesis at p=0.05 

Table 38 presents the statistical results for the question of whether the combined volume 

from the ITS detectors was different than AHTD’s tube data. A t-test showed that the 

combined volume from the ITS detectors was not different than the AHTD data with a 95 

percent confidence level. Tables 37 and 38 test significance for two different sources of 

ITS detector data. 
120

Table 38. Combined Volume From The ITS Detectors (63 and 25) Was Not 

Different Than The AHTD Tube Data 

Dataset (n = 240) 

Hourly volume difference between tube data 

and ITS detectors (in percentage) 

(Mean ± Standard Error) 

May 21 – Jun 20, 2004. Detectors No 63 & 25 

(RTMS), and data from I-30 & Raymar Rd 

(Tube data) 

0.071 ± 0.17 

Statistical Comparison Results 

(Null Hypothesis: Mean of the differences equals 0; Alternative Hypothesis: Mean of the 

differences does not equal 0) 

Calculated t-value 0.42 

Tabulated t-value (p=0.05) 1.960 

Outcome Fail to Reject null hypothesis at p=0.05 
121

Technical Report Documentation Page 

1. Report No. 

FHWA-HOP-09-002 

2. Government Accession No. 3. Recipient's Catalog No. 

5. Report Date 

October 2008 

4. Title and Subtitle 

Comparative Analysis Report: The Benefits of Using Intelligent 

Transportation Systems in Work Zones 

6. Performing Organization Code 

7. Author(s) 

Tim Luttrell (SAIC), Mark Robinson (SAIC), Jennifer Rephlo 

(SAIC), Robert Haas (SAIC), Jordan Srour (SAIC), Rahim 

Benekohal (UIUC), Jun-Seok Oh (WMU), Tracy Scriba (FHWA) 

8. Performing Organization Report No. 

9. Performing Organization Name and Address 10. Work Unit No. (TRAIS) 

Science Applications International Corporation 

1710 SAIC Drive 

McLean, VA 22102 

11. Contract or Grant No. 

DTFH61-02-C-00061 

12. Sponsoring Agency Name and Address 13. Type of Report and Period Covered 

U.S. Department of Transportation 

Federal Highway Administration 

Office of Operations 

1200 New Jersey Avenue, SE 

Washington, DC 20590 

14. Sponsoring Agency Code 

HOTO 

15. Supplementary Notes 

Project Leader: Tracy Scriba, FHWA 

16. Abstract 

This document provides quantitative benefits of using Intelligent Transportation Systems in highway 

construction and maintenance work zones. The technical report covers case study sites in the District of 

Columbia, Texas, Michigan, Arkansas, and North Carolina. The document provides insights into the 

mobility and safety benefits of ITS for work zone traffic management.

17. Key Word 

WORK ZONE, ITS, INTELLIGENT 

TRANSPORTATION SYSTEMS, WORK ZONE 

SAFETY AND MOBILITY, WORK ZONE TRAFFIC 

MANAGEMENT 

18. Distribution Statement 

19. Security Classif. (of this report) 

Unclassified 

20. Security Classif. (of this page) 

Unclassified 

21. No. of Pages 

122 

22. Price 

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
Comparative Analysis Report: 

The Benefits of Using Intelligent Transportation 

Systems in Work Zones

U.S. Department of Transportation 

Federal Highway Administration 

Office of Transportation Operations 

1200 New Jersey Ave., SE 

Washington, D.C. 20590 

Toll-Free Help Line: 866.367.7487 

www.fhwa.dot.gov/workzones

FHWA-HOP-09-002