Traffic Analysis Toolbox Volume II:

Decision Support Methodology for

Selecting Traffic Analysis Tools

PUBLICATION NO. FHWA-HRT-04-039 JULY 2004

Research, Development, and Technology

Turner-Fairbank Highway Research Center

6300 Georgetown Pike

McLean, VA 22101-2296
Foreword

“Traffic analysis tools” is a collective term used to describe a variety of software-based 

analytical procedures and methodologies that support different aspects of traffic and 

transportation analyses. Traffic analysis tools include methodologies such as sketch-planning, 

travel demand modeling, traffic signal optimization, and traffic simulation. While traffic 

analysis tools have the capability to provide meaningful insights into transportation analyses, 

far too often they are misapplied. Namely, the most appropriate tool for the job is not the tool 

that is used. 

The purpose of this Decision Support Methodology for Selecting Traffic Analysis Tools is to provide 

an overview of the role of traffic analysis tools in transportation analyses and to present a 

detailed methodology for selecting the appropriate tool for the job at hand. The report 

describes the selection process including selection criteria and worksheets that can be used in 

applying the selection process. 

This document serves as Volume II in the Traffic Analysis Toolbox. Other volumes currently in 

the toolbox include: Volume I: Traffic Analysis Tools Primer and Volume III: Guidelines for 

Applying Traffic Microsimulation Modeling Software.

The intended audience for this report is the transportation professional or analyst who uses 

traffic analysis tools and makes decisions on the types of analyses to use. 

 Jeffery A. Lindley, P.E. 

 Director 

 Office of Transportation Management 

Notice 

This document is disseminated under the sponsorship of the U.S. Department of Transportation 

in the interest of information exchange. The U.S. Government assumes no liability for the use of 

the information contained in this document. 

The U.S. Government does not endorse products or manufacturers. Trademarks or 

manufacturers’ names appear in this report only because they are considered essential to the 

object of the document. 

Quality Assurance Statement 

The Federal Highway Administration (FHWA) 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. 
Technical Report Documentation Page 

1. Report No.

FHWA-HRT-04-039 

2. Government Accession No. 3. Recipient’s Catalog No.

 

5. Report Date 

June 2004 

4. Title and Subtitle 

Traffic Analysis Toolbox 

Volume II: Decision Support Methodology for Selecting Traffic 

Analysis Tools 

6. Performing Organization Code

 

7. Author(s) 

Krista Jeannotte, Andre Chandra, Vassili Alexiadis, Alexander 

Skabardonis 

8. Performing Organization Report No. 

 

10. Work Unit No. 

 

9. Performing Organization Name and Address 

Cambridge Systematics, Inc. 

555 12th Street, Suite 1600 

Oakland, CA 94607 

11. Contract or Grant No. 

DTFH61-01-C-00181 

13. Type of Report and Period Covered 

Final Report, May 2002 – August 2003 

12. Sponsoring Agency Name and Address 

Office of Operations 

Federal Highway Administration 

400 7th Street, S.W. 

Washington, DC 20590 

14. Sponsoring Agency Code 

 

15. Supplementary Notes 

FHWA COTR: John Halkias, Office of Transportation Management 

16. Abstract 

This report provides an overview of the role of traffic analysis tools in the transportation analysis process and 

provides a detailed decision support methodology for selecting the appropriate type of analysis tool for the job at 

hand. 

An introduction to the role of traffic analysis tools and tool categories is provided. A set of criteria for selecting 

the appropriate type of traffic analysis tool is described in detail and each tool category is scored as to its 

relevance to the criteria. The criteria include the analysis context, study area, facility type, travel mode, 

management strategy, traveler response, performance measures, and cost-effectiveness. A process and 

worksheets for an analyst to rate a tool category for a particular transportation analysis task are presented based 

on the criteria and the analyst's weighting of the criteria. Some challenges and limitations of the use of traffic 

analysis tools are provided. 

The appendices include: a) a summary of current limitations to the highway capacity manual (HCM) 

methodologies, b) tool category selection worksheets, c) worksheets for selecting an individual tool within a 

category, d) a list of recommended further reading, and e) a list of traffic analysis tools by category. 

This is the second volume in a series of volumes in the Traffic Analysis Toolbox. The other volumes currently in 

the Traffic Analysis Toolbox are: 

Volume I: Traffic Analysis Tools Primer (FHWA-HRT-04-038) 

Volume III: Guidelines for Applying Traffic Microsimulation Modeling Software (FHWA-HRT-04-040) 

17. Key Words 

Traffic analysis tools, traffic simulation, highway 

capacity, decision support, tool selection 

18. Distribution Statement 

No restrictions. This document is available to the public 

through the National Technical Information Service, 

Springfield, VA 22161. 

19. Security Classif. (of this report) 

Unclassified 

20. Security Classif. (of this page) 

Unclassified 

21. No of Pages

108

22. Price 

 

Form DOT F 1700.7 (8-72) Reproduction of completed pages authorized 
ii 

SI* (MODERN METRIC) CONVERSION FACTORS 

APPROXIMATE CONVERSIONS TO SI UNITS

Symbol When You Know Multiply By To Find Symbol 

LENGTH 

in inches 25.4 millimeters mm 

ft feet 0.305 meters m 

yd yards 0.914 meters m 

mi miles 1.61 kilometers km 

AREA 

in2 square inches 645.2 square millimeters mm2

ft2 square feet 0.093 square meters m2

yd2 square yard 0.836 square meters m2

ac acres 0.405 hectares ha 

mi2 square miles 2.59 square kilometers km2

VOLUME 

fl oz fluid ounces 29.57 milliliters mL 

gal gallons 3.785 liters L 

ft3 cubic feet 0.028 cubic meters m3 

yd3 cubic yards 0.765 cubic meters m3 

NOTE: volumes greater than 1000 L shall be shown in m3

MASS 

oz ounces 28.35 grams g

lb pounds 0.454 kilograms kg

T short tons (2000 lb) 0.907 megagrams (or "metric ton") Mg (or "t") 

TEMPERATURE (exact degrees) o

F Fahrenheit 5 (F-32)/9 Celsius oC 

or (F-32)/1.8 

ILLUMINATION 

fc foot-candles 10.76 lux lx 

fl foot-Lamberts 3.426 candela/m2 cd/m2

FORCE and PRESSURE or STRESS 

lbf poundforce 4.45 newtons N 

lbf/in2 poundforce per square inch 6.89 kilopascals kPa 

APPROXIMATE CONVERSIONS FROM SI UNITS 

Symbol When You Know Multiply By To Find Symbol 

LENGTH

mm millimeters 0.039 inches in 

m meters 3.28 feet ft 

m meters 1.09 yards yd 

km kilometers 0.621 miles mi 

AREA mm2

 square millimeters 0.0016 square inches in2 

m2 square meters 10.764 square feet ft2 

m2 square meters 1.195 square yards yd2 

ha hectares 2.47 acres ac 

km2 square kilometers 0.386 square miles mi2 

VOLUME 

mL milliliters 0.034 fluid ounces fl oz 

L liters 0.264 gallons gal 

m3 cubic meters 35.314 cubic feet ft3 

m3 cubic meters 1.307 cubic yards yd3 

MASS 

g grams 0.035 ounces oz

kg kilograms 2.202 pounds lb

Mg (or "t") megagrams (or "metric ton") 1.103 short tons (2000 lb) T 

TEMPERATURE (exact degrees) o

C Celsius 1.8C+32 Fahrenheit oF 

ILLUMINATION 

lx lux 0.0929 foot-candles fc 

cd/m2 candela/m2 0.2919 foot-Lamberts fl

FORCE and PRESSURE or STRESS 

N newtons 0.225 poundforce lbf 

kPa kilopascals 0.145 poundforce per square inch lbf/in2

*SI is the symbol for th International System of Units. Appropri e ate rounding should be made to comply with Section 4 of ASTM E380. 

(Revised March 2003)
iii 

Table of Contents 

1.0 Background and Objectives ........................................................................................ 1 

1.1 Overview of the Transportation Analysis Process ............................................ 2 

1.2 Role of Traffic Analysis Tools............................................................................... 3 

1.3 Categories of Traffic Analysis Tools.................................................................... 6 

1.4 Comparison of HCM and Simulation ................................................................. 8 

1.4.1 Overview of HCM..................................................................................... 8 

1.4.2 HCM Strengths and Limitations............................................................. 9 

1.4.3 Simulation Strengths and Limitations.................................................... 10 

1.4.4 Traffic Performance Measures: Differences Between HCM and 

Simulation .................................................................................................. 11 

1.4.5 Strategy for Overcoming the Limitations of HCM............................... 11 

2.0 Criteria for Selecting the Appropriate Type of Traffic Analysis Tool................ 13 

2.1 Analytical Context ................................................................................................. 14 

2.2 Criteria for Analytical Tool Selection and Assessment of Tool Capabilities . 16 

2.2.1 Study Area/Geographic Scope ............................................................... 17 

2.2.2 Facility Type............................................................................................... 18 

2.2.3 Travel Mode............................................................................................... 20 

2.2.4 Management Strategy and Applications ............................................... 21 

2.2.5 Traveler Response..................................................................................... 25 

2.2.6 Performance Measures ............................................................................. 26 

2.2.7 Tool/Cost-Effectiveness........................................................................... 29 

3.0 Methodology for Selecting a Traffic Analysis Tool ............................................... 33 

3.1 Steps for Selecting the Appropriate Tool Category........................................... 33 

3.2 Examples for Using the Tool Category Selection Worksheets......................... 39 

3.2.1 Example 1: Ramp Metering Corridor Study ........................................ 39 

3.2.2 Example 2: ITS Long-Range Plan........................................................... 41 

3.2.3 Example 3: Arterial Signal Coordination and Preemption ................. 42 

3.3 Guidance for Selecting the Specific Tool............................................................. 43 

4.0 Available Traffic Analysis Tools................................................................................ 61 

5.0 Challenges and Limitations in the Use of Traffic Analysis Tools....................... 63 
iv 

Table of Contents (continued) 

Appendix A: Limitations of HCM ..................................................................................... 65 

Appendix B: Tool Category Selection Worksheet .......................................................... 69 

Appendix C: Tool Selection Worksheet............................................................................ 75 

Appendix D: Recommended Reading............................................................................... 85 

Appendix E: Traffic Analysis Tools by Category ........................................................... 87 

E.1 Sketch-Planning Tools ........................................................................................... 87 

E.2 Travel Demand Models......................................................................................... 88 

E.3 Analytical/ Deterministic Tools (HCM Methodologies).................................. 88 

E.4 Traffic Optimization Tools.................................................................................... 91 

E.5 Macroscopic Simulation Models.......................................................................... 92 

E.6 Mesoscopic Simulation Models............................................................................ 92 

E.7 Microscopic Simulation Models........................................................................... 93 

E.8 Integrated Traffic Analysis Tools......................................................................... 94 

Appendix F: References ........................................................................................................ 97 
v 

List of Figures 

1. Overview of the transportation analysis process....................................................... 5 

2. Criteria for selecting a traffic analysis tool category. ................................................ 15 

3. Selecting the appropriate tool category, step 1. ......................................................... 33 

4. Selecting the appropriate tool category, step 2. ......................................................... 35 

5. Selecting the appropriate tool category, step 3. ......................................................... 36 

6. Selecting the appropriate tool category, step 4. ......................................................... 36 

7. Selecting the appropriate tool category, steps 5–7..................................................... 37 

8. Selecting the appropriate tool category, step 8. ......................................................... 37 

9. Selecting the appropriate tool category, steps 9 and 10. ........................................... 38 

10. Selecting the appropriate tool category, step 11. ....................................................... 38 

11. Selecting the appropriate tool category, steps 12 and 13. ......................................... 39 

12. Selecting the specific tool, step 1. ................................................................................. 44 

13. Selecting the specific tool, step 2. ................................................................................. 44 

14. Selecting the specific tool, steps 3 and 4...................................................................... 45 

15. Selecting the specific tool, steps 5–7............................................................................. 45 

16. Selecting the specific tool, steps 8 and 9...................................................................... 46 

17. Selecting the specific tool, steps 10–13......................................................................... 47 
vi 

List of Tables 

1. Relevance of traffic analysis tool categories with respect to analytical context. ... 16 

2. Relevance of traffic analysis tool categories with respect to study area/ 

geographic scope. ........................................................................................................... 18

3. Relevance of traffic analysis tool categories with respect to facility type. ............. 19 

4. Relevance of traffic analysis tool categories with respect to travel mode. ............. 21 

5. Relevance of traffic analysis tool categories with respect to management 

strategy and applications. ............................................................................................. 24 

6. Relevance of traffic analysis tool categories with respect to traveler response..... 25 

7. Relevance of traffic analysis tool categories with respect to performance 

measures. ......................................................................................................................... 28 

8. Relevance of traffic analysis tool categories with respect to tool/cost 

effectiveness. ................................................................................................................... 32 

9. Example 1 worksheet (refer to sections 2.1 and 2.2 for criteria definitions). ......... 48 

10. Example 2 worksheet (refer to sections 2.1 and 2.2 for criteria definitions). ......... 52 

11. Example 3 worksheet (refer to sections 2.1 and 2.2 for criteria definitions). ......... 56 

12. Limitations of the HCM methodologies...................................................................... 66 

13. Tool category selection worksheet (refer to sections 2.1 and 2.2 for criteria 

definitions). ..................................................................................................................... 70 

14. Tool selection worksheet. .............................................................................................. 76 
1 

1.0 Background and Objectives 

Entering the 21st century, the Nation’s transportation system has matured; it only expands 

its infrastructure by a fraction of a percentage each year. However, congestion continues 

to grow at an alarming rate, adversely impacting our quality of life and increasing the 

potential for crashes and long delays. These are expected to escalate, calling for 

transportation professionals to increase the productivity of existing transportation systems 

through the use of operational improvements. To assess the potential effectiveness of a 

particular strategy, it must be analyzed using traffic analysis tools or methodologies. 

There are several traffic analysis methodologies and tools available for use; however, there 

is little or no guidance on which tool should be used. These tools all vary in their scope, 

capabilities, methodology, input requirements, and output. In addition, there is no one 

tool that can address all of the analytical needs of a particular agency. 

The objective of Decision Support Methodology for Selecting Traffic Analysis Tools (Volume II) 

is to assist traffic engineers, planners, and traffic operations professionals in the selection 

of the correct type of traffic analysis tool for operational improvements. This document is 

intended to assist practitioners in selecting the category of tool for use (e.g., Highway 

Capacity Manual (HCM) versus traffic simulation); this document does not include an 

assessment of the capabilities of specific tools within an analytical tool category. Another 

objective of this document is to assist in creating analytical consistency and uniformity 

across State departments of transportation (DOTs) and Federal/regional/local 

transportation agencies. 

Decision Support Methodology for Selecting Traffic Analysis Tools identifies the criteria that 

should be considered in the selection of an appropriate traffic analysis tool and helps 

identify the circumstances when a particular type of tool should be used. A methodology 

is also presented to guide users in the selection of the appropriate tool category. This 

document includes worksheets that transportation professionals can use to select the 

appropriate tool category and provides assistance in identifying the most appropriate tool 

within the selected category. An automated tool that implements this methodology can be 

found at the Federal Highway Administration (FHWA) Traffic Analysis Tools Web site at: 

http://ops.fhwa.dot.gov/Travel/Traffic_Analysis_Tools/traffic_analysis_tools.htm

This methodology was developed for FHWA. The FHWA Traffic Analysis Tools Team 

made extensive contributions to this document and to the automated tool. This document 

is organized into the following sections: 

Section 1.0: Background and Objectives: Describes the objectives of the document and 

highlights the need for and the role of traffic analysis tools, including the definitions of the 

analytical tool categories covered in this document. This section also presents a 

comparison of HCM with traffic simulation models. 
2 

Section 2.0: Criteria for Selecting the Appropriate Type of Traffic Analysis Tool: 

Identifies the criteria that should be considered in the selection of an appropriate traffic 

analysis tool and helps identify the circumstances when a particular type of tool should be 

used. A methodology is presented to guide users in the selection of the appropriate tool 

category. 

Section 3.0: Methodology for Selecting a Traffic Analysis Tool: Provides guidance to 

users on how to use the criteria in section 2.0 to select the appropriate analytical tool 

category. This section includes worksheets that transportation professionals can use to 

select the appropriate tool category and assistance in identifying the most appropriate tool 

within the selected category. 

Section 4.0: Available Traffic Analysis Tools: Presents a list of available analytical tools. 

Section 5.0: Challenges and Limitations in the Use of Traffic Analysis Tools: Highlights 

some of the challenges and limitations of the analytical tools for consideration by users. 

Appendix A: Limitations of HCM: Lists the limitations of the HCM methodologies. 

Appendix B: Tool Category Selection Worksheet: Contains a worksheet that can be used 

to select an appropriate tool category for the task. 

Appendix C: Tool Selection Worksheet: Contains a worksheet that can assist users with 

the selection of a specific traffic analysis tool. 

Appendix D: Recommended Reading: Contains a list of documents that discuss or 

compare some of the specific traffic analysis tools. 

Appendix E: Traffic Analysis Tools by Category: Provides a list of analytical tools by 

category and their Web site links. This is only intended to be a starting point for users 

once they have selected an analytical tool category. 

Appendix F: References: Documents the literature reviewed and used in the development 

of this document. 

1.1 Overview of the Transportation Analysis Process 

The Intermodal Surface Transportation Efficiency Act (ISTEA), the Transportation Equity 

Act for the 21st Century (TEA-21), and Federal/State Clean Air legislation have reinforced 

the importance of traffic management and control of existing highway capacity. As 

transportation agencies deploy more sophisticated hardware and software system 

management technologies, there is an increased need to respond to recurring and 

nonrecurring congestion in a proactive fashion, and to predict and evaluate the outcome of 

various improvement plans without the inconvenience of a field experiment. 

Out of these needs, traffic analysis tools emerge as one of the most efficient methods to 

evaluate transportation improvement projects. This document addresses quantifiable 
3 

traffic operations analytical tools categories, but does not include real-time or predictive 

models. Traffic analysis tools may include software packages, methodologies, and 

procedures, and are defined as those typically used for the following tasks: 

• Evaluating, simulating, or optimizing the operations of transportation facilities and 

systems. 

• Modeling existing operations and predicting probable outcomes for proposed design 

alternatives. 

• Evaluating various analytical contexts, including planning, design, and 

operations/construction projects. 

Figure 1 presents an overview of the transportation analysis process, along with its 

various evaluation contexts and the types of traffic analysis tools that are typically used in 

each context. Typically, transportation analysis needs result from the policies and 

objectives of State/regional/local transportation plans and programs. A transportation 

improvement (project) goes through several phases, including planning, project 

development, design, implementation, and post-implementation operational assessment 

and modification. As shown in figure 1, each of these phases requires different analytical 

methodologies and tools. A project’s early planning stage usually involves the application 

of sketch-planning or travel demand modeling techniques. These methodologies help 

agencies screen the different transportation improvements, resulting in the selection of a 

few candidate transportation improvements. Later stages (such as project development or 

post-implementation modifications) usually involve the application of more rigorous and 

detailed techniques, such as traffic simulation and/or optimization. The role of traffic 

analysis tools is further explained in the following section. 

1.2 Role of Traffic Analysis Tools 

Traffic analysis tools are designed to assist transportation professionals in evaluating the 

strategies that best address the transportation needs of their jurisdiction. Specifically, 

traffic analysis tools can help practitioners: 

• Improve the decisionmaking process. Traffic analysis tools help practitioners arrive at 

better planning/engineering decisions for complex transportation problems. They are 

used to estimate the impact of the deployment of traffic management and other 

strategies, and to help set priorities among competing projects. In addition, they can 

provide a consistent approach for comparing potential improvements or alternatives. 

• Project potential future traffic. Traffic analysis tools can be used to project and 

analyze future traffic conditions. This is especially useful for planning long-term 

improvements and evaluating future impact. 

• Evaluate and prioritize planning/operational alternatives. This typically involves 

comparing “no build” conditions with alternatives, which include various types of 
4 

potential improvements. The impacts are reported as performance measures and are 

defined as the difference between the no-build and alternative scenarios. The results 

can be used to select the best alternative or prioritize improvements, increasing the 

odds of having a successful deployment. 

• Improve design and evaluation time and costs. Traffic analysis tools are relatively 

less costly when compared to pilot studies, field experiments, or full implementation 

costs. Furthermore, analytical tools can be used to assess multiple deployment 

combinations or other complex scenarios in a relatively short time. 

• Reduce disruptions to traffic. Traffic management and control strategies come in 

many forms and options, and analytical tools provide a way to cheaply estimate the 

effects prior to full deployment of the management strategy. They may be used to 

initially test new transportation management systems concepts without the 

inconvenience of a field experiment. 

• Present/market strategies to the public/stakeholders. Some traffic analysis tools have 

excellent graphical and animation displays, which could be used as tools to show 

“what if” scenarios to the public and/or stakeholders. 

• Operate and manage existing roadway capacity. Some tools provide optimization 

capabilities, recommending the best design or control scenarios to maximize the 

performance of a transportation facility. 

• Monitor performance. Analytical tools can also be used to evaluate and monitor the 

performance of existing transportation facilities. In the future, it is hoped that 

monitoring systems can be directly linked to analytical tools for a more direct and realtime analytical process. 
5 

Statewide Policies and Objectives

Statewide or Regional 

Transportation Plan and Program

• Sketch planning

• Travel demand models

Local Transportation Plans

Project Development (Geometric 

and Operational)

• Sketch planning

• HCM/Analytical methods

• Traffic simulation models

• Traffic optimization models

Environmental Impact Statement

Design and Implementation

Ongoing Operational Assessment 

and Modification

• Sketch planning

• HCM/Analytical methods

• Traffic simulation models

• Traffic optimization

Regional 

Environmental 

Analyses

Note: Boxes outlined by a bold line represent the primary realm of application of traffic 

analysis tools.

Interface with 

Other Regional 

Plans

Figure 1. Overview of the transportation analysis process. 
6 

1.3 Categories of Traffic Analysis Tools 

The intent of this document is to provide guidance on the selection of the appropriate type 

of analytical tool, not the specific tool. To date, numerous traffic analysis methodologies 

and tools have been developed by public agencies, research organizations, and various 

consultants. Traffic analysis tools can be grouped into the following categories: 

• Sketch-Planning Tools: Sketch-planning methodologies and tools produce general 

order-of-magnitude estimates of travel demand and traffic operations in response to 

transportation improvements. They allow for the evaluation of specific projects or 

alternatives without conducting an indepth engineering analysis. Sketch-planning 

tools perform some or all of the functions of other analytical tools using simplified 

analytical techniques and highly aggregated data. For example, a highway engineer 

can estimate how much it will cost to add a lane to an existing roadway simply by 

using sketch-planning techniques and without doing a complete site evaluation. 

Similarly, traffic volume-to-capacity ratios are often used in congestion analyses. Such 

techniques are primarily used to prepare preliminary budgets and proposals, and are 

not considered a substitute for the detailed engineering analysis often needed later in 

the implementation process. Therefore, sketch-planning approaches are typically the 

simplest and least costly of the traffic analysis techniques. However, sketch-planning 

techniques are usually limited in scope, analytical robustness, and presentation 

capabilities. 

• Travel Demand Models: Travel demand models have specific analytical capabilities, 

such as the prediction of travel demand and the consideration of destination choice, 

mode choice, time-of-day travel choice, and route choice, and the representation of 

traffic flow in the highway network. These are mathematical models that forecast 

future travel demand based on current conditions and future projections of household 

and employment characteristics. Travel demand models were originally developed to 

determine the benefits and impact of major highway improvements in metropolitan 

areas. However, they were not designed to evaluate travel management strategies, 

such as intelligent transportation systems (ITS)/operational strategies. Travel demand 

models only have limited capabilities to accurately estimate changes in operational 

characteristics (such as speed, delay, and queuing) resulting from implementation of 

ITS/operational strategies. These inadequacies generally occur because of the poor 

representation of the dynamic nature of traffic in travel demand models. 

• Analytical/Deterministic Tools (HCM-Based): Most analytical/deterministic tools 

implement the procedures of the Highway Capacity Manual (HCM). The HCM 

procedures are closed-form, macroscopic, deterministic, and static analytical 

procedures that estimate capacity and performance measures to determine the level of 

service (e.g., density, speed, and delay). They are closed-form because they are not 

iterative. The practitioner inputs the data and the parameters and, after a sequence of 

analytical steps, the HCM procedures produce a single answer. Moreover, the HCM 

procedures are macroscopic (input and output deal with average performance during 

a 15-minute or a 1-hour analytical period), deterministic (any given set of inputs will 
7 

always yield the same answer), and static (they predict average operating conditions 

over a fixed time period and do not deal with transitions in operations from one 

system state to another). As such, these tools quickly predict capacity, density, speed, 

delay, and queuing on a variety of transportation facilities and are validated with field 

data, laboratory test beds, or small-scale experiments. Analytical/deterministic tools are 

good for analyzing the performance of isolated or small-scale transportation facilities; 

however, they are limited in their ability to analyze network or system effects. The 

HCM procedures and their strengths and limitations are discussed in more detail in 

section 1.4. 

• Traffic Signal Optimization Tools: Similar to the analytical/deterministic tools, 

traffic optimization tool methodologies are mostly based on the HCM procedures. 

However, traffic optimization tools are primarily designed to develop optimal signal 

phasings and timing plans for isolated signal intersections, arterial streets, or signal 

networks. This may include capacity calculations; cycle length; splits optimization, 

including left turns; and coordination/offset plans. Some optimization tools can also 

be used for optimizing ramp metering rates for freeway ramp control. The more 

advanced traffic optimization tools are capable of modeling actuated and semi-actuated 

traffic signals, with or without signal coordination. 

• Macroscopic Simulation Models: Macroscopic simulation models are based on the 

deterministic relationships of the flow, speed, and density of the traffic stream. The 

simulation in a macroscopic model takes place on a section-by-section basis rather 

than by tracking individual vehicles. Macroscopic simulation models were originally 

developed to model traffic in distinct transportation subnetworks, such as freeways, 

corridors (including freeways and parallel arterials), surface-street grid networks, and 

rural highways. They consider platoons of vehicles and simulate traffic flow in brief 

time increments. Macroscopic simulation models operate on the basis of aggregate 

speed/volume and demand/capacity relationships. The validation of macroscopic 

simulation models involves replication of observed congestion patterns. Freeway 

validation is based on both tachometer run information and speed contour diagrams 

constructed for the analytical periods, which are then aggregated to provide a 

“typical” congestion pattern. Surface-street validation is based on speed, queue, delay, 

and capacity information. Macroscopic models have considerably fewer demanding 

computer requirements than microscopic models. They do not, however, have the 

ability to analyze transportation improvements in as much detail as microscopic 

models, and do not consider trip generation, trip distribution, and mode choice in 

their evaluation of changes in transportation systems. 

• Mesoscopic Simulation Models: Mesoscopic models combine the properties of both 

microscopic (discussed below) and macroscopic simulation models. As in microscopic 

models, the unit of traffic flow for mesoscopic models is the individual vehicle. Similar 

to microscopic simulation models, mesoscopic tools assign vehicle types and driver 

behavior, as well as their relationships with roadway characteristics. Their movement, 

however, follows the approach of macroscopic models and is governed by the average 

speed on the travel link. Mesoscopic model travel prediction takes place on an 

aggregate level and does not consider dynamic speed/volume relationships. As such, 
8 

mesoscopic models provide less fidelity than microsimulation tools, but are superior 

to the typical planning analysis techniques. 

• Microscopic Simulation Models: Microscopic simulation models simulate the 

movement of individual vehicles based on car-following and lane-changing theories. 

Typically, vehicles enter a transportation network using a statistical distribution of 

arrivals (a stochastic process) and are tracked through the network over brief time 

intervals (e.g., 1 second or a fraction of a second). Typically, upon entry, each vehicle is 

assigned a destination, a vehicle type, and a driver type. In many microscopic 

simulation models, the traffic operational characteristics of each vehicle are influenced 

by vertical grade, horizontal curvature, and superelevation, based on relationships 

developed in prior research. The primary means of calibrating and validating 

microscopic simulation models are through the adjustment of driver sensitivity 

factors. Computer time and storage requirements for microscopic models are 

significant, usually limiting the network size and the number of simulation runs that 

can be completed. 

1.4 Comparison of HCM and Simulation 

The intent of this section is to provide an overview of the strengths and limitations of the 

HCM and traffic simulation tools and to provide additional guidance on assessing when 

traffic simulation may be more appropriate than the HCM-based methods or tools. 

1.4.1 Overview of HCM 

HCM is a compilation of peer-reviewed procedures for computing the capacity and 

operational performance of various transportation facilities. HCM was first produced in 

1950 and has undergone many major revisions since then. It is currently published by the 

Transportation Research Board. The current edition of HCM was produced in 2000. 

Highway Capacity Manual 2000 (HCM 2000) has more than 1,100 pages and 30 chapters. 

Parts I and II of the manual present introductory information on capacity and the quality 

of service analysis. Part III presents the actual analytical procedures. Part IV provides 

information on applying HCM to corridor and areawide planning analyses. Part V 

provides introductory materials on models that go beyond the HCM procedures described 

in part III. 

Each chapter in part III focuses on a specific facility type and capacity analysis problem. 

For example, there are four chapters devoted to freeway facilities: freeway facilities, basic 

freeway segments, ramps and ramp junctions, and freeway weaving. There are three 

chapters devoted to the analysis of urban facilities: urban streets, signalized intersections, 

and unsignalized intersections. There are also chapters that cover procedures for the 

analysis of multilane highways, two-lane rural roads, transit, pedestrian facilities, and 

bicycle facilities. 
9 

The HCM procedures are closed-form, macroscopic, deterministic, and static analytical 

procedures that estimate capacity, and performance measures to determine the level of 

service (e.g., density, speed, and delay). They are closed-form because they are not 

iterative. The practitioner inputs the data and parameters, and after a sequence of 

analytical steps, the HCM procedures produce a single answer. In general, the HCM 

procedures have the following characteristics: 

• Macroscopic: HCM’s input and output deal with average performance during a 15-

minute or 1-hour analytical period. 

• Deterministic: Any given set of input will always yield the same answer. 

• Static: The HCM procedures predict average operating conditions over a fixed time 

period and do not deal with transitions in operation from one system state to another 

(such as would be addressed in a dynamic analysis). 

1.4.2 HCM Strengths and Limitations 

For many applications, HCM is the most widely used and accepted traffic analysis 

technique in the United States. The HCM procedures are good for analyzing the 

performance of isolated facilities with relatively moderate congestion problems. These 

procedures are quick and reliable for predicting whether or not a facility will be operating 

above or below capacity, and they have been well tested through significant fieldvalidation efforts. However, the HCM procedures are generally limited in their ability to 

evaluate system effects. 

Most of the HCM methods and models assume that the operation of one intersection or 

road segment is not adversely affected by conditions on the adjacent roadway. Long 

queues at one location that interfere with another location would violate this assumption. 

The HCM procedures are of limited value in analyzing queues and the effects of the 

queues. 

There are also several gaps in the HCM procedures. HCM is a constantly evolving and 

expanding set of analytical tools and, consequently, there are still many real-world 

situations for which HCM does not yet have a recommended analytical procedure. The 

following list identifies some of these gaps: 

• Multilane or two-lane rural roads where traffic signals or stop signs significantly 

impact capacity and/or operations. 

• Climbing lanes for trucks. 

• Short through-lane is added or dropped at a signal. 

• Two-way left-turn lanes. 
10 

• Roundabouts of more than a single lane. 

• Tight diamond interchanges. 

Appendix A summarizes the limitations of HCM based on information listed in HCM 

2000. 

1.4.3 Simulation Strengths and Limitations 

Simulation tools are effective in evaluating the dynamic evolution of traffic congestion 

problems on transportation systems. By dividing the analytical period into time slices, a 

simulation model can evaluate the buildup, dissipation, and duration of traffic congestion. 

By evaluating systems of facilities, simulation models can evaluate the interference that 

occurs when congestion builds up at one location and impacts capacity at another location. 

Also, traffic simulators can model the variability in driver/vehicle characteristics. 

Simulation tools, however, require a plethora of input data, considerable error checking of 

the data, and manipulation of a large amount of potential calibration parameters. Simulation 

models cannot be applied to a specific facility without calibration of those parameters to 

actual conditions in the field. Calibration can be a complex and time-consuming process. 

The algorithms of simulation models are mostly developed independently and are not 

subject to peer review and acceptance in the professional community. There is no national 

consensus on the appropriateness of a simulation approach. 

Simulation models, for all their complexity, also have limitations. Commercially available 

simulation models are not designed to model the following: 

• Two-way left-turn lanes. 

• Impact of driveway access: Major driveways can be modeled as unsignalized Tintersections. However, models cannot address the impact of numerous minor 

driveways along a street segment (link). They can only be approximately modeled as a 

midblock sink or node. 

• Impact of onstreet parking, commercial vehicle loading, and double parking (although 

such conditions may be approximately modeled as short-term incidents). 

• Interferences that can occur among bicycles, pedestrians, and vehicles sharing the 

same roadway. 

Simulation models also assume “100 percent safe driving,” so they will not be effective in 

predicting how changes in design might influence the probability of collisions. In 

addition, simulation models do not take into consideration how changes in the roadside 

environment (outside of the traveled way) affect driver behavior within the traveled way 

(e.g., obstruction of visibility, roadside distractions such as a stalled vehicle, etc.). 
11 

1.4.4 Traffic Performance Measures: Differences Between HCM and 

Simulation 

The HCM methodologies and tool procedures take a static approach to predicting traffic 

performance; simulation models take a dynamic approach. HCM estimates the average 

density, speed, or delay over the peak 15 minutes of an hour, while simulation models 

predict density, speed, and delay for each time slice within the analytical period (which 

can be longer than an hour). 

Not only are there differences in approach, there are differences in the definitions of the 

performance measures produced by simulation models and the HCM tools. Some of the 

most notable differences include: 

• Simulation models report density for actual vehicles, while HCM reports density in 

terms of equivalent passenger cars (trucks and other heavy vehicles are counted more 

than once in the computation of density). 

• Simulation models report vehicle flow in terms of actual vehicles, while HCM reports 

capacity for freeways and highways in terms of passenger-car equivalents. 

• Simulation models report delay only on the street segment where the vehicles are 

slowed down, while HCM reports all delays caused by a given bottleneck (regardless 

of the actual physical location of the vehicles). 

• Simulation models report queues only on the street segment where the vehicles are 

actually queued, while HCM reports all queued vehicles resulting from a given 

bottleneck (regardless of the actual physical location of the vehicles). 

• Simulation models do not necessarily report control delay at signalized intersections. 

The reported values include midblock delays for the vehicles traveling along the link, 

or only stopped delay at the traffic signal. 

1.4.5 Strategy for Overcoming the Limitations of HCM 

Once a transportation professional has decided that the HCM procedures do not meet the 

needs of the analysis, the next step is to determine whether microscopic, mesoscopic, or 

macroscopic simulation is required. There are several simulation programs available for 

evaluating a variety of transportation improvements, facilities, modes, traveler responses, 

and performance measures. These analytical tools vary in their data requirements, 

capabilities, methodology, and output. In addition, the performance measures for the 

simulation models and the HCM procedures may differ in definition and/or methodology 

(e.g., the number of stops may be estimated at speeds of less than 8 kilometers per hour 

(km/h) (5 miles per hour (mi/h)) in one tool, but at 0 km/h for another). 

If it is not necessary to microscopically trace individual vehicle movement, then the 

analyst can take advantage of the simpler data entry and control optimization features 
12 

available in many macroscopic simulation models. However, macroscopic models often 

have to make certain assumptions of regularity in order to be able to apply macroscopic 

vehicle behavior relationships. If these assumptions are not valid for the situation being 

studied, then the analyst must resort to mesoscopic or microscopic simulation. 

Simulation models require a considerable amount of detailed data for input, calibration, 

and validation. In general, microscopic simulation models have more demanding data 

requirements than mesoscopic and macroscopic models. Simulation models are also more 

complicated and require a considerable amount of effort to gain an understanding of the 

assumptions, parameters, and methodologies involved in the analysis. The lack of 

understanding of these tools often makes credibility and past performance 

(use/popularity) a major factor in the selection of a particular simulation tool. 

More information on this issue may be found in Guidelines for Applying Traffic 

Microsimulation Modeling Software (Volume III). 
13 

2.0 Criteria for Selecting the Appropriate Type 

of Traffic Analysis Tool 

This section identifies criteria that can be considered in the selection of an appropriate 

traffic analysis tool and helps identify under what circumstances a particular tool should 

be used. Section 3.0 of this document contains guidance on how to use this information to 

select the appropriate tool. 

Sections 2.1 and 2.2 present the criteria a user should consider when selecting a type of 

traffic analysis tool. The first step is identification of the analytical context for the task—

planning, design, or operations/construction. Seven additional criteria are necessary to 

help identify the analytical tools that are most appropriate for a particular project. 

Depending on the analytical context and the project’s goals and objectives, the relevance 

of each criterion may differ. The criteria include: 

1. Ability to analyze the appropriate geographic scope or study area for the analysis, 

including isolated intersection, single roadway, corridor, or network. 

2. Capability of modeling various facility types, such as freeways, high-occupancy 

vehicle (HOV) lanes, ramps, arterials, toll plazas, etc. 

3. Ability to analyze various travel modes, such as single-occupancy vehicle (SOV), 

HOV, bus, train, truck, bicycle, and pedestrian traffic. 

4. Ability to analyze various traffic management strategies and applications, such as 

ramp metering, signal coordination, incident management, etc. 

5. Capability of estimating traveler responses to traffic management strategies, including 

route diversion, departure time choice, mode shift, destination choice, and 

induced/foregone demand. 

6. Ability to directly produce and output performance measures, such as safety 

measures (crashes, fatalities), efficiency (throughput, volumes, vehicle-miles of travel 

(VMT)), mobility (travel time, speed, vehicle-hours of travel (VHT)), productivity (cost 

savings), and environmental measures (emissions, fuel consumption, noise). 

7. Tool/cost-effectiveness for the task, mainly from a management or operational 

perspective. Parameters that influence cost-effectiveness include tool capital cost, level 

of effort required, ease of use, hardware requirements, data requirements, animation, 

etc. 

Each analytical tool category was evaluated against each criterion to identify whether or 

not a category of analytical tool was appropriate for use. This evaluation is presented in 

the form of matrices. In each matrix cell, a value has been assigned to each tool category 
14 

according to its relevance or applicability to the corresponding criterion. A solid circle (●) 

indicates that the particular tool category adequately addresses the criterion. An empty 

circle (○) indicates that the traffic analysis tool category poorly addresses the specific 

criterion. A null symbol (∅) indicates that some tools within the tool category may address 

the criterion and others may not. Not applicable (N/A) indicates that the particular tool 

category does not address the corresponding criterion at all and should not be used for the 

analysis. 

Figure 2 below summarizes the criteria that may be considered for the selection of a tool 

category. 

The steps for selecting the appropriate type of analytical tool are: 

1. Users should begin by identifying the project’s analytical context (discussed in 

section 2.1). 

2. Next, users should filter through criteria 1 through 6 to limit the appropriate tool 

categories to one or two options (as discussed in sections 2.2.1 through 2.2.6). 

3. Finally, criterion 7 (tool/cost effectiveness) should be used to select the final tool 

category (presented in section 2.2.7) based on parameters outside of the technical 

context of the analysis, such as tool cost, training, hardware requirements, etc. 

Step-by-step guidance for the tool selection process is presented in section 3.0. An 

automated tool that implements the guidance can be found at the FHWA Traffic Analysis 

Tools Web site at: 

http://ops.fhwa.dot.gov/Travel/Traffic_Analysis_Tools/traffic_analysis_tools.htm

Finally, a listing of available tools for each category and their Web site links are provided 

in section 4.0. 

2.1 Analytical Context 

The first step in selecting the appropriate type of traffic analysis tool is the identification of 

the analytical context of the project. Figure 2 illustrates a typical transportation analysis 

process, which contains several analytical phases, including: 

• Planning: This phase includes short- or long-term studies or other State, regional, or 

local transportation plans (e.g., master plans, congestion management plans, ITS 

strategic plans, etc.). 
What is your 

study area?

Isolated LocationSegmentCorridor/ Small NetworkRegion

Which facility 

types do you 

want to 

include?

Isolated IntersectionRoundaboutArterialHighwayFreewayHOV LaneHOV Bypass LaneRampAuxiliary LaneReversible LaneTruck LaneBus LaneToll PlazaLight Rail Line

Which travel 

modes do you 

want to 

include?

SOVHOV (2, 3, 3+)BusRailTruckMotorcycleBicyclePedestrian

Which 

management 

strategies should 

be analyzed?

Freeway MgmtArterial IntersectionsArterial MgmtIncident MgmtEmergency MgmtWork ZoneSpec EventAPTSATISElectronicPaymentRRXCVOAVCSSWeather MgmtTDM

Which traveler 

responses 

should be 

analyzed?

Route Diversion

− Pre-Trip− En-Route

Mode ShiftDeparture Time ChoiceDestination ChangeInduced/ Foregone Demand

What 

performance 

measures are 

needed?

LOSSpeedTravel TimeVolumeTravel DistanceRidershipAVOv/c RatioDensityVMT/PMTVHT/PHTDelay Queue Length# StopsCrashes/ DurationTT ReliabilityEmissions/ Fuel ConsumpNoiseMode SplitBenefit/Cost

What 

operational 

characteristics 

are necessary?

Tool Capital CostEffort (Cost/ Training)Ease of UsePopular/WellTrustedHardware RequirementsData RequirementsComputer RunTimePost-ProcessingDocumentationUser SupportKey Parameters User DefinableDefault ValuesIntegrationAnimation/ Presentation

1

Geographic 

Scope

2

Facility 

Type

3

Travel

Mode

4

Management

Strategy

5

Traveler

Response

6

Performance

Measures

7

Tool/CostEffectiveness

Analysis Context: 

Planning, Design, or Operations/Construction

Figure 2. Criteria for selecting a traffic analysis tool category. 

15 
16 

• Design: This phase includes approved and funded projects that are going through 

analysis of the alternatives or preliminary design to determine the best option for 

implementation. This phase also includes the analysis of roadway features needed to 

operate at a desired level of service (LOS). Full design projects (e.g., 

horizontal/vertical alignments, pavement design, etc.) are not included in this 

category. 

• Operations/Construction: These projects share many similar characteristics with 

design projects, but are performed to determine the best approach for optimizing or 

evaluating existing systems. 

Table 1 presents the general relevance of each tool category for each analytical context, 

including planning, design, and operations/construction. 

Table 1. Relevance of traffic analysis tool categories with respect to analytical context. 

Analytical Tools/Methodologies 

Analytical 

Context

Sketch 

Planning

Travel 

Demand 

Models 

Analytical/ 

Deterministic 

Tools (HCMBased)

Traffic 

Optimization Macroscopic 

Simulation 

Mesoscopic 

Simulation 

Microscopic 

Simulation 

Planning ● ● ∅ ○ ∅ ∅ ○

Design N/A ∅ ● ● ● ● ●

Operations/ 

Construction ∅ ○ ● ● ● ● ●

Notes: ● Specific context is generally addressed by the corresponding analytical tool/methodology. 

∅ Some of the analytical tools/methodologies address the specific context and some do not. 

○ The particular analytical tool/methodology does not generally address the specific context. 

 N/A The particular methodology is not appropriate for use in addressing the specific context. 

Notes and Assumptions: 

• The role of these tools may vary according to the analytical context. For example, the 

use of simulation can differ considerably for planning versus operations. In planning, 

the system does not exist and modeling or simulation is necessary for analyzing 

alternatives. However, when considering traffic-responsive control measures for an 

existing system, real measurements should first be considered, while simulation plays 

a secondary role. 

2.2 Criteria for Analytical Tool Selection and Assessment of Tool 

Capabilities 

Criteria 1 through 7 from figure 2 are discussed in the following sections, with the first six 

criteria focusing on the various technical aspects of the analysis (e.g., facility type, travel 
17 

mode, management strategy, etc.), while criterion 7 helps to identify the best tool category 

from a management/operational perspective. 

2.2.1 Study Area/Geographic Scope 

Traffic analysis tools have varying degrees of capabilities with respect to the analytical 

environment and geographic scope of the project. Table 2 summarizes the general 

relevance of each tool category based on the study area/geographic scope appropriate for 

the task. Four types of study areas are included: 

• Isolated Location: Limited study area, such as a single intersection or interchange. 

• Segment: Linear or small-grid roadway network. 

• Corridor/Small Network: Expanded study area that typically includes one major 

corridor with one or two parallel arterials and their connecting cross-streets, typically 

less than 520 square kilometers (km2) (200 square miles (mi2)). 

• Region: Citywide or countywide study area involving all freeway corridors and major 

arterials, typically 520 km2 (200 mi2) or larger. 

Notes and Assumptions: 

• The study area/geographic scope is the only criterion that has varying relevance with 

respect to the analytical context. The user should identify both the analytical context 

and the study area type for this matrix. 

• For the traffic simulation tool categories (macroscopic, mesoscopic, and microscopic 

simulations), the geographic area relevance factors are identical because, in general, 

simulation tools feature the same geographic areas (e.g., segment, corridor, etc.), but 

with varying levels of detail. 

• Typically, analytical/deterministic tools are based on the HCM procedures, which are 

more focused on single roadways or isolated locations rather than on a network or a 

roadway grid system. 
18 

Table 2. Relevance of traffic analysis tool categories with respect to study 

area/geographic scope. 

Analytical Tools/Methodologies 

Analytical 

Context/ 

Geographic 

Scope

Sketch 

Planning

Travel 

Demand 

Models 

Analytical/ 

Deterministic 

Tools (HCMBased)

Traffic 

Optimization Macroscopic 

Simulation 

Mesoscopic 

Simulation 

Microscopic 

Simulation 

Planning

Isolated 

Location ○ ○ ● ∅ ○ ○ ○

Segment ● ○ ● 1 ○ ∅ ∅ ∅

Corridor/ 

Small 

Network 

∅ ● ○ ○ ∅ ∅ ∅

Region ∅ ● N/A N/A N/A N/A N/A 

Design

Isolated 

Location N/A N/A ● ● ● ∅ ●

Segment N/A ○ ● ∅ ● ● ●

Corridor/ 

Small 

Network 

N/A ∅ ○ ○ ● ● ●

Region N/A ∅ N/A N/A ○ ○ ∅

Operations/Construction

Isolated 

Location N/A N/A ● ● ● ∅ ●

Segment ∅ ○ ● ● ● ● ●

Corridor/ 

Small 

Network 

N/A ∅ ○ ∅ ● ● ●

Region N/A ∅ N/A N/A ∅ ○ ∅

Notes: ● Specific context is generally addressed by the corresponding analytical tool/methodology. 

∅ Some of the analytical tools/methodologies address the specific context and some do not. 

○ The particular analytical tool/methodology does not generally address the specific context. 

 N/A The particular methodology is not appropriate for use in addressing the specific context. 

 1For linear networks 

2.2.2 Facility Type 

This section discusses the ability of the tools to analyze various facility types. Definitions 

for the facility types were based on HCM 2000. The relevance of the analytical tool 

categories with respect to the facility-type criterion is presented in table 3. The facility 

types include: 
19 

Table 3. Relevance of traffic analysis tool categories with respect to facility type. 

Analytical Tools/Methodologies 

Facility 

Type

Sketch 

Planning

Travel 

Demand 

Models 

Analytical/ 

Deterministic 

Tools (HCMBased)

Traffic 

Optimization Macroscopic 

Simulation 

Mesoscopic 

Simulation 

Microscopic 

Simulation 

Isolated 

Intersection ○ ∅ ● ● ● ● ●

Roundabout ○ ○ ● ○ ∅ ○ ∅

Arterial ● ● ● ● ● ● ●

Highway ● ● ● ∅ ● ● ●

Freeway ∅ ● ● ∅ ● ● ●

HOV Lane ∅ ● ∅ ○ ● ● ●

HOV Bypass 

Lane ○ ● ○ ∅ ∅ ∅ ●

Ramp ∅ ● ● ● ● ● ●

Auxiliary 

Lane ○ ○ ∅ ∅ ● ● ●

Reversible 

Lane ○ ∅ ○ ○ ○ ○ ∅

Truck Lane ○ ● ∅ ∅ ∅ ○ ●

Bus Lane ○ ● ○ ○ ∅ ○ ●

Toll Plaza ○ ∅ ∅ ○ ○ ○ ●

Light-Rail 

Line ○ ● ○ ○ ○ ○ ●

Notes: ● Specific context is generally addressed by the corresponding analytical tool/methodology. 

∅ Some of the analytical tools/methodologies address the specific context and some do not. 

○ The particular analytical tool/methodology does not generally address the specific context. 

• Isolated Intersection: Single crossing point between two or more roadway facilities. 

• Roundabout: Unsignalized intersection with a circulatory roadway around a central 

island with all entering vehicles yielding to circulating traffic. 

• Arterial: Signalized street that primarily serves through traffic and that secondarily 

provides access to abutting properties (signal spacing of 3.2 kilometers (km) (2 miles 

(mi)) or less. 

• Highway: High-speed roadway connecting major areas or arterials, with little or no 

traffic signal interruption (e.g., two-lane highway, expressway). 

• Freeway: Multilane, divided highway with a minimum of two lanes for the exclusive 

use of traffic in each direction and full control of access without traffic interruption. 
20 

• HOV Lane: Exclusive highway or street lane for vehicles with a defined minimum 

number of occupants (more than one), including buses, taxis, or carpools (may be used 

by other traffic under certain circumstances, such as during off-peak hours, for making 

a right or left turn, or by motorcycles, depending on the jurisdiction’s traffic laws). 

• HOV Bypass Lane: Exclusive on-ramp lane for vehicles with a defined minimum 

number of occupants (more than one), including buses, taxis, carpools, for specified 

time periods. 

• Ramp: Short segment of roadway connecting two roadway facilities. 

• Auxiliary Lane: Additional lane on a freeway to connect an on-ramp and an off-ramp. 

• Reversible Lane: Roadway lane that changes directions during different hours of the 

day (reversible lanes are typically used to help alleviate congestion by accommodating 

the peak direction of traffic). 

• Truck Lane: Designated lane for commercial vehicles, but not for public transit vehicles. 

• Bus Lane: Highway or street lane reserved primarily for buses during specified 

periods (may be used by other traffic under certain circumstances, such as for making 

a right or left turn, or by taxis, motorcycles, or carpools that meet the requirements of 

the jurisdiction’s traffic laws). 

• Toll Plaza: Facility where payment transaction for the use of the roadway takes place 

(may be located upstream or downstream of the toll facility). 

• Light-Rail Line: Electric-powered railway system operating single cars or short trains 

on a variety of alignment types on a partially controlled right-of-way. 

Notes and Assumptions: 

• Generally, it is not appropriate to optimize a two-lane highway or roundabout. 

2.2.3 Travel Mode 

Table 4 presents a matrix rating the appropriateness of each tool category in analyzing the 

different travel modes. The definitions for the travel modes are based on HCM 2000: 

• SOV: Vehicle with the driver as the only occupant. 

• HOV: Vehicle with a defined minimum number of occupants (more than one), including 

buses, taxis, carpools, and vanpools. 

• Bus: Self-propelled, rubber-tired road vehicle designed to carry a substantial number 

of passengers and commonly operated on streets and highways. 
21 

Table 4. Relevance of traffic analysis tool categories with respect to travel mode. 

Analytical Tools/Methodologies 

Travel 

Mode

Sketch 

Planning

Travel 

Demand 

Models 

Analytical/ 

Deterministic 

Tools (HCMBased)

Traffic 

Optimization 

Macroscopic 

Simulation 

Mesoscopic 

Simulation 

Microscopic 

Simulation 

SOV ● ● ● ● ● ● ●

HOV ∅ ● ∅ ∅ ∅ ● ●

Bus ∅ ● ∅ ∅ ∅ ● ●

Rail ∅ ● ○ ○ ○ ∅ ∅

Truck ∅ ∅ ∅ ∅ ∅ ∅ ∅

Motorcycle ○ ∅ ○ ○ ○ ○ ○

Bicycle ∅ ∅ ∅ ○ ○ ○ ∅

Pedestrian ∅ ○ ∅ ∅ ∅ ∅ ∅

Notes: ● Specific context is generally addressed by the corresponding analytical tool/methodology. 

∅ Some of the analytical tools/methodologies address the specific context and some do not. 

○ The particular analytical tool/methodology does not generally address the specific context. 

• Rail: Transit system using trains operating in exclusive or shared rights-of-way 

(includes both light and heavy rail systems). 

• Truck: Heavy vehicle engaging primarily in the transport of goods and materials or in 

the delivery of services other than public transportation. 

• Motorcycle: Self-propelled vehicle with two wheels in tandem that may be ridden by a 

maximum of two persons. 

• Bicycle: Vehicle with two wheels in tandem that is propelled by human power and is 

usually ridden by one person. 

• Pedestrian: Individual traveling on foot. 

2.2.4 Management Strategy and Applications 

The following are the major classifications of transportation management strategies 

(adapted from the National ITS Architecture): 

• Freeway Management: Controls, guides, and warns traffic in order to improve the 

flow of people and goods on limited-access facilities. Examples of freeway 

management include the integration of surveillance information with freeway road 
22 

geometry; vehicle control, such as ramp metering; dynamic message signs (DMS); and 

highway advisory radio (HAR). 

• Arterial Intersections: Includes intersection or arterial operations, such as geometric 

improvements, parking adjustments, and signal timing for individual intersections. 

These improvements would typically involve capacity analysis, LOS analysis, and 

unsignalized and signalized intersection studies. 

• Arterial Management: Applies State and local planning, capital, and regulatory and 

management tools to enhance and/or preserve the transportation functions of the 

arterial roadway through the use of surveillance devices, advanced signal algorithms, 

and coordination. 

• Incident Management: Manages unexpected incidents so that the impact on the 

transportation network and traveler safety is minimized. Includes incident detection 

capabilities through roadway surveillance devices and incident response through 

coordination with freeway service patrols and emergency response agencies. 

• Emergency Management: Represents public safety and other agency systems that 

support coordinated emergency response, including police, fire, emergency medical 

services, hazardous materials (HazMat) response teams, Mayday service providers, 

and security/surveillance services that improve traveler security in public areas. 

• Work Zones: Uses traffic control devices (signs, channeling devices, barriers, etc.) and 

traveler information to maximize the availability of roadways during construction or 

maintenance while minimizing the impact on the traveling public and highway 

workers. 

• Special Events: Manages planned events so that the impact on the transportation 

network and traveler safety is minimized through coordination with other traffic 

management, maintenance and construction management, and emergency 

management centers, and event promoters. 

• Advanced Public Transportation System (APTS): Applies advanced technologies to 

the operations, maintenance, customer information, planning, and management 

functions for the transit agency. APTS includes advanced communications between 

the transit departments and the public, personnel and other operating entities such as 

emergency response services, and traffic management systems; automatic vehicle 

locator (AVL); traffic signal priority; transit operations software; advanced transit 

scheduling systems (ATSS); transit security; and fleet maintenance. 

• Advanced Traveler Information System (ATIS): Ranges from simply providing fixed 

transit schedule information to multimodal traveler information, including real-time 

traffic conditions and transit schedules, and information to support mode and route 

selection. 
23 

• Electronic Payment System: Allows travelers to pay for transportation services by 

electronic means, including tolls, transit fares, and parking. 

• Rail Grade Crossing Monitors: Manages traffic at highway-rail intersections where 

operational requirements demand advanced features. Includes the capabilities from 

the Standard Rail Crossing equipment package and augments these with additional 

safety features, including positive barrier systems and wayside interface equipment 

that detects or communicates with the approaching train. 

• Commercial Vehicle Operations (CVO): Performs advanced functions that support 

commercial vehicle operations, including communications between drivers, fleet 

managers, and roadside officials; automates identification and safety processing at 

mainline speeds; and timely and accurately collects HazMat cargo information after a 

vehicle incident. 

• Advanced Vehicle Control and Safety System (AVCSS): Includes vehicle safety 

systems such as vehicle or driver safety monitoring; longitudinal, lateral, or 

intersection warning control or collision avoidance; pre-crash restraint; and automated 

highway systems. 

• Weather Management: Includes automated collection of weather condition data and 

the use of that data to detect hazards such as ice, high winds, snow, dense fog, etc. 

This information can be used to provide road condition information and more 

effectively deploy maintenance and construction resources. 

• Travel Demand Management (TDM): TDM strategies are designed to maximize 

person throughput or influence the need for or time of travel. They are typically 

implemented in urban areas to reduce traffic congestion and air pollution, and to 

increase the efficiency of the transportation system. TDM strategies include employer 

trip reduction programs, vanpool programs, the construction of park-and-ride lots, 

and alternative work schedules. 

Table 5 summarizes tool category relevance for analyzing major traffic management 

strategies. A more detailed listing of management strategies, which can be helpful in the 

selection of a specific traffic analysis tool, is presented in appendix C. 

Notes and Assumptions: 

• Some analytical/deterministic tools can estimate the impact of incidents, work zones, 

special events, and weather through reductions in capacity for specific times and 

locations. However, they cannot model the temporal and spatial effects of congestion. 

• Macroscopic and mesoscopic models assume macroscopic traffic behavior (e.g., all 

vehicles travel at the same average speed). Therefore, they are not well suited to 

evaluate traffic management strategies that require the sensing of individual vehicles 

(e.g., adaptive control at individual intersections or arterials). 
24 

Table 5. Relevance of traffic analysis tool categories with respect to management 

strategy and applications. 

Analytical Tools/Methodologies 

Management 

Strategy and 

Applications

Sketch 

Planning

Travel 

Demand 

Models 

Analytical/ 

Deterministic 

Tools (HCMBased)

Traffic 

Optimization Macroscopic 

Simulation 

Mesoscopic 

Simulation 

Microscopic 

Simulation 

Freeway 

Management ● ∅ ∅ ● ● ● ●

Arterial 

Intersections ○ ○ ● ● ● ● ●

Arterial 

Management ∅ ∅ ∅ ● ● ● ●

Incident 

Management ∅ ○ ∅ ○ ● ● ●

Emergency 

Management ∅ ○ ∅ ○ ∅ ∅ ∅

Work Zones ∅ ○ ● ○ ● ● ●

Special Events ∅ ○ ● ○ ∅ ∅ ∅

Advanced 

Public 

Transportation 

System 

∅ ○ ○ ○ ○ ○ ∅

Advanced 

Traveler 

Information 

System 

∅ ○ ○ ○ ∅ ∅ ∅

Electronic 

Payment 

System 

∅ ○ ○ ○ ○ ○ ●

Rail Grade 

Crossing 

Monitors 

∅ ○ ○ ○ ○ ○ ●

Commercial 

Vehicle 

Operations 

∅ ○ ○ ○ ○ ○ ∅

Advanced 

Vehicle 

Control and 

Safety System 

∅ ○ ○ ○ ○ ○ ∅

Weather 

Management ○ ○ ○ ○ ∅ ∅ ∅

Travel 

Demand Mgmt ● ● ∅ ○ ∅ ∅ ∅

Notes: ● Specific context is generally addressed by the corresponding analytical tool/methodology. 

∅ Some of the analytical tools/methodologies address the specific context and some do not. 

○ The particular analytical tool/methodology does not generally address the specific context. 
25 

2.2.5 Traveler Response 

In response to different operational improvements, travelers can change their route of 

travel, change their time of travel (temporal choice), can use a different mode of 

transportation, change their destination, or completely cancel or create a new trip 

(induced/foregone demand). Table 6 indicates how well or how poorly the analytical tool 

categories can model the following traveler responses: 

• Route Diversions: Captures changes in travel routes, including pre-trip route 

diversion and en route diversion.

• Mode Shifts: Captures changes regarding the selection of travel modes.

• Departure Time Choices: Captures changes in the time of travel.

• Destination Changes: Represents changes to travel destinations.

• Induced/Foregone Demand: Estimates new trips (induced demand) or foregone trips 

resulting from the implementation of traffic management strategies. 

Table 6. Relevance of traffic analysis tool categories with respect to traveler response. 

Analytical Tools/Methodologies 

Traveler 

Response

Sketch 

Planning

Travel 

Demand 

Models 

Analytical/ 

Deterministic 

Tools (HCMBased)

Traffic 

Optimization Macroscopic 

Simulation 

Mesoscopic 

Simulation 

Microscopic 

Simulation 

Route 

Diversion 

Pre-Trip ∅ ○ N/A ○ ● ● ●

En Route ∅ ● N/A ○ ∅ ∅ ∅

Mode Shift ∅ ● N/A ○ ∅ ∅ ∅

Departure 

Time Choice ∅ ○ N/A ○ ∅ ∅ ∅

Destination 

Change N/A ∅ N/A N/A N/A ○ ○

Induced/ 

Foregone 

Demand 

∅ ∅ N/A N/A N/A N/A ∅

Notes: ● Specific context is generally addressed by the corresponding analytical tool/methodology. 

∅ Some of the analytical tools/methodologies address the specific context and some do not. 

○ The particular analytical tool/methodology does not generally address the specific context. 

 N/A The particular methodology is not appropriate for use in addressing the specific context. 
26 

Notes and Assumptions: 

• Analytical/deterministic models assume that traffic demand is fixed throughout the 

analytical period. Although it may be possible to specify changes in demand (e.g., 

changes caused by diversion during an incident), the amount of diverted traffic and 

the time periods must be specified a priori by the analyst. 

• Most models require that the origin-destination (O-D) distribution be provided. Some 

mesoscopic models are capable of updating the O-D trips in real time; however, they 

may not be capable of modeling the destination choice. 

• For ramp metering strategies, some traffic optimization modules may be used to 

determine optimal ramp metering rates. 

• Most traffic optimization models assume constant demand. 

• Most traffic analysis tools are not capable of predicting destination changes or 

induced/foregone demand as a result of transportation improvements. Readers of this 

document should consider this when applying criteria weights to these items in the 

tool selection worksheet (appendix B). 

2.2.6 Performance Measures 

This section discusses the ability of the tool categories to produce various performance 

measures in the areas of safety, efficiency, mobility, productivity, and the environment (as 

summarized in table 7). The performance measures discussed in this section include: 

• Level of Service (LOS): Qualitative measure describing operational conditions within 

a traffic stream, based on service measures such as speed and travel time, freedom to 

maneuver, traffic interruptions, comfort, and convenience. Ranges from LOS A (best) 

to LOS F (worst).

• Speed: Rate of motion (expressed in distance per unit of time).

• Travel Time: Average time spent by vehicles traversing a facility, including control 

delay, in seconds or minutes per vehicle.

• Volume: Number of persons or vehicles passing a point on a roadway during some 

time interval (expressed in vehicles, bicycles, or persons per hour).

• Travel Distance: Extent of the space between the trip origin and the destination, 

measured along a vehicular route.

• Ridership: Number of passengers on the transit system being evaluated.

• Average Vehicle Occupancy (AVO): Average number of persons per vehicle, 

including transit vehicles, on the transportation facility or system. 
27 

• Volume-to-Capacity (V/C) Ratio: Ratio of flow rate to capacity for a transportation 

facility.

• Density: Number of vehicles on a roadway segment averaged over space (usually 

expressed in vehicles per mile or vehicles per mile per lane).

• Vehicle-Miles of Travel (VMT)/Person-Miles of Travel (PMT): Total distance 

traveled by all vehicles or persons on a transportation facility or network during a 

specified time period (expressed in miles).

• Vehicle-Hours of Travel (VHT)/Person-Hours of Travel (PHT): Total travel time 

spent by all vehicles or persons on a transportation facility or network during a 

specified time period (expressed in hours).

• Delay: Additional travel time experienced by travelers at speeds less than the freeflow (posted) speed (expressed in seconds or minutes).

• Queue Length: Length of queued vehicles waiting to be served by the system 

(expressed in distance or number of vehicles).

• Number of Stops: Number of stops experienced by the section and/or corridor (based 

on some minimum travel speed).

• Crashes: Number of crashes on a transportation facility or network.

• Incident Duration: Includes all crashes and vehicle incidents, such as running out of 

gas and mechanical problems. It is calculated from the moment the vehicle or object 

obstructs travel until the incident is cleared (expressed in minutes or hours).

• Travel Time Reliability: Travel time reliability is a quantification of the unexpected 

non-recurring delay associated with excess travel demand, incidents, weather, or 

special events. There are several methods for predicting reliability or variability in 

travel times. Reliability of travel time is a significant benefit to travelers as individuals 

are better able to predict their travel time and budget less time for their trip.

• Emissions: Predicted emissions for each pollutant type on a transportation facility or 

network.

• Fuel Consumption: Fuel consumption rate associated with the use of a transportation 

facility or network.

• Noise: Sound level produced by traffic (expressed in decibels).

• Mode Split: Percentage of travelers using each travel mode (SOV, HOV, transit, 

bicycle, pedestrian, etc.).
28 

• Benefit/Cost: Ratio of annualized, monetized benefits to total costs associated with 

transportation improvement(s). 

Table 7. Relevance of traffic analysis tool categories with respect to performance 

measures. 

Analytical Tools/Methodologies 

Performance 

Measures

Sketch 

Planning

Travel 

Demand 

Models 

Analytical/ 

Deterministic 

Tools (HCMBased)

Traffic 

Optimization Macroscopic 

Simulation 

Mesoscopic 

Simulation 

Microscopic 

Simulation 

LOS ○ ∅ ● ● ∅ ∅ ∅

Speed ● ● ● ● ● ● ●

Travel Time ∅ ∅ ● ● ● ● ●

Volume ● ● ● ● ● ● ●

Travel 

Distance ○ ○ ○ ○ ○ ● ●

Ridership ○ ∅ ○ ○ ○ ∅ ∅

Average 

Vehicle 

Occupancy 

(AVO) 

○ ∅ ○ ○ ○ ○ ○

V/C Ratio ○ ● ● ∅ ∅ ∅ ∅

Density ○ ○ ● ● ● ● ●

VMT/PMT ∅ ● ∅ ∅ ● ● ●

VHT/PHT ∅ ● ∅ ∅ ● ● ●

Delay ∅ ● ● ● ● ● ●

Queue Length ○ ○ ● ● ● ● ●

Number of 

Stops ∅ ○ ○ ○ ○ ∅ ●

Crashes ∅ ○ ○ ○ ○ ∅ ∅

Incident 

Duration ○ ○ ○ ○ ○ ∅ ∅

Travel Time 

Reliability ∅ ○ ○ ○ ○ ○ ○

Emissions ∅ ○ ○ ○ ○ ∅ ∅

Fuel 

Consumption ∅ ○ ○ ○ ∅ ∅ ∅

Noise ∅ ○ ○ ○ ○ ○ ○

Mode Split ○ ● ● ∅ ∅ ∅ ∅

Benefit/Cost ∅ ○ ○ ○ ○ ○ ○

Notes: ● Specific context is generally addressed by the corresponding analytical tool/methodology. 

∅ Some of the analytical tools/methodologies address the specific context and some do not. 

○ The particular analytical tool/methodology does not generally address the specific context. 
29 

Notes and Assumptions: 

• Practitioners should consider the reliability of the tools used before interpreting the 

results. The level of accuracy depends on several factors, including the accuracy and 

level of detail of the input data, analytical assumptions, the calibration of the tool to 

local conditions, and the accuracy of the analytical methodology. 

• Relevance factors for the performance measures listed in table 7 are based on the 

assumption that these measures are generally direct outputs of the tool category. 

• Table 7 does not take into consideration post-processing tools that can produce these 

measures. 

2.2.7 Tool/Cost-Effectiveness 

While the first six criteria help to evaluate the appropriateness of each tool category from a 

technical perspective, the seventh criteria (tool/cost-effectiveness) helps evaluate 

management and operational considerations for selecting the most appropriate tool 

category. Resource requirements, whether they are financial, personnel, or skill-related, 

can be a major consideration in selecting an analytical tool. In addition, using a more 

advanced and data-intensive tool may provide a greater understanding of the alternatives; 

however, accurate and detailed data are still needed to produce representative results. The 

level of effort and the operational characteristics criteria to be considered are summarized 

in table 8 and include the following: 

• Tool Capital Cost: What is the average capital cost to acquire the traffic analysis tool? 

In this category, tools that cost, on average, less than $1,000 are considered to be 

inexpensive, while tools that cost from $1,000 to $5,000 are considered to be mid-range. 

Any tools that cost more than $5,000 are considered to be expensive. Inexpensive tools 

are indicated in table 8 by a solid circle (●), mid-range tools are indicated by a null (or 

neutral) symbol (∅), and expensive tools are indicated by an empty circle (○).

• Level of Effort (Cost/Training): Is the tool methodology type easy to learn? Does it 

require expensive and/or lengthy training sessions? Tools requiring little or no training 

are indicated by a ●, tools requiring a moderate amount of training are indicated by a 

∅, and tools requiring expensive and lengthy training are indicated by an ○.

• Easy to Use: Is the tool generally user-friendly? (For example, Microsoft® Windows®-

based tools have drag-and-drop features, etc.) Easy-to-use and intuitive tools are 

indicated by a ●. Tools requiring a significant amount of additional coding and/or 

data input and analysis are cumbersome and are indicated by an ○. Those in between 

are indicated by a ∅.

• Popular/Well Trusted: Is the tool popular and well regarded by current users? If yes, 

the tool category is indicated by a ●. Tools that are frequently used, but the accuracy 
30 

of the results is highly constrained by data input and methodology constraints are 

indicated by a ∅. Tools that are generally not used in practice at this time are indicated 

by an ○.

• Hardware Requirements: How much computer power is necessary to adequately run 

the analysis? Tools that can be used on older computers and require minimal 

computing power are considered to have low hardware requirements (○), tools that 

require a large amount of computing power (memory and hard-drive space) are 

considered to have high hardware requirements (●), and tools that fall in between are 

considered to have medium hardware requirements (∅).

• Data Requirements: What is the typical amount of input data required to perform the 

analysis? The input data may include traffic volume, speed limit, traffic signal timing, 

intersection/roadway geometric characteristics, the number of general-purpose and 

HOV lanes, ramp metering locations and their timings, detector locations, O-D trip 

tables, etc. Low data requirements are indicated by a ●, moderate data requirements 

are indicated by a ∅, and data-intensive tools are indicated by an ○.

• Computer Run Time: Assuming that adequate computer hardware is available, how 

long does the tool take to perform the analysis? Run times of less than 5 minutes are 

considered minimal (●), run times averaging from 5 minutes to 1 hour are considered 

moderate (∅), and run times lasting more than 1 hour per run are considered long (○).

• Post-Processing Requirements: Does the tool generally produce output in formats 

that require no further post-processing or reformatting? Many tools cannot calculate 

travel time directly; instead, users must invest additional time to generate this output 

from speed and distance information. Tools requiring little or no post-processing or 

reformatting are indicated by a ●, those with moderate amounts are indicated by a ∅, 

and tools requiring a significant amount of post-processing and/or additional coding 

are indicated by an ○.

• Documentation: Does the tool have a detailed and well-written user’s manual? Are 

there articles and reports on past projects evaluated using this type of tool? Excellent 

documentation is indicated by a ●, moderate documentation is indicated by a ∅, and 

little or no documentation is indicated by an ○.

• User Support: Is technical support generally available for this tool? Are there mailing 

lists, chat rooms, or newsgroups dedicated to this tool where users can communicate 

with each other? Tools with a high level of user support are indicated by a ●, 

moderate support is indicated by a ∅, and no support is indicated by an ○.

• Key Parameters Can Be User-Defined: Does the tool allow for customization of the 

key analytical parameters? Is the tool flexible enough to allow for customization (e.g., 

many microsimulation tools are flexible enough to allow users to add custom 
31 

programming codes in addition to the standard package)? Available customization is 

indicated by a ●, limited customization capabilities are indicated by a ∅, and lack of 

customization is indicated by an ○.

• Default Values Are Provided: Does the tool generally provide default values for its 

parameters, rates, or impact values? In some cases, there is not enough time and 

resources to collect the appropriate values for all of the necessary parameters (e.g., 

average walking speed, average reaction time, etc.). Tools with defaults available for 

most parameters are indicated by a ●, tools with some defaults are indicated by a ∅, 

and tools with few or no defaults available are indicated by an ○.

• Integration With Other Software: Does the tool generally have export/import 

features to/from other software (e.g., integration with Microsoft® Excel, Geographic 

Information Systems (GIS) tools, other traffic analysis tools, etc.)? Simple 

export/import features are indicated by a ●, tools with some or limited capabilities are 

indicated by a ∅, and tools with no import/export capabilities are indicated by an ○.

• Animation/Presentation: Does the tool have animation/presentation features (e.g., 

animated, colorful, three-dimensional views, zoom-in/-out capabilities, detailed link 

views as opposed to “stick figures,” ability to produce charts and tables, etc.)? 
32 

Table 8. Relevance of traffic analysis tool categories with respect to tool/cost 

effectiveness. 

Analytical Tools/Methodologies 

Tool/Cost 

Effectiveness

Sketch 

Planning

Travel 

Demand 

Models 

Analytical/ 

Deterministic 

Tools (HCMBased)

Traffic 

Optimization 

Macroscopic 

Simulation 

Mesoscopic 

Simulation 

Microscopic 

Simulation 

Tool Capital 

Cost ● ○ ● ● ∅ ○ ○

Level of Effort ● ○ ● ∅ ∅ ○ ○

Easy to Use ● ○ ● ∅ ∅ ○ ○

Popular/Well 

Trusted ∅ ∅ ● ● ∅ ○ ∅

Hardware 

Requirements ● ∅ ● ● ○ ○ ○

Data 

Requirements ● ○ ● ● ○ ○ ○

Computer Run 

Time ● ∅ ● ● ● ○ ○

PostProcessing 

Requirements 

∅ ○ ∅ ∅ ∅ ● ●

Documentation ∅ ∅ ● ∅ ∅ ∅ ∅

User Support ∅ ● ○ ○ ∅ ∅ ∅

Key 

Parameters 

Can Be UserDefined 

∅ ● ∅ ∅ ● ● ●

Default Values 

Are Provided ● ○ ● ● ● ● ●

Integration 

With Other 

Software (e.g., 

Excel, GIS) 

○ ∅ ∅ ∅ ∅ ∅ ∅

Animation/ 

Presentation ○ ∅ ○ ○ ∅ ● ●

Note: See section 2.2.7 above for descriptions of ●, ∅, and ○, for each subcriteria. 
33 

3.0 Methodology for Selecting a Traffic Analysis 

Tool 

The purpose of this section is to provide guidance to users on how to use the criteria 

presented in section 2.0 to select the appropriate analytical tool category. Worksheets are 

provided in this section to help users work through the process of selecting the 

appropriate tool for addressing the project’s goals and objectives. In addition, an 

automated tool has been developed to implement these steps. This tool can be found on 

the FHWA Traffic Analysis Tools Web site at: 

http://ops.fhwa.dot.gov/Travel/Traffic_Analysis_Tools/traffic_analysis_tools.htm

3.1 Steps for Selecting the Appropriate Tool Category 

This section details the recommended steps for selecting the appropriate tool category for 

the task. Depending on the project, more than one analytical tool may be capable of 

analyzing and producing the desired output. It should also be recognized that one specific 

tool might not be able to address all of the project’s needs. Multiple tools may be desirable 

for conducting a particular study and those tools may or may not be from the same tool 

category. 

Appendix B contains a worksheet that may be used to assist with the tool category 

selection process. Using the steps described below, fill out the cells of table 13: 

1. Define the context of the project and assign context relevance weights (column 2). In 

most cases, the most appropriate tool category or tool depends on the type of project 

and the level of detail required by each project context. Therefore, the first step is to 

carefully think about the context of the project (whether it is planning, design, or 

operations/construction) and the goals, objectives, issues, and needs of the project. 

Next, enter the analytical context relevance weight in column 2, depending on the type 

of study. The values entered in column 2 should range from 0 (not relevant) to 5 (most 

relevant). For example, if the project is a long-range plan, the context relevance weight 

should be 5 for “Planning” and 0 for “Design” and “Operations/Construction.” For 

definitions of the analytical contexts, refer to section 2.1. 

Step 1 – Determine the project 

context (planning, design, or 

operations/construction). Define 

the project’s goals and objectives, 

needs, and issues. Enter the 

context weights into Column 2. 

Values range from 0 (not relevant) 

to 5 (most relevant).

2

0 Analysis Context (0 = not relevant, 5 = most relevant)

Planning 5

Design 0

Operations/Construction 0

Context 

Criteria Relevance

1 Step 1 – Determine the project 

context (planning, design, or 

operations/construction). Define 

the project’s goals and objectives, 

needs, and issues. Enter the 

context weights into Column 2. 

Values range from 0 (not relevant) 

to 5 (most relevant).

2

0 Analysis Context (0 = not relevant, 5 = most relevant)

Planning 5

Design 0

Operations/Construction 0

Context 

Criteria Relevance

1

Figure 3. Selecting the appropriate tool category, step 1. 
34 

2. Assign subcriteria relevance weights (column 2). In this step, the user assigns 

relevance weights to subcriteria within each type of criterion. Subcriteria that are 

highly desirable as part of the project should be given higher weights. The relevance 

values that should be entered in column 2 range from 0 (not relevant) to 5 (most 

relevant). Enter the weights for each subcriterion as they relate to each other and the 

needs of the project. 

Here are some examples for assigning relevance weights: 

a. Geographic Scope: If the study area consists of a 8-km-long (5-mi-long) freeway 

segment with two parallel arterials on each side, plus all connecting streets, a 

weight of 5 should be given to “Corridor/Small Network” and weights of 0 should 

be given to all other subcriteria. 

b. Facility Type: If the facility types in the study area are primarily a freeway, its 

parallel arterials, and the connecting ramps and streets, but there are also auxiliary 

lanes and HOV lanes and the impact on those is not as important, a weight of 5 

should be given to “Freeway,” “Arterial,” and “Ramps,” while a weight of 3 might 

be given to “HOV Lane” and “Auxiliary Lane.” Weights of 0 would be given to the 

other facility-type subcriteria. 

c. Travel Mode: The project involves ramp metering and data related to SOV, HOV, 

and truck modes are available. However, the project focus is on the SOV mode. A 

weight of 5 would be given to “SOV,” a 2 would be given to “HOV,” a 1 would be 

given to “Truck,” and weights of 0 would be given to the other modes. 

d. Management Strategy/Application: The project involves ramp metering only. A 

weight of 5 would be given to “Freeway Management” and the other subcriteria 

would be given weights of 0. 

e. Traveler Response: It is anticipated that there will be some route diversion as a 

result of ramp metering, so it should be given a high weight. There may be some 

mode shift or departure time choice; however, they are not nearly as relevant for 

the analysis. “Route Diversion” should be given a weight of 5, “Mode Shift” and 

“Departure Time Choice” should each be given a 2, and the other traveler 

responses should be given weights of 0. 

f. Performance Measures: The stakeholders for this project are interested in travel 

speed, volume, and the travel time changes anticipated from the ramp metering 

project. A benefit/cost comparison is also desired for determining whether the 

project is worthwhile to implement. The measures to be considered for the 

benefit/cost comparison include mobility (delay), travel time reliability, safety 

(crashes), emissions, and fuel consumption. Weights of 5 would be given to 

“Speed,” “Volume,” “Travel Time,” “Delay,” “Travel Time Reliability,” “Crashes,”

“Emissions,” “Fuel Consumption,” and “Benefit/Cost.” Many of these measures 

are based on VMT and VHT/PHT. Therefore, if some of the desired measures are 

not available, “VMT/PHT” and “VHT/PHT” measures would each be given a 

weight of 4. Because this is a ramp metering project, it would also be desirable to 
35 

know the queue length, but it is not required, so a weight of 2 would be given to 

“Queue Length.” The other performance measure subcriteria would be given 

weights of 0. 

g. Tool/Cost-Effectiveness: There is an adequate budget for addressing all aspects of 

the project, including the costs of acquiring the tool, staff training, hardware 

requirements, and analytical runs. The high priorities for the project in this area 

involve confidence in the results, the ability of the tool to be adjusted to local 

conditions, and that the results can be easily produced and presented to the 

stakeholders. In this case, weights of 5 would be given to “Popular/Well Trusted,”

“Post-Processing Requirements,” “Key Parameters Can Be User-Defined,” and 

“Animation/Presentation Features.” Weights of 3 would be given to “Easy to 

Use,” “Data Requirements,” and “Default Values Are Provided.” Weights of 2 

would be given to “Low Tool Costs,” “Level of Effort/Training,”

“Documentation,” and “User Support.” In addition, a weight of 1 would be given 

to “Hardware Requirements.” “Integration With Other Software” is not a concern 

and would be given a weight of 0. 

2

1 Geographic Scope (0 = not relevant, 5 = most relevant)

Isolated Location 0

Segment 5

Corridor/Small Network 0

Region 0

1

Criteria

SubCriteria 

Relevance

Step 2 – Enter sub-criteria 

relevance for each criterion into 

Column 2. Values range between 

0 (not relevant) and 5 (most 

relevant).

Figure 4. Selecting the appropriate tool category, step 2. 

3. Assign tool relevance values (column 3). Most of these values are provided as part of 

the worksheet (appendix B) based on the assessment presented in tables 1 through 8. 

Only the geographic scope criterion requires user input of tool relevance values in 

column 3. Using the appropriate analytical context and the tool relevance factors 

presented in table 2, enter the tool relevance values for “Geographic Scope” in 

column 3: 

a. For every solid circle (●), assign a value of 10. 

b. For every null symbol (∅), assign a value of 5. 

c. For every empty circle (○), assign a value of 0. 

d. For every not applicable (N/A), assign a value of -99. 
36 

2

Tool Category Relevance*

Sketch 

Plan TDM

Analytical

(HCM)

Traffic 

Opt

Macro 

Sim

Meso 

Sim

Micro 

Sim

1 Geographic Scope (0 = not relevant, 5 = most relevant)

Isolated Location 0 0 0 10 5 0 0 0

Segment 5 10 0 10 0 5 5 5

Corridor/Small Network 0 5 10 0 0 5 5 5

Region 0 5 10 -99 -99 -99 -99 -99

SubCriteria 

Criteria Relevance

1 3

Step 3 – Fro m table 2, enter 

relevance factors for Geographic 

Scope criteria into Column 3 

using the appropriate analytical 

context. Use the following values: 

(●) = 10 points; (∅) = 5 points, 

(○) = 0 points, (N/A) = -99 points.

Figure 5. Selecting the appropriate tool category, step 3. 

4. Multiply columns 2 and 3 (column 4). For the analytical context and each subcriterion, 

multiply the entries in column 2 by the entries in each subcolumn in column 3, and 

enter the products into the appropriate cells in column 4. 

2

Too

Sketch 

Plan TDM

An

(H

0 0 0

5 10 0

0 5 10

0 5 10

SubCriteria 

Relevance

Column 2 x Column 3

icro 

im

Sketch 

Plan TDM

Analytical

(HCM)

Traffic 

Opt

Macro 

Sim

Meso 

Sim

Micro 

Sim

0x0 = 0 0 0 0000

5x10 = 50 0 50 0 25 25 25

0x5 = 0 0 0 0000

0x5 = 0 0 0 0000

4

Step 4 – M ultiply the value in 

Column 2 by each tool category 

value in Col umn 3, and enter the 

values into Col umn 4.

Figure 6. Selecting the appropriate tool category, step 4. 

5. Sum the values of column 4. For the analytical context and each criterion, add up the 

values for each tool category in column 4 and enter the result into the “Subtotal” row 

in column 4. 

6. Count the number of subcriteria relevance weights greater than 0. For the analytical 

context and each criterion, count the number of relevance weights in column 2 that are 

greater than 0 and enter the value into the “Relevance Weights Above 0” cell. 
37 

7. Calculate the criteria ratings. Divide the values in the “Subtotal” rows by the number 

of “Relevance Weights Above 0” cell and enter the amount into the “Weighted 

Subtotal” row in order to normalize the scores. Repeat this process for each criterion. 

Column 2 x Column 3

Sketch 

Plan TDM

Analytical

(HCM)

Traffic 

Opt

Macro 

Sim

Meso 

Sim

Micro 

Sim

0 0 0 0000

50 0 50 0 25 25 25

0 0 0 0000

0 0 0 0000

Subtotal 0+50+0+0=50 0 50 0 25 25 25

Relevance Weights Above 0 1

WEIGHTED SUBTOTAL 50/1 = 50 0 50 0 25 25 25

4

Step 5 – S um values for each tool 

category and criteria into the 

“Subtotal” row. Step 6 – Count the number of 

relevance weights (Column 2) that 

are greater than zero.

Step 7 – Divide the values i n the 

“Subtotal” rows by the

“Relevance Weights Above 0” 

cell, enter i nto the “Weighted 

Subtotal” row.

Figure 7. Selecting the appropriate tool category, steps 5–7. 

8. Group weighted subtotals (column 7). Copy the weighted subtotals for the analytical 

context and seven criteria from their respective rows to column 7 at the bottom of the 

worksheet. 

Weighted Subtotals

Sketch 

Plan TDM

Analytical

(HCM)

Traffic 

Opt

Macro 

Sim

Meso 

Sim

Micro 

Sim

50 0 50 0 25 25 25

7

WEIGHTED SUBTOTAL

WEIGHTED SUBTOTAL

WEIGHTED SUBTOTAL

WEIGHTED SUBTOTAL

WEIGHTED SUBTOTAL

WEIGHTED SUBTOTAL

WEIGHTED SUBTOTAL

Step 8 – Copy all weighted 

subtotals into Column 7.

50 0 50 0 25 25 25

Figure 8. Selecting the appropriate tool category, step 8. 

9. Review and reassess weighted subtotals. Review the values in column 7 for each 

criterion and tool category, with particular focus on the negative values. For each 

negative criteria value, identify the source of the negative value (column 4) and verify 

the subcriteria relevance in column 2. Make adjustments as necessary to the subcriteria 

relevance values based on the project’s goals and objectives, priorities, needs, and 

issues. 
38 

10. Assign criteria relevance weights (column 6). The prior weighting scheme (column 2) 

was applied to the subcriteria within each major criteria category. This step involves 

weighting the major criteria categories against each other. This should be based on the 

project’s goals and objectives, priorities, needs, and issues. For the analytical context 

and each of the seven criteria, assign the appropriate weights, ranging from 0 (not 

relevant) to 5 (most relevant). If a user wants to weight each of the criteria and 

analytical context equally, a weight of 5 can be applied to all. A different weighting 

scheme may be used if greater differentiations between criteria are necessary. The user 

should carefully consider the project’s priorities, needs, and constraints when selecting 

the criteria weights. 

6

Weighted Subtotals

Sketch 

Plan TDM

Analytical

(HCM)

Traffic 

Opt

Macro 

Sim

Meso 

Sim

Micro 

Sim

5 50 50 25 0 25 25 0

3 50 0 50 0 25 25 25

3 15 33 20 16 23 21 33

3 16 25 13 13 13 21 21

4 19 13 17 20 27 27 30

1 13 23 -2664 0 22 22 22

5 13 16 16 16 18 22 23

5 20 11 22 19 19 10 11

7

Criteria 

Relevance

Step 9 – Revi ew negative values 

in Col umn 7 and reassess

relevance values for s ubcriteria.

Step 10 – Assign relevance 

weights for the a nalytical context 

and seven criteria, ranging from 0 

(not relevant) to 5 (most relevant).

Figure 9. Selecting the appropriate tool category, steps 9 and 10. 

11. Multiply columns 6 and 7 (column 8). For each context/criterion, multiply the value 

in column 6 by each of the subcolumns in column 7 and enter the result into the 

appropriate cells in column 8. 

Column 6 x Column 7

Micro 

Sim

Sketch 

Plan TDM

Analytical

(HCM)

Traffic 

Opt

Macro 

Sim

Meso 

Sim

Micro 

Sim

250 250 125 0 125 125 0

150 0 150 0 75 75 75

45 100 60 48 70 63 98

49 75 39 38 38 62 64

76 52 68 80 108 108 120

13 23 -124 0 22 22 22

65 82 78 82 91 110 114

100 57 111 93 93 50 57

6 8

Weig

Sketch 

Plan TDM

Analytic

(HCM)

5 50 50 25

3 50 0 50

3 15 33 20

3 16 25 13

4 19 13 17

1 13 23 -2664

5 13 16 16

5 20 11 22

 7

Criteria 

Relevance

Step 11 – M ultiply the value in 

Column 6 by Col umn 7 for each 

tool category, and enter the values 

in Col umn 8.

Figure 10. Selecting the appropriate tool category, step 11. 
39 

12. Determine the best tool categories. Sum the products of the multiplication for each 

tool category in column 8 and enter the values in the “Weighted Totals” row at the 

bottom of the worksheet. The tool categories with the highest totals based on this 

mathematical process are the most appropriate tools for the task. 

WEIGHTED TOTALS 748 639 507 340 621 614 549

Most Appropriate Tool Categories: 1. Sketch Plan

2. TDM

Step 13 – Select the top two tool 

categories. Given the users’ input 

into this worksheet, these are the 

most appropriate tool types for 

consideration.

Step 12 – Sum values of each subcolumn in Column 8 and enter in 

the “Weighted Totals” cells.

WEIGHTED TOTALS 748 639 507 340 621 614 549

Most Appropriate Tool Categories: 1. Sketch Plan

2. TDM

Step 13 – Select the top two tool 

categories. Given the users’ input 

into this worksheet, these are the 

most appropriate tool types for 

consideration.

Step 12 – Sum values of each subcolumn in Column 8 and enter in 

the “Weighted Totals” cells.

Figure 11. Selecting the appropriate tool category, steps 12 and 13. 

13. Select the top two tool categories for further consideration. It is recommended that 

the user further explore the available tools for the top two most appropriate tool 

categories, particularly if the total scores are close in value. Tool categories with final 

scores of less than 0 should not be considered. It should be recognized that one specific 

tool may not be able to address all of the project’s needs. Multiple tools may be 

necessary for conducting a particular study and those tools may or may not be from 

the same tool category. Each of the subcriteria with high relevance factors and low 

scores in column 4 will need to be assessed to determine if that particular category of 

tool weakness can be overcome through other means (e.g., there is a need for 

microsimulation; however, the computer resources are insufficient to accommodate 

the analytical needs). 

3.2 Examples for Using the Tool Category Selection Worksheets 

The following are three examples for using the tool category selection worksheets. 

3.2.1 Example 1: Ramp Metering Corridor Study 

A State department of transportation (DOT) needs to assess the future impact of ramp 

metering. Without the convenience of a field experiment, the DOT must estimate the 

volume, speed, and travel time impacts of ramp metering on a freeway corridor, the 

ramps, and the parallel arterials. The study corridor is approximately 24 km long (15 mi 

long), running north-south, with one parallel arterial on each side of the freeway less than 

0.8 km (0.5 mi) away. The impact of passenger cars is the focus of the study for both the 

SOV and HOV travel modes. Ramp metering strategies to be considered include fixed-time 

and adaptive ramp metering, with the following parameter permutations: (1) with and 
40 

without queue control, (2) with and without HOV bypass lanes, and (3) restrictive and less 

restrictive metering rates. Since ramp metering may cause diversion of traffic to the 

parallel arterials, the ability of the traffic analysis tool to adapt to dynamic traffic 

conditions is crucial to the project. In addition, the corridor is currently undergoing major 

infrastructure changes. HOV lanes are being constructed at the southern portion of the 

corridor and a few interchanges are being realigned. 

The project manager has stressed that deployment of ramp meters at this corridor will not 

occur without the support of the local city partners. The State DOT and the local traffic 

jurisdictions have developed excellent working relationships over the years; however, the 

cities are reluctant to support the ramp metering project because they fear that the traffic 

queues at the on-ramps and route diversion would reduce the performance of their 

arterials. Therefore, an objective of the evaluation is to select the ramp metering strategy 

that can be accepted by all stakeholders. The ability of the tool to produce animated 

results is preferred, but is not crucial; however, the tool must be well accepted and widely 

used. 

The project team consists of experienced analysts and engineers who are equipped with 

high-performance computers. The State has obtained the arterial/interchange signal 

timings from the local cities in preparation for this project. Old aerial photographs 

showing the corridor before construction work and design drawings from the 

construction sites are available. 

Project Assessment 

Based on the information provided, the following can be used to summarize the project: 

• Project Context: Design 

• Project Goal: Evaluation and selection of optimal ramp metering strategy 

• Project Objectives and Background: 

− Analyze fixed-time and adaptive ramp metering under various operating 

parameters. 

− Corridor study area is 24 km (15 mi), with two parallel arterials. 

− Focus on roadways and passenger vehicles. 

− Aerial photographs, design drawings, and existing signal timings are available. 

− Volume, speed, and travel time are the main output. 

− Traveler response, particularly route diversion, is crucial. 

− Good presentation/animation capabilities are preferred. 

− Tool should be versatile yet sensitive enough to model small variations in 

parameters. 

− Tool should be popular/well-trusted by the industry. 
41 

Tool Category Selection Worksheet for Example 1 

Table 9, which can be found at the end of this section, shows a completed worksheet for 

this example. Based on the analysis performed using the worksheet, this project can be 

best evaluated using three different tool categories (there are only two negative final 

scores, while three of seven scores are close). The most appropriate tool category is the 

microscopic simulation tools, followed by macroscopic and mesoscopic simulation tools. 

3.2.2 Example 2: ITS Long-Range Plan 

A metropolitan planning organization (MPO) plans to assess the future costs and benefits 

of ITS investments in its jurisdiction. The study area is the entire metropolitan area, which 

is about 1300 km2 (500 mi2); however, the MPO is only concerned about travel on 

freeways, highways, and major arterials. 

A skeleton network with nodes, links, and trip table data is available from the local travel 

demand model. Aerial photographs are available. However, they are a few years old, but 

the major transportation infrastructure has not changed and no changes are expected in 

the future. Alternative modes of transportation (e.g., transit, motorcycles, trucks, and light 

rail) are important; however, the focus of the study is the impact on passenger cars. The 

ITS strategies to be considered include ramp metering, incident management, arterial 

management, and advanced traveler information systems (ATIS). The MPO has 

developed O-D trip tables for both existing and future scenarios. At least five different 

alternatives will need to be analyzed. As for the output, the MPO Board is mostly 

concerned with the benefit/cost ratios related to each of the ITS alternatives. If necessary, 

a second tool may be used to convert the output into monetary terms. 

The project manager is an experienced modeler who has worked with demand forecasting 

tools in the past, but most of her team members are relatively new to the field. However, 

the team members are computer-savvy and seem to absorb new ideas extremely well, 

given the availability of learning resources. This project has a healthy budget; however, 

time is of the essence, since the board needs to submit a report to the finance department 

by the end of the fiscal year, which is only 6 months away. 

Project Assessment 

Based on the information provided, the following can be used to summarize the project: 

• Project Context: Planning 

• Project Goal: Benefit/cost evaluation of ITS investments 

• Project Objectives and Background: 

− Analyze the impacts related to the deployment of ITS strategies: ramp metering, 

incident management, arterial management, and ATIS. 
42 

− Large study area is 1300 km2 (500 mi2). 

− Focus on roadways and passenger vehicles. 

− O-D matrices and skeleton network are available. 

− Benefit/cost ratios are the main output. 

− Tool should be easy to use and have good documentation. 

− Deadline is in 6 months. 

Tool Category Selection Worksheet for Example 2 

The completed worksheet for this example is shown in table 10, located at the end of this 

section. Criteria and subcriteria weights that address the project’s goals and objectives 

were given higher values. Based on the analysis performed for this example, the most 

appropriate tool category is the travel demand model. The sketch-planning tool category 

should also be considered since the scores are reasonably close. The user should further 

explore the specific tools that fall within these two categories to determine which tool(s) 

best serves the needs of the project. Other tool categories in this example have scores of 

less than 0 and should not be considered for analysis. 

3.2.3 Example 3: Arterial Signal Coordination and Preemption 

A city traffic department is conducting a major traffic signal timing improvement on one 

of its most critical arterials, which is about 16 km long (10 mi long). This study is being 

conducted in conjunction with a large redevelopment project that hopes to revive the 

economy in this section of town. Multiple interest groups, neighborhood groups, and city 

jurisdictions are involved with the project. 

The arterial is vital to the city and currently serves all travel modes; however, the city is 

most interested in improving travel on the arterial for passenger vehicles, buses, and light 

rail, primarily through the use of signal coordination. No major alignment changes are 

being considered; however, traffic signal preemption for buses and light rail is a major 

component that will be introduced for the first time in this city. Many citizens are not 

familiar with the technology and are quite skeptical about its effectiveness. In fact, many 

perceive that preemption would result in worse traffic conditions. Therefore, an 

evaluation process and an outreach program highlighting the benefits of the project to the 

community are needed. The results of the analysis must be presented to the public and the 

stakeholders in the most effective manner. 

The best and most experienced staff members have been assigned to this project. They are 

experts in a few modeling and simulation tools, but are looking for the best tool available 

with a short and flat learning curve. Otherwise, they are more inclined to use the tools that 

they are already familiar with. The computers available for the project are older Intel®

Pentium® II machines. The city maintains good records for traffic volumes and roadway 

geometrics for the entire arterial and parallel roadways, and is interested in evaluating as 

many performance measures as can be provided by the tool. However, the following three 

performance measures are crucial: LOS, speed, and intersection delays, both at the 
43 

aggregate level and for each travel mode. Traveler response needs to be considered since 

route shifting between the arterial and parallel facilities is of interest to the stakeholders. 

Project Assessment 

Based on the information provided, the following can be used to summarize the project: 

• Project Context: Operations 

• Project Goal: Signal optimization and successful introduction of signal preemption 

• Project Objectives and Background: 

− Traffic signal optimization 

− Long arterial study area with parallel roadways 16 km (10 mi)) 

− Emphasis on cars, buses, and light rail 

− Volumes, geometric data available 

− Traveler response, particularly route diversion, is necessary 

− Good presentation/animation capabilities 

− Avoidance of high-end, computer-intensive analytical tools 

− Dependable, trusted tool with flat learning curve 

− Output in terms of LOS, speed, travel time, and intersection delay by mode 

Tool Category Selection Worksheet for Example 3 

Table 11, at the end of this section, shows a completed worksheet for example 3. Based on 

the analysis performed using the worksheet, it seems that this project can be adequately 

evaluated using four different tool categories, including microscopic simulation tools, 

followed by macroscopic and mesoscopic simulation tools and traffic optimization tools. 

However, the city will probably need to improve their computing capabilities in order to 

conduct the analysis using simulation. 

3.3 Guidance for Selecting the Specific Tool 

Once the most appropriate tool category has been identified, the user should narrow 

down the candidate tools within the category. While the features of the specific traffic 

analysis tools are beyond the scope of this document, the worksheet presented in appendix C 

may assist users in comparing different tools during their research effort or vendor 

interviews. This approach is intended to help users identify what is important to consider 

in their selection of the specific tool(s). Instructions on how to use the worksheet are 

provided below: 

1. Enter the name of the tool being reviewed. If reviewing different versions/releases of 

the same tool, do not forget to include the version number or release date. 
44 

Step 1 – Enter name, version, and 

contact information for tool being 

reviewed.

Tool Name: Acme Traffic Version/Release: 2.0 .

Vendor Name/Contact Information: AcmeSoft, Inc. / Mr. John Smith .

Figure 12. Selecting the specific tool, step 1. 

2. Assign subcriteria relevance weights (column 2). The subcriteria listed in this 

worksheet are expanded versions of the ones listed in appendix B. An “other” field has 

been added to each criterion for users to consider other subcriteria that may not be 

included in this list. Subcriteria that should be highly considered in the analysis 

should be given higher weights. The values should range from 0 (not relevant) to 5 

(most relevant). The relevance factors entered in the subcriteria relevance cells should 

be the relevance within that particular criteria (e.g., is the SOV travel mode more 

important than the HOV mode?). The subcriteria relevance weights in column 2 

should be identical for every tool considered. 

Step 2 – E nter s ubcriteria

relevance weights in Column 2. 

Values range between 0 (not 

relevant) and 5 (most rel evant).

2

Subcriteria Relevance

1 Geographic Scope (0 = not important, 5 = most important)

Isolated Location 0

Segment 1

Corridor 3

Region 5

Other: ________________

1

Criteria

Figure 13. Selecting the specific tool, step 2. 

3. Assign tool relevance values (column 3). The relevance factors presented in tables 1 

through 8 are generalized views of available tools for each tool category. Therefore, 

users must perform additional research to find the most appropriate tool within the 

tool category. Based on literature reviews, product specifications, or vendor 

interviews, the user should rate the relevance of the tools under review against the 

criteria presented in this worksheet. Appendix D identifies some readily available 

literature that contains detailed reviews of some of the more commonly used traffic 

analysis tools. The values entered in column 3 should range from 0 (not featured by 

the tool) to 5 (strongly featured by the tool). If necessary, use column 5 for additional 

notes and/or comments. 
45 

23 4 5

Subcriteria RelevanceTool Relevance*Col 2 x Col 3

Comments

1 Geographic Scope (0 = not important, 5 = most important)

Isolated Location 0 0 0x0 = 0 Poor for intersections

Segment 1 1 1x1 = 1

Corridor 3 5 3x5 = 15

Region 5 4 5x4 = 20

Other: ________

1

Criteria

Step 3 – Based on tool r esearch or 

vendor interviews, rate the tool’s 

capabilities in Col umn 3. Values 

range from 0 (not featured) to 5 

(strongly featured). Use Col umn 

5 for comments.

Step 4 – M ultiply Columns 2 and 

3 for each s ubcriteria, and ins ert 

results in Column 4.

Figure 14. Selecting the specific tool, steps 3 and 4. 

4. Multiply columns 2 and 3 (column 4). For each subcriterion, multiply the values in 

columns 2 and 3 and enter into column 4. 

5. Sum the values of column 4. Add up the values in column 4 for each criteria category, 

and enter the total into the “Subtotal” row for each criterion. 

6. Count the number of subcriteria relevance weights above 0. For each criterion, count 

the number of subcriteria relevance weights in column 2 that are larger than 0, and 

enter the number into the “Relevance Weights Above 0” cell. 

7. Calculate the adjusted ratings. Divide the value in the “Subtotal” row with the 

“Relevance Weights Above 0” value and enter into the “Weighted Subtotal” row. 

Repeat this process for each criterion. 

0

1

15

20

Subtotal 0+1+15+20=36

Criteria Weights Above 0 3

WEIGHTED SUBTOTAL 36/3=12

Step 5 – For each criterion, sum 

the values of Column 4 into the 

“Subtotal” row.

Step 6 – Count the number of 

subcriteria relevance weights 

(Column 2) that are greater than 

zero for each criterion.

Step 7 – Divide the values i n the 

“Subtotal” rows by the

“Relevance Weights Above 0” 

cell, enter i n the “Weighted 

Subtotal” row.

Figure 15. Selecting the specific tool, steps 5–7. 
46 

8. Group weighted subtotals (column 8). For each criterion, copy the weighted subtotals 

from the respective rows to column 8 at the bottom of the worksheet. 

9. Assign criteria relevance weights (column 7). In steps 1 through 8, the weighting 

scheme was applied to the subcriteria within each major criteria category. This step 

involves weighting the major criteria categories against each other. This should be 

based on the project’s goals and objectives, priorities, needs, and constraints. For each 

of the seven criteria, assign the appropriate weights, ranging from 0 (not relevant) to 5 

(most relevant). The criteria relevance weights in column 7 should be identical for 

every tool considered. 

7 8

Criteria WeightWeighted Subtotals

1 Geographic Scope 3 12

2 Facility Type 4

3 Travel Mode 2

4 Management Strategy/Application 2

5 Traveler Response 5

6 Performance Measures 2

7 Tool/Cost Effectiveness 5

6

Criteria 

(0 = not relevant, 5 = most relevant)

Step 8 – Copy the criteria-weighted

subtotals into Column 8.

Step 9 – Assign rel evance weights 

for each criteria, ranging from 0 

(not relevant) to 5 (most relevant).

WEIGHTED SUBTOTAL

WEIGHTED SUBTOTAL

WEIGHTED SUBTOTAL

WEIGHTED SUBTOTAL 12

Figure 16. Selecting the specific tool, steps 8 and 9. 

10. Multiply columns 7 and 8 (column 9). Multiply columns 7 and 8 for each criterion and 

enter the products into the appropriate cells in column 9. 

11. Determine the tool’s total score. Sum column 9 and enter the product in the “Total 

Score” cell. 

12. Repeat this process for all tools considered. Use one worksheet for each tool under 

consideration. Keep in mind that the users’ criteria and subcriteria relevance weights 

should remain constant for all tools. Users are encouraged to review as many tools as 

possible from each tool category selected (section 3.1). Please refer to appendix E for a 

list of available tools for each category and their Web site links to obtain further 

information. 
47 

13. Select the best tool. Compare the total scores of all tools under review. The one with 

the highest score is the probably the best tool for the project under consideration. 

Col 9

36

125

0

226

96

360

125

TOTAL SCORE 968

Steps 12 and 13 – Use one 

worksheet for each tool being 

reviewed. Select the most suitable 

tool with the highest score.

Step 10 – M ultiply Columns 7 and 

8. Enter r esults in Col umn 9.

Step 11 – S um the values in 

Column 9. This is the reviewed 

tool’s total score.

Figure 17. Selecting the specific tool, steps 10–13. 

Again, the user should review the subcriteria with high weights, but low scores, to 

assess whether they can be addressed through other means. If the best tool selected by 

this process does not satisfy the users’ needs (e.g., the project’s goal is ramp metering 

analysis; however, the best tool’s ramp metering feature is only a “3”), additional tools 

should be researched. If necessary, review the project’s goals and objectives, needs, 

and constraints and repeat the entire process if no tool within a particular category 

addresses the project’s needs. In most cases, the tool selection process would be 

iterative. Hopefully, careful consideration of the project’s goals and objectives in this 

process will lead the user to the most appropriate tool for the project. 
Table 9. Example 1 worksheet (refer to sections 2.1 and 2.2 for criteria definitions). 

48 
Table 9. Example 1 worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued). 

49 
Table 9. Example 1 worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued).

50 
Table 9. Example 1 worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued). 

51 
Table 10. Example 2 worksheet (refer to sections 2.1 and 2.2 for criteria definitions). 

52 
Table 10. Example 2 worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued). 

53 
Table 10. Example 2 worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued). 

54 
Table 10. Example 2 worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued). 

55 
Table 11. Example 3 worksheet (refer to sections 2.1 and 2.2 for criteria definitions). 

56 
Table 11. Example 3 worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued). 

57 
Table 11. Example 3 worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued). 

58 
Table 11. Example 3 worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued). 

59 

61 

4.0 Available Traffic Analysis Tools 

Before selecting a particular tool, users are strongly encouraged to assess the strengths 

and weaknesses of the specific analytical tools since this document only presents a 

generalized view of each tool category. Appendix E provides a list of available traffic 

analysis tools by tool category and Web site links for further information (available as of 

August 2003). An updated version of this list can be found at the FHWA Office of 

Operations Web site at: 

http://ops.fhwa.dot.gov/Travel/Traffic_Analysis_Tools/traffic_analysis_tools.htm

The worksheet in appendix C may be used to assess the capabilities of each tool in 

comparison to the project’s goals and objectives. 

63 

5.0 Challenges and Limitations in the Use of 

Traffic Analysis Tools 

As long as they are used correctly, traffic analysis tools are useful and effective in helping 

transportation professionals best address their transportation needs. Each tool and tool 

category is designed to perform different traffic analysis functions, and there is no one 

analytical tool that can do everything or solve every problem. This section addresses some 

of the challenges and limitations of available traffic analysis tools that should be 

considered when selecting a tool: 

• Availability of quality data. If good data are not available, the user should consider a 

less data-intensive tool category, such as a sketch-planning tool rather than 

microsimulation. However, the results of the simpler tool categories are usually more 

generalized, so the user should carefully balance the needs of a more detailed analysis 

with the amount of data required. 

• Limited empirical data. Data collection can often be the most costly component of a 

study. The best approach is to look at the ultimate goals and objectives of the task and 

focus data collection on the data that are crucial to the study. 

• Limited funding. Limited funding for conducting the study, purchasing tools, 

running analytical scenarios, and training users is often a consideration in 

transportation studies. Traffic analysis tools can require a significant capital 

investment. Software licensing and training fees can make up a large portion of the 

budget. Also, the analysis of more scenarios costs money. When faced with funding 

limitations, focus on the project’s goals and objectives, and try to identify the point of 

diminishing returns for the investment. 

• Training limitations. Traffic simulation tools usually have steep learning curves and, 

as a result, some transportation professionals do not receive adequate modeling and 

simulation training. 

• Limited resources. Limitations in staffing, capabilities, and funding for building the 

network and conducting the analysis should be considered. The implementation of 

most traffic analysis tools is a resource-intensive process, especially in the model 

coding and calibration (front-end) phases for simulation analyses. Careful scheduling 

and pre-agreed upon acceptance criteria are necessary to keep the project focused and 

on target. 

• Data input and the diversity and inconsistency of data. Each tool uses unique 

analytical methodologies, so the data requirements for analysis can vary greatly from 

tool to tool and by tool category. In many cases, data from previous projects contribute 

very little to a new analytical effort. Adequate resources must be budgeted for data 

collection. 
64 

• Lack of understanding of the limitations of analytical tools. Often, limitations and 

“bugs” are not discovered until the project is underway. It is important to learn from 

experiences with past projects or to communicate with fellow users of a particular tool 

or tool category in order to assess the tool’s capabilities and limitations. By researching 

the experiences of others, users can gain a better understanding of what they may 

encounter as the project progresses. 

• Tools may not be designed to evaluate all types of impacts produced by 

transportation strategies/applications. The output measures produced by each tool 

vary, so the process of matching the project’s desired performance measures with the 

tool’s output is important. In addition, there are very few tools that directly analyze 

ITS strategies and the impacts associated with them (e.g., reduction in incident 

duration, agency cost savings, etc.). 

• Lack of features. Some analytical tools are not designed to evaluate the specific 

strategies that users would like to implement. This is more prevalent in modeling ITS 

strategies or other advanced traffic operations strategies. Often, “tricking” the tool into 

mimicking a certain strategy is a short-term solution; however, there should be 

flexibility so that advanced users may customize the tools. 

• Desire to run real-time solutions. Many tools require a significant amount of time for 

setup, modeling, and analysis. It is hoped that future tools will be able to be linked to 

traffic management centers (TMCs) and detectors so that the analysis can be 

implemented directly and in real time. This would allow transportation professionals 

to respond to recurring and nonrecurring congestion using real-time solutions. 

• Tendency to use simpler analytical tools and those available in house, although 

they might not be the best tools for the job. Because of lack of resources, past 

experience, or lack of familiarity with other available tools, many agencies prefer to 

use a tool currently in their possession, even if it is not the most appropriate tool for 

the project. 

• Biases against models and traffic analysis tools. These biases are not only because of 

the challenges listed above, but also because models are not always reliable and are 

often considered “black boxes.” Some transportation professionals prefer to use “backof-the-envelope” calculations, charts, or nomographs to estimate the results. This may 

be adequate for simpler tasks; however, more complex projects require more advanced 

tools. 

• Long computer run times. Depending on the computer hardware and the scope of the 

study (e.g., area size, data requirements, duration, analytical time periods, etc.), an 

analytical run may range from a few seconds to several hours. The most effective 

approaches to addressing this issue involve using the most robust computer 

equipment available and/or carefully limiting the scope of the study to conform to the 

analytical needs. 
65 

Appendix A: Limitations of HCM 
66 

Table 12. Limitations of the HCM methodologies. 

Section Limitations 

“Urban Street 

Methodology” 

(chapter 15, 

HCM 2000)

This methodology does not directly account for the following conditions that can occur 

between intersections: 

• Presence or lack of onstreet parking 

• Driveway density or access control 

• Lane additions leading up to or lane drops leading away from intersections 

• Impact of grades between intersections 

• Any capacity constraints between intersections (such as a narrow bridge) 

• Midblock medians and two-way left-turn lanes 

• Turning movements that exceed 20 percent of the total volume on the street 

• Queues at one intersection backing up to and interfering with the operation of an 

upstream intersection 

• Cross-street congestion blocking through traffic 

Because any one of these conditions might have a significant impact on the speed of 

through traffic, the analyst should modify the methodology to incorporate the effects as 

well as possible. 

“Signalized 

Intersection 

Methodology”

(chapter 16, 

HCM 2000) 

This methodology does not take into account the potential impact of downstream 

congestion on intersection operation, nor does it detect and adjust for the impact of 

turn-pocket overflows on through traffic and intersection operation. 

“Unsignalized 

Intersection 

Methodology”

(chapter 17, 

HCM 2000) 

HCM 2000 does not include a detailed method for estimating delay for yield signcontrolled intersections. All of the methods are for steady-state conditions (i.e., the 

demand and capacity conditions are constant during the analysis period). The methods 

are not designed to evaluate how fast or how often the facility transitions from one 

demand/capacity state to another. Analysts interested in that kind of information 

should consider applying simulation models. 

“Pedestrian 

Methodology” 

(chapter 18, 

HCM 2000) 

HCM 2000 treats each of these facilities from the point of view of the pedestrian. 

Procedures for assessing the impact of pedestrians on vehicular capacity and LOS are 

incorporated into other chapters. The material in HCM 2000 is the result of research 

sponsored by FHWA. 

The pedestrian methodology for midblock sidewalk analysis cannot determine the 

effects of high volumes of pedestrians entering from the doorways of office buildings 

or subway stations. It also cannot determine the effects of high volumes of motor 

vehicles entering or leaving a parking garage and crossing the sidewalk area. 

Moreover, the methodology does not consider grades; it is adequate for grades from -3 

to +3 percent; however, the effects of more extreme grades have not been well 

documented. 

“Bicycle 

Methodology”

(chapter 19, 

HCM 2000) 

The bicycle methodology does not account for bicycle paths or lane-width reduction 

caused by fixed objects adjacent to these facilities. No credible data were found on fixed 

objects and their effects on bicycles using these types of facilities. In addition, the 

methodology does not account for the effects of right-turning motor vehicles crossing 

bicycle lanes at intersections or midblock locations, and grade is not considered. The 

methodology can be used for the analysis of facilities with grades from -3 to +3 percent. 

The effects created by more extreme grades are unknown. 
67 

Table 12. Limitations of the HCM methodologies (continued). 

Section Limitations 

“Two-Lane 

Highway 

Methodology”

(chapter 20, 

HCM 2000) 

Some two-lane highways—particularly those that involve interactions among several 

passing or climbing lanes—are too complex to be addressed by the procedures of HCM 

2000. For analytical problems beyond the scope of HCM 2000, see part V of HCM 2000, 

which describes the application of simulation modeling to two-lane highway analyses. 

Several design treatments discussed in appendix A in HCM 2000 are not accounted for 

by the methodology. 

The operational analytical methodologies in HCM 2000 do not address two-lane 

highways with signalized intersections. Isolated signalized intersections on two-lane 

highways can be evaluated using the signalized intersections methodology (chapter 16, 

HCM 2000). Two-lane highways in urban and suburban areas with multiple signalized 

intersections at spacings of 3.2 km (2.0 mi) or less can be evaluated using the urban 

street methodology (chapter 15, HCM 2000). 

“Multilane 

Highway 

Methodology”

(chapter 21, 

HCM 2000)

The methodology in HCM 2000 does not take into account the following conditions: 

• Transitory blockages caused by construction, crashes, or railroad crossings 

• Interference caused by parking on the shoulders (such as in the vicinity of a country 

store, flea market, or tourist attraction) 

• Three-lane cross sections 

• Effects of lane drops and additions at the beginning or ending of the segments 

• Possible queuing delays when a transition from a multilane segment to a two-lane 

segment is neglected 

• Differences between median barriers and two-way left-turn lanes 

• Free-flow speeds below 72 km/h (45 mi/h) or above 97 km/h (60 mi/h) 

“Freeway 

Methodology”

(chapter 22, 

HCM 2000) 

A complete discussion of freeway control systems or even the analysis of the 

performance alternatives is beyond the scope of HCM 2000. The reader should consult 

the references identified in HCM 2000. The methodology does not account for delays 

caused by vehicles using alternate routes or vehicles leaving before or after the 

duration of the study. 

Certain freeway traffic conditions cannot easily be analyzed by the methodology (e.g., 

multiple overlapping bottlenecks). Therefore, other tools may be more appropriate for 

specific applications beyond the capabilities of the methodology. Refer to part V, HCM 

2000, for a discussion of simulations and other models. 

User demand responses, such as spatial, temporal, modal, or total demand responses 

caused by traffic management strategies, are not automatically incorporated within the 

methodology. After viewing the facility traffic performance results, the analyst can 

modify the demand input manually to analyze the effect of user demand responses or 

traffic growth. The accuracy of the results depends on the accuracy of the estimation of 

the users’ demand responses. 

The freeway facility methodology is limited to the extent that it can accommodate 

demand in excess of capacity. The procedures address only local oversaturated flow 

situations, not systemwide oversaturated flow conditions. 

The completeness of the analysis will be limited if freeway segments in the first time 

interval, the last time interval, and the first freeway segment do not all have demandto-capacity ratios less than 1.00. The rationale for these limitations is discussed in the 

section on demand-capacity ratio. 
68 

Table 12. Limitations of the HCM methodologies (continued). 

Section Limitations 

“Freeway 

Methodology”

(chapter 22 

(continued), 

HCM 2000) 

Given enough time, the analyst can analyze a completely undersaturated time-space 

domain manually, although this is difficult. It is not expected that analysts will ever 

manually analyze a time-space domain that includes oversaturation. For heavily 

congested freeway facilities with interacting bottleneck queues, the analyst may wish to 

review part V, HCM 2000, before undertaking this methodology. 

“Basic Freeway 

Segment 

Methodology”

(chapter 23, 

HCM 2000)

The methodology does not apply to or take into account (without modification by the 

analyst) the following: 

• Special lanes reserved for a single vehicle type, such as HOV lanes, truck lanes, and 

climbing lanes 

• Extended bridge and tunnel segments 

• Segments near a toll plaza 

• Facilities with free-flow speeds below 89km/h (55 mi/h) or in excess of 121km/h 

(75 mi/h) 

• Demand conditions in excess of capacity (refer to chapter 22, HCM 2000, for further 

discussion) 

• Influence of downstream blockages or queuing on a segment 

• Posted speed limit, extent of police enforcement, or presence of ITS features related 

to vehicle or driver guidance 

• Capacity-enhancing effects of ramp metering 

The analyst would have to draw upon other research information and develop specialpurpose modifications of this methodology to incorporate the effects of the above 

conditions. 

“Freeway 

Weaving 

Methodology”

(chapter 24, 

HCM 2000) 

The HCM 2000 methodology does not specifically address the following subjects 

(without modifications by the analyst): 

• Special lanes, such as HOV lanes, in the weaving segment 

• Ramp metering on entrance ramps forming part of the weaving segment 

• Specific operating conditions when oversaturated conditions occur 

• Effects of speed limits or enforcement practices on weaving segment operations 

• Effects of ITS technologies on weaving segment operations 

• Weaving segments on collector-distributor roadways 

• Weaving segments on urban streets 

• Multiple weaving segments 

The last subject, which has been treated in previous editions of HCM, has been deleted. 

Multiple weaving segments must be divided into appropriate merge, diverge, and 

simple weaving segments for analysis. 

“Ramp and 

Ramp Junction 

Methodologies”

(chapter 25, 

HCM 2000) 

The HCM 2000 methodology does not take into account, nor is it applicable to (without 

modifications by the analyst), the following: 

• Special lanes, such as HOV lanes, as ramp entrance lanes 

• Ramp metering 

• Oversaturated conditions 

• Posted speed limits and the extent of police enforcement 

• Presence of ITS features 

Source: HCM 2000
69 

Appendix B: Tool Category Selection Worksheet 
Table 13. Tool category selection worksheet (refer to sections 2.1 and 2.2 for criteria definitions). 

70 
Table 13. Tool category selection worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued). 

71 
Table 13. Tool category selection worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued). 

72 
Table 13. Tool category selection worksheet (refer to sections 2.1 and 2.2 for criteria definitions) (continued). 

73 

75 

Appendix C: Tool Selection Worksheet 
Table 14. Tool selection worksheet. 

Tool Name: __________________________________________________ Version/Release: ___________________________

Vendor Name/Contact Information: ________________________________________________________________________

23 4 5

Sub-Criteria 

Relevance

Tool 

Relevance*

Col 2 x Col 3 Comments

1 Geographic Scope (0 = not relevant, 5 = most relevant)

Isolated LocationSegmentCorridor/Small NetworkRegionOther: _____________________________

Subtotal

Relevance Weights Above 0

WEIGHTED SUBTOTAL

2 Facility Type (0 = not relevant, 5 = most relevant)

Isolated IntersectionRoundaboutArterialHighway

UrbanRural

Freeway

MainlineShoulder

HOV Lane

Barrier-separatedBuffer-separatedShoulder HOVHOT Lane

HOV Bypass LaneRampAuxiliary LaneReversible LaneTruck LaneBus LaneToll PlazaLight Rail LineOther: _____________________________

Subtotal

Relevance Weights Above 0

WEIGHTED SUBTOTAL

1

Criteria

76 
Table 14. Tool selection worksheet (continued). 

23 4 5

Sub-Criteria 

Relevance

Tool 

Relevance*

Col 2 x Col 3 Comments

3 Travel Mode (0 = not relevant, 5 = most relevant)

SOVHOV

HOV 2+HOV 3+As percentage of total vehicles

Bus

LocalExpress

TrainTruckMotorcycleBicyclePedestrianOther: _____________________________

Subtotal

Relevance Weights Above 0

WEIGHTED SUBTOTAL

4 Management Strategy/Application (0 = not relevant, 5 = most relevant)

Freeway Management

Adding general purpose lanesAdding HOV lanesGeometric improvementsInterchange geometric improvementsElectronic toll collection (ETC)Fixed-time ramp meteringAdaptive/actuated ramp meteringCentrally controlled meteringAdd HOV bypassFreeway connector meteringReconstruction management

Arterial Intersections

Adding lanesPre-timed signalActuated signalTraffic adaptive control signalCentrally controlled signal

1

Criteria

77 
Table 14. Tool selection worksheet (continued). 

23 4 5

Sub-Criteria 

Relevance

Tool 

Relevance*

Col 2 x Col 3 Comments

4 Management Strategy/Application (0 = not relevant, 5 = most relevant) (continued)

Work Zone/Special Events

Road closures due to eventsTraffic diversion due to eventsWork zone managementWork zone safety monitoringMaintenance/construction vehicle AVLMaintenance/construction vehicle maintenance

Advanced Public Transportation Systems

Fleet maintenanceAutomatic scheduling for transitAutomatic vehicle location (AVL)Transit security systemsElectronic transit fare payment

Advanced Traveler Information Systems

Pre-trip ATISTelephone-based traveler informationWeb-based traveler informationKiosksHandheld traveler informationEn-route ATISHighway Advisory Radio (HAR)Dynamic Message Sign (DMS)Transit DMSIn-vehicle/handheld traveler information

Rail Grade Crossing MonitorCommercial Vehicle Operations

Fleet administrationElectronic screeningWeigh-in-motionElectronic clearanceSafety information exchangeOn-board safety monitoringElectronic roadside safety inspectionHazMat incident response/management

1

Criteria

78 
Table 14. Tool selection worksheet (continued). 

23 4 5

Sub-Criteria 

Relevance

Tool 

Relevance*

Col 2 x Col 3 Comments

4 Management Strategy/Application (0 = not relevant, 5 = most relevant) (continued)

Advanced Vehicle Control & Safety System

Ramp rollover warningDownhill speed warningLongitudinal collision avoidanceLateral collision avoidanceIntersection collision avoidanceVision enhancement for crashesSafety readinessAutomated highway system

Traffic Surveillance

CCTV/radar/microwaveLoop detectorsProbe vehicles

Travel Demand Management (TDM)

Dynamic ridesharingCongestion pricingFlex-timePark and ride facilitiesPreferential parkingTrip reduction programs

Traffic Calming

RoundaboutRaised intersectionSpeed humpsSpeed control

Parking Management

On-streetOff-street/parking garages

Bicycle Program

Bike lane/path routingBike racks/lockers

1

Criteria

79 
Table 14. Tool selection worksheet (continued). 

23 4 5

Sub-Criteria 

Relevance

Tool 

Relevance*

Col 2 x Col 3 Comments

4 Management Strategy/Application (0 = not relevant, 5 = most relevant) (continued)

Weather Management

Data collectionInformation processing/distributionAutomated treatmentWinter maintenanceResource allocation management

Other: _____________________________

Subtotal

Relevance Weights Above 0

WEIGHTED SUBTOTAL

5 Traveler Response (0 = not relevant, 5 = most relevant)

Route Diversion

Pre-Trip Route DiversionEn-Route Route DiversionAll-or-nothingCapacity restraintStochastic/probabilisticIncrementalEquilibriumDynamicTransit system-basedRoute-basedTimetable-basedMultipathOther: ___________________________

Departure Time ChoiceMode Shift

LogitNested logitOther: ___________________________

1

Criteria

80 
Table 14. Tool selection worksheet (continued). 

23 4 5

Sub-Criteria 

Relevance

Tool 

Relevance*

Col 2 x Col 3 Comments

5 Traveler Response (0 = not relevant, 5 = most relevant) (continued)

Destination Choice

Gravity modelFRATAR modelTrip chainingParking cost-basedOther: ___________________________

Induced/Foregone DemandOther: _____________________________

Subtotal

Relevance Weights Above 0

WEIGHTED SUBTOTAL

6 Performance Measures (0 = not relevant, 5 = most relevant)

LOS Circle all that apply: Aggregated by link/node/vehicle type/facility type/regionwide/other: ______Speed link/node/vehicle type/facility type/regionwide/other: ______

Space-mean speed link/node/vehicle type/facility type/regionwide/other: ______

Time-mean speed link/node/vehicle type/facility type/regionwide/other: ______

Travel Time link/node/vehicle type/facility type/regionwide/other: ______Volume link/node/vehicle type/facility type/regionwide/other: ______

Detector volume link/node/vehicle type/facility type/regionwide/other: ______

Link average volume link/node/vehicle type/facility type/regionwide/other: ______

Travel Distance link/node/vehicle type/facility type/regionwide/other: ______Ridership link/node/vehicle type/facility type/regionwide/other: ______Transit frequencyTransit reliabilityAverage Vehicle Occupancy (AVO) link/node/vehicle type/facility type/regionwide/other: ______V/C Ratio link/node/vehicle type/facility type/regionwide/other: ______Density link/node/vehicle type/facility type/regionwide/other: ______VMT/PMT link/node/vehicle type/facility type/regionwide/other: ______VHT/PHT link/node/vehicle type/facility type/regionwide/other: ______Delay link/node/vehicle type/facility type/regionwide/other: ______

Stopped delay link/node/vehicle type/facility type/regionwide/other: ______

Intersection delay link/node/vehicle type/facility type/regionwide/other: ______Total delay link/node/vehicle type/facility type/regionwide/other: ______

Queue Length link/node/vehicle type/facility type/regionwide/other: ______Number of Stops link/node/vehicle type/facility type/regionwide/other: ______

1

Criteria

81 
Table 14. Tool selection worksheet (continued). 

23 4 5

Sub-Criteria 

Relevance

Tool 

Relevance*

Col 2 x Col 3 Comments 5 Traveler Response (0 = not relevant 5 = most relevant) (continued) 6 Performance Measures (0 = not relevant, 5 = most relevant) (continued)

Crashes/ Accidents link/node/vehicle type/facility type/regionwide/other: ______

Accidents by severity link/node/vehicle type/facility type/regionwide/other: ______Incident Duration link/node/vehicle type/facility type/regionwide/other: ______

Travel Time Reliability link/node/vehicle type/facility type/regionwide/other: ______Emissions link/node/vehicle type/facility type/regionwide/other: ______Fuel Consumption link/node/vehicle type/facility type/regionwide/other: ______Noise link/node/vehicle type/facility type/regionwide/other: ______Vehicle Operating CostsAgency operating costsMode Split link/node/vehicle type/facility type/regionwide/other: ______Monetized Benefits link/node/vehicle type/facility type/regionwide/other: ______Net Benefit link/node/vehicle type/facility type/regionwide/other: ______Implementation Cost link/node/vehicle type/facility type/regionwide/other: ______Benefit/Cost link/node/vehicle type/facility type/regionwide/other: ______Other: _____________________________ link/node/vehicle type/facility type/regionwide/other: ______

Subtotal

Relevance Weights Above 0

WEIGHTED SUBTOTAL

7 Tool/Cost Effectiveness (0 = not relevant, 5 = most relevant)

Tool capital cost Price:Level of effort/training Training classes available:Easy to use

Windows-basedDrag-and-drop capabilities

Popular/well-trusted Years in the U.S. market:Hardware requirements Recommended minimum hardware:Data requirements

VolumeGeometryRoad conditionsSignal or meter phase/timingNode requirementsLink requirementsO-D tables

1

Criteria

82 
Table 14. Tool selection worksheet (continued). 

23 4 5

Sub-Criteria 

Relevance

Tool 

Relevance*

Col 2 x Col 3 Comments

7 Tool/Cost Effectiveness (0 = not relevant, 5 = most relevant) (continued)

Turn movements/fractionsTraffic compositionOccupancyControl devicesSpacing

Computer run time Average run time:Post-processing requirements

Metric option availableU.S. standards option available

Documentation

User's Manual Where to download:Newsgroup available Newsgroup address:Chat rooms available Chat room address:E-mail lists available How to join list:

User support Tech support contact:

Free/affordable annual cost of support Price:Toll-free support available Toll-free number:24-hour support available 24-hour support number:Rapid response Turnaround time:

Key parameters can be user-definedDefault values are providedIntegration with other software Compatible software:

Geocoding to GIS availableData exchange

Animation/presentation features

DynamicPassive

Network size limitations Size limitations (nodes, links, vehicles):Compatible with most operating systems Ideal OS:

1

Criteria

83 
Table 14. Tool selection worksheet (continued). 

23 4 5

Sub-Criteria 

Relevance

Tool 

Relevance*

Col 2 x Col 3 Comments

7 Tool/Cost Effectiveness (0 = not relevant, 5 = most relevant) (continued)

Other model capabilities/conditions

Oversaturated conditionsWeavingEffects of Incidents (objects, breakdowns, crashes)Weather effects (rain, ice, wind, snow)Queue spill backEffects of pedestriansEffects of bicycles/motorbikesEffects of parked vehiclesEffects of commercial vehiclesAcceleration/deceleration effects

Models U.S. (right-hand side) roadwaysOther: _____________________________

Subtotal

Relevance Weights Above 0

WEIGHTED SUBTOTAL

78 9

Criteria 

Weight

Weighted 

Subtotals

Col 7 x Col 8

1 Geographic Scope

2 Facility Type3 Travel Mode4 Management Strategy/Applications5 Traveler Response6 Performance Measures7 Tool/Cost Effectiveness

TOTAL SCORE

* Use the following values for Tool Relevance: 0 = not featured, 5 = strongly featured by the tool.

6

Criteria 

(0 = not relevant, 5 = most relevant)

1

Criteria

84 
85 

Appendix D: Recommended Reading 

The following documents are recommended reading for detailed overviews and 

comparisons of some of the more commonly used traffic analysis tools: 

Algers, S., E. Bernauer, M. Boero, L. Breheret, C. DiTaranto, M. Dougherty, K. Fox, and 

J.F. Gabard. Smartest Review of Micro-Simulation Models, Transport RTD, August 1997 

(available at www.its.leeds.ac.uk/projects/smartest/index.html). 

Elefteriadou, L., et al. Beyond the Highway Capacity Manual: A Framework for Selecting Simulation 

Models in Traffic Operational Analysis, Paper No. 991233, Transportation Research Board, 

Washington, DC, January 1999. 

Freeman, W.J., K.Y. Ho, and E.A. McChesney. An Evaluation of Signalized Intersection 

System Analysis Techniques (available at 

www.trafficware.com/documents/1999/00055.pdf). 

Mekemson, J., E. Herlihy, and S. Wong. Traffic Models Overview Handbook, Publication 

No. FHWA-SA-93-050, FHWA, 1993. 

Skabardonis, A. Assessment of Traffic Simulation Models, Washington State DOT, Seattle, 

WA, May 1999. 

Skabardonis, A. Simulation Models for Freeway Corridors: State-of-the-Art and Research Needs, 

(preprint), Paper No. 981275, Transportation Research Board, Washington, DC, January 

1998. 

“This Week’s Survey Results: Micro-Simulation Software Characteristics, Part I,” The 

Urban Transportation Monitor, Feb. 8, 2002, pp. 8-11. 

“This Week’s Survey Results: Micro-Simulation Software Characteristics, Part II,” The 

Urban Transportation Monitor, Feb. 22, 2002, pp. 8-12. 

“This Week’s Survey Results: Urban Transportation Planning Software, Part I,” The Urban 

Transportation Monitor, Apr. 5, 2002, pp. 9-11. 

“This Week’s Survey Results: Urban Transportation Planning Software, Part II,” The Urban 

Transportation Monitor, Apr. 19, 2002, pp. 8-13. 

Traffic Analysis Software Tools, Circular No. E-CO14, Transportation Research 

Board/National Research Council, September 2002. 

87 

Appendix E: Traffic Analysis Tools by Category 

E.1 Sketch-Planning Tools 

Examples of sketch-planning tools: 

• Better Decisions: http://mctrans.ce.ufl.edu/store/description.asp?itemID=165

• HDM (Highway Design and Management): http://hdm4.piarc.org

• IDAS (ITS Deployment Analysis System): http://idas.camsys.com

• IMPACTS: www.fhwa.dot.gov/steam/impacts.htm

• MicroBENCOST: http://mctrans.ce.ufl.edu/ti_ved/store/description.asp?itemID=166

• QuickZone: www.tfhrc.gov/its/quickzon.htm

• SCRITS (Screening for ITS): www.fhwa.dot.gov/steam/scrits.htm 

• Sketch Methods: http://plan2op.fhwa.dot.gov/toolbox/toolbox.htm

• SMITE (Spreadsheet Model for Induced Travel Estimation): 

www.fhwa.dot.gov/steam/smite.htm

• SPASM (Sketch-Planning Analysis Spreadsheet Model): 

www.fhwa.dot.gov/steam/spasm.htm

• STEAM (Surface Transportation Efficiency Analysis Model): 

www.fhwa.dot.gov/steam/index.htm

• TEAPAC (Traffic Engineering Applications Package)/SITE: 

www.strongconcepts.com/Products.htm

• TrafikPlan: http://mctrans.ce.ufl.edu/store/description.asp?itemID=162 

• TransDec (Transportation Decision): 

http://tti.tamu.edu/researcher/v34n3/transdec.stm

• Trip Generation: http://mctrans.ce.ufl.edu/store/description.asp?itemID=179

• Turbo Architecture: 

http://itsarch.iteris.com/itsarch/html/turbo/turbooverview.htm
88 

E.2 Travel Demand Models 

Available travel demand modeling tools: 

• b-Node Model: http://mctrans.ce.ufl.edu/store/description.asp?itemID=482

• CUBE/MINUTP: www.citilabs.com/minutp/index.html

• CUBE/TP+/Viper: www.citilabs.com/viper/index.html

• CUBE/TRANPLAN (Transportation Planning): 

www.citilabs.com/tranplan/index.html

• CUBE/TRIPS (Transport Improvement Planning System): 

http://citilabs.com/trips/index.html

• EMME/2: www.inro.ca/products/e2_products.html

• IDAS: http://idas.camsys.com

• MicroTRIMS: http://mctrans.ce.ufl.edu/store/description.asp?itemID=483

• QRS II (Quick Response System II): http://my.execpc.com/~ajh/index.html

• SATURN (Simulation and Assignment of Traffic to Urban Road Network): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=157 

• TModel: www.tmodel.com

• TransCAD: www.caliper.com/tcovu.htm

• TRANSIMS (Transportation Analysis Simulation System): 

http://transims.tsasa.lanl.gov

E.3 Analytical/ Deterministic Tools (HCM Methodologies) 

There is a wide array of analytical/deterministic tools currently available, including: 

• 5-Leg Signalized Intersection Capacity: 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=36

• aaSIDRA (Signalized and Unsignalized Intersection Design and Research Aid): 

www.aatraffic.com/SIDRA/aboutsidra.htm

• ARCADY (Assessment of Roundabout Capacity and Delay): 

www.trlsoftware.co.uk/productARCADY.htm
89 

• ARTPLAN (Arterial Planning): 

www11.myflorida.com/planning/systems/sm/los/default.htm

• CATS (Computer-Aided Transportation Software): 

http://tti.tamu.edu/product/software/cats

• CCG (Canadian Capacity Guide)/Calc2: 

www.bagroup.com/Pages/software/CCGCALC.html

• CINCH: http://mctrans.ce.ufl.edu/store/description.asp?itemID=4

• CIRCAP (Circle Capacity): www.teppllc.com/publications/CIRCAP.html

• DELAYE (Delay Enhanced): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=407

• dQUEUE-TOLLSIM (Dynamic Toll Plaza Queuing Analysis Program): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=290

• FAZWEAVE: http://tigger.uic.edu/~jfazio/weaving

• FREEPLAN (Freeway Planning): 

www11.myflorida.com/planning/systems/sm/los/default.htm

• FREWAY (Freeway Delay Calculation Program): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=291

• FRIOP (Freeway Interchange Optimization Model): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=408

• General-Purpose Queuing Model: 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=409

• Generalized Annual Average Daily Service Volume Tables: 

www11.myflorida.com/planning/systems/sm/los/default.htm

• Generalized Peak-Hour Directional Service Volume Tables: 

www11.myflorida.com/planning/systems/sm/los/default.htm

• GradeDec 2000: www.gradedec.com

• HCM/Cinema: www.kldassociates.com/unites.htm

• HCS (Highway Capacity Software) 2000: 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=48

• HiCAP (Highway Capacity Analysis Package): www.hicap2000.com
90 

• HIGHPLAN (Highway Planning): 

www11.myflorida.com/planning/systems/sm/los/default.htm

• Highway Safety Analysis: www.x32group.com/HSA_Soft.html

• ICU (Intersection Capacity Utilization): www.trafficware.com/ICU/index.html

• IQPAC (Integrated Queue Analysis Package): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=294

• Left-Turn Signal/Phase Warrant Program: 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=56

• NCAP (Intersection Capacity Analysis Package): www.tmodel.com

• PICADY (Priority Intersection Capacity and Delay): 

www.trlsoftware.co.uk/productPICADY.htm

• PROGO (Progression Graphics and Optimization): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=78

• Quality/Level of Service Handbook: 

www11.myflorida.com/planning/systems/sm/los/default.htm

• RoadRunner: http://mctrans.ce.ufl.edu/store/description.asp?itemID=85

• SIG/Cinema: www.kldassociates.com/unites.htm

• SIPA (Signalized Intersection Planning Analysis): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=22

• SPANWIRE: http://mctrans.ce.ufl.edu/store/description.asp?itemID=304

• SPARKS (Smart Parking Analysis): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=305

• Synchro: www.trafficware.com

• TEAPAC/NOSTOP: www.strongconcepts.com/Products.htm

• TEAPAC/SIGNAL2000: www.strongconcepts.com/Products.htm

• TEAPAC/WARRANTS: www.strongconcepts.com/Products.htm

• TGAP (Traffic Gap Analysis Program): www.tmodel.com

• TIMACS (Timing Implementation Method for Actuated Coordinated Systems): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=92
91 

• Traffic Engineer’s Toolbox: http://home.pacifier.com/~jbtech

• Traffic Noise Model: www.thewalljournal.com/a1f04/tnm

• TRAFFIX: www.traffixonline.com

• TSDWIN (Time-Space Diagram for Windows): 

www.fortrantraffic.com/whatsnew/new2.htm

• TS/PP-Draft (Time-Space/Platoon-Progression Diagram Generator): www.tsppd.com

• WEST (Workspace for Evaluation of Signal Timings): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=126

• WHICH (Wizard of Helpful Intersection Control Hints): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=127

• WinWarrants: http://home.pacifier.com/~jbtech

E.4 Traffic Optimization Tools 

Examples of traffic optimization tools: 

• PASSER (Progression Analysis and Signal System Evaluation Routine) II-02: 

http://ttisoftware.tamu.edu/fraPasserII_02.htm

• PASSER III-98: http://ttisoftware.tamu.edu/fraPasserIII_98.htm

• PASSER IV-96: http://ttisoftware.tamu.edu/fraPasserIV_96.htm

• PROGO: http://mctrans.ce.ufl.edu/store/description.asp?itemID=78

• SOAP84: http://mctrans.ce.ufl.edu/store/description.asp?itemID=435

• Synchro: www.trafficware.com

• TEAPAC/NOSTOP: www.strongconcepts.com/Products.htm

• TEAPAC/SIGNAL2000: www.strongconcepts.com/Products.htm

• TEAPAC/WARRANTS: www.strongconcepts.com/Products.htm

• TRANSYT-7F: http://mctrans.ce.ufl.edu/store/description.asp?itemID=437

• TSDWIN: www.fortrantraffic.com/whatsnew/new2.htm

• TS/PP-Draft: www.tsppd.com
92 

E.5 Macroscopic Simulation Models 

Examples of macroscopic simulation traffic analysis tools: 

• BTS (Bottleneck Traffic Simulator): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=287

• FREQ12: www.its.berkeley.edu/computing/software/FREQ.html

• KRONOS: www.its.umn.edu/labs/itslab.html

• METACOR/METANET: www.inrets.fr/ur/gretia/METACOR-Ang-H-HajSalem.htm

• NETCELL: www.its.berkeley.edu/computing/software/netcell.html

• PASSER II-02: http://ttisoftware.tamu.edu/fraPasserII_02.htm

• PASSER III-98: http://ttisoftware.tamu.edu/fraPasserIII_98.htm

• PASSER IV-96: http://ttisoftware.tamu.edu/fraPasserIV_96.htm

• SATURN: www.its.leeds.ac.uk/software/saturn/index.html

• TRAF-CORFLO (Corridor Flow): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=441

• TRANSYT-7F: http://mctrans.ce.ufl.edu/store/description.asp?itemID=437

• VISTA (Visual Interactive System for Transport Algorithms): 

http://its.civil.northwestern.edu/vista

E.6 Mesoscopic Simulation Models 

Three examples of mesoscopic simulation tools: 

• CONTRAM (Continuous Traffic Assignment Model): www.contram.com

• DYNAMIT-P, DYNAMIT-X, DYNASMART-P, DYNASMART-X: 

www.dynamictrafficassignment.org

• MesoTS: http://plan2op.fhwa.dot.gov/pdfs/Pdf2/mesoscopic.pdf
93 

E.7 Microscopic Simulation Models 

Examples of microscopic traffic simulation models: 

• AIMSUN2 (Advanced Interactive Microscopic Simulator for Urban and Non-Urban 

Networks): www.tss-bcn.com/aimsun.html

• ANATOLL: www.its.leeds.ac.uk/projects/smartest/append3d.html#a4 

• AUTOBAHN: www.its.leeds.ac.uk/projects/smartest/append3d.html#a5

• CASIMIR: www.its.leeds.ac.uk/projects/smartest/append3d.html#a6

• CORSIM/TSIS (Traffic Software Integrated System): www.fhwa-tsis.com

• DRACULA (Dynamic Route Assignment Combining User Learning and 

Microsimulation): www.its.leeds.ac.uk/software/dracula

• FLEXSYT-II: www.flexsyt.nl/informatieuk.htm

• HIPERTRANS (High-Performance Transport): www.cpc.wmin.ac.uk/~traffic

• HUTSIM (Helsinki University of Technology Simulator): 

www.hut.fi/Units/Transportation/HUTSIM

• INTEGRATION: www.intgrat.com

• MELROSE (Mitsubishi Electric Road Traffic Simulation Environment): 

www.its.leeds.ac.uk/projects/smartest/append3d.html#a14 

• MicroSim: www.zpr.uni-koeln.de/GroupBachem/VERKEHR.PG

• MICSTRAN (Microscopic Simulator Model for Traffic Networks): 

www.its.leeds.ac.uk/projects/smartest/append3d.html#a16

• MITSIM (Microscopic Traffic Simulator): http://web.mit.edu/its/products.html

• MIXIC: www.its.leeds.ac.uk/projects/smartest/append3d.html#a18

• NEMIS: www.its.leeds.ac.uk/projects/smartest/append3d.html#a19

• PADSIM (Probabilistic Adaptive Simulation Model): 

www.its.leeds.ac.uk/projects/smartest/append3d.html#a21

• PARAMICS: www.paramics-online.com

• PHAROS (Public Highway and Road Simulator): 

www.its.leeds.ac.uk/projects/smartest/append3d.html#a23
94 

• PLANSIM-T: www.its.leeds.ac.uk/projects/smartest/append3d.html#a24

• ROADSIM (Rural Road Simulator): www.kldassociates.com/simmod.htm

• SHIVA (Simulated Highways for Intelligent Vehicle Algorithms): 

www.its.leeds.ac.uk/projects/smartest/append3d.html#a25

• SIGSIM: www.its.leeds.ac.uk/projects/smartest/append3d.html#a26

• SIMDAC: www.its.leeds.ac.uk/projects/smartest/append3d.html#a27

• SIMNET: www.its.leeds.ac.uk/projects/smartest/append3d.html#a28

• SimTraffic: www.trafficware.com

• SISTM (Simulation of Strategies for Traffic on Motorways): 

www.its.leeds.ac.uk/projects/smartest/append3d.html#a29

• SITRA B+: www.its.leeds.ac.uk/projects/smartest/append3d.html#a30

• SITRAS: www.its.leeds.ac.uk/projects/smartest/append3d.html#a31

• SmartPATH: www.path.berkeley.edu/PATH/Research

• TEXAS (Texas Model for Intersection Traffic): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=449

• TRANSIMS: http://transims.tsasa.lanl.gov

• TRARR: www.engr.umd.edu/~lovell/lovmay94.html

• TWOPAS: www.tfhrc.gov/safety/ihsdm/tamweb.htm

• VISSIM: www.itc-world.com

• WATSim (Wide Area Traffic Simulation): www.kldassociates.com/unites.htm

E.8 Integrated Traffic Analysis Tools 

There are some programs or utilities available that integrate two or more programs to 

provide a common data input format (all allow a user to run several programs). Some 

examples of integrated traffic simulation models include: 

• AAPEX (Arterial Analysis Package Executive): 

http://mctrans.ce.ufl.edu/store/description.asp?itemID=426

• ITRAF: http://mctrans.ce.ufl.edu/store/description.asp?itemID=445
95 

• PROGO: http://mctrans.ce.ufl.edu/store/description.asp?itemID=78

• UNITES (Unified Integrator of Transportation Engineering Software): 

www.kldassociates.com/unites.htm

97 

Appendix F: References 

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