bluuebunny/crossref_metadata_2025 huggingface dataset:
Versatile Model for Simulation of Rural Road Traffic
Authors: Tapani Andreas
Published: May 2018

In many countries the road mileage is dominated by rural highways. For that reason it is important to have access to efficient tools for evaluation of the performance of such roads. For other road types, e.g., freeways and urban street networks, a wealth of microsimulation models is available. However, only a few models dedicated to rural roads have been developed. None of these models handles traffic flows interrupted by intersections or roundabouts, nor are the models capable of describing the traffic flow on rural roads with a cable barrier between oncoming lanes. These are major drawbacks when Swedish roads, on which cable barriers and roundabouts are becoming increasingly important, are modeled. Moreover, as new areas of application for rural road simulation arise, a flexible and detailed model is needed. Such applications include, among other things, simulation of driver assistance systems and estimation of pollutant emissions. This paper introduces a versatile traffic microsimulation model for the rural roads of today and of the future. The model system presented, the Rural Traffic Simulator (RuTSim), is capable of handling all common types of rural roads, including the effects of roundabouts and intersections on the traffic on the main road. The purpose of the paper is to describe the simulation approach and the traffic modeling used in RuTSim. A verification of the RuTSim model is also included. RuTSim is found to produce outputs representative of all common types of rural roads in Sweden.
Calibration and Validation of Microscopic Models of Traffic Flow
Authors: Brockfeld Elmar , Kühne Reinhart D. , Wagner Peter
Published: May 2018

Because microscopic models are heavily used in applications, the appropriate calibration and validation of these models have been a recent concern. The contribution of this paper is to compare some of these models by calibrating and validating them with data from double loop detectors on a multilane freeway. To simplify this task, the models were tested by simplifying the multilane reality to a simulation of only a single lane. The results show that by simulating the multilane road with single-lane models, calibration errors (Theil's U-value, or the root mean square error) of 14% to 16% were obtained. A validation of the models, which was done by taking the calibrated parameters of one data set to reproduce the other data sets, gives additional errors of about 0.5 to 2.5 percentage points. This is in good agreement with other calibration and validation approaches performed recently.
Development and Evaluation of a Procedure for the Calibration of Simulation Models
Authors: Park Byungkyu (Brian) , Qi Hongtu (Maggie)
Published: May 2018

Microscopic traffic simulation models have been playing an important role in the evaluation of transportation engineering and planning practices for the past few decades, particularly in cases in which field implementation is difficult or expensive to conduct. To achieve high fidelity and credibility for a traffic simulation model, model calibration and validation are of utmost importance. Most calibration efforts reported in the literature have focused on the informal practice, and they have seldom proposed a systematic procedure or guideline for the calibration and validation of simulation models. This paper proposes a procedure for microscopic simulation model calibration. The validity of the proposed procedure was demonstrated by use of a case study of an actuated signalized intersection by using a widely used microscopic traffic simulation model, Verkehr in Staedten Simulation (VISSIM). The simulation results were compared with multiple days of field data to determine the performance of the calibrated model. It was found that the calibrated parameters obtained by the proposed procedure generated performance measures that were representative of the field conditions, while the simulation results obtained with the default and best-guess parameters were significantly different from the field data.
Using Decision Support System and Graphical User Interface to Choose Appropriate Lane Configurations at Toll Facilities
Authors: Zarrillo Marguerite L.
Published: May 2018

This study shows that tools can be devised to assist engineers and operators make decisions concerning a network of toll roads. A decision support system (DSS) was connected to a database containing highway network hourly geometric and traffic information for one typical day. The DSS provided operators with online tools that could assist with their hour-to-hour decisions concerning toll plaza lane configurations. This pilot study could be extended, and the DSS could be connected to a realtime database to assist operators with their day-to-day decisions. Operators could plan for special scheduled events in which traffic volumes are known to surge. Engineers could design lane configurations at toll facilities that could meet traffic requirements. Engineers could also design new interchange locations and predict the effect on toll plaza segments. They could also predict the effect of adding additional lanes to busy highway segments. Highway operators could determine the effects of an incident or other unscheduled lane closing at any particular hour of the day. Furthermore, they could schedule maintenance and lane closings for construction at hours of the day in which bottlenecks are at a minimum.
Development of Methodology to Design Advanced Traffic Surveillance Systems for Traffic Information Based on Origin–Destination
Authors: Oh Cheol , Ritchie Stephen G.
Published: May 2018

The innovative feature of this study is first to develop a methodology for designing advanced traffic surveillance systems based on microscopic traffic simulations. The developed methodology makes it possible ultimately to obtain algorithm structures and associated parameter values. The methodology consists of two main simulation experiments. The first experiment includes a parametric evaluation based on Monte Carlo simulation to identify the required performance of the surveillance system. The second experiment involves performing a microscopic traffic simulation with actual surveillance algorithms and synthetic algorithm inputs. Paramics capable of adding various external modeling routines realized by advanced programming interfaces was used for both simulation experiments. As an application of the proposed methodology, an inductive signature–based anonymous vehicle tracking system was designed via origin–destination flow estimation problem. The outcomes of this study can serve as a logical and necessary precursor to field implementation of a variety of traffic surveillance systems.
Modeling Urban Link Travel Time with Inductive Loop Detector Data by Using the k-NN Method
Authors: Robinson Steve , Polak John W.
Published: May 2018

The need to measure urban link travel time (ULTT) is becoming increasingly important for network management and traveler information provision. This paper proposes the use of the k nearest neighbors ( k-NN) technique to estimate ULTT with the use of single loop inductive loop detector (ILD) data. Real-world data from London is used. This paper explores the sensitivity of travel time estimates to various k-NN design parameters. It finds that the k-NN method is not particularly sensitive to the distance metric, although care must be taken in selecting the right combination of local estimation method (LEM) and value of k. A robust LEM should be used. The optimized k-NN model is found to provide more accurate estimates than other ULTT methods. To obtain a more accurate estimate of ULTT, a potential application of this approach could be to aggregate GPS probe vehicle ULTT records from different times but the same underlying travel time distribution.
Markov Chain Monte Carlo Multiple Imputation Using Bayesian Networks for Incomplete Intelligent Transportation Systems Data
Authors: Ni Daiheng , Leonard John D.
Published: May 2018

The rich data on intelligent transportation systems (ITS) are a precious resource for transportation researchers and practitioners. However, the usability of this resource is greatly limited by missing data. Many imputation methods have been proposed in the past decade. However, some issues are still not addressed or are not sufficiently addressed, for example, the missing of entire records, temporal correlation in observations, natural characteristics in raw data, and unbiased estimates for missing values. This paper proposes an advanced imputation method based on recent development in other disciplines, especially applied statistics. The method uses a Bayesian network to learn from the raw data and a Markov chain Monte Carlo technique to sample from the probability distributions learned by the Bayesian network. It imputes the missing data multiple times and makes statistical inferences about the result. In addition, the method incorporates a time series model so that it allows data missing in entire rows–-an unfavorable missing pattern frequently seen in ITS data. Empirical study shows that the proposed method is robust and accurate. It is ideal for use as a high-quality imputation method for off-line application.
Simple Map-Matching Algorithm Applied to Intelligent Winter Maintenance Vehicle Data
Authors: Blazquez Carola A. , Vonderohe Alan P.
Published: May 2018

Intelligent winter maintenance vehicles are equipped with automatic vehicle location (AVL) technology, including differential Global Positioning System (DGPS) receivers and various additional sensors that collect equipment status and material use data. DGPS data points are associated with the nearest roadway centerline by calculating minimum perpendicular distances between each roadway centerline representation and the DGPS data points. Highly accurate roadway centerline maps and DGPS measurements are not always available. Thus, spatial mismatches may occur at converging and diverging roadways, divided highways, and intersections. Decision makers use winter maintenance performance measures to evaluate achievement of goals and objectives and to improve winter maintenance operations in public agencies. These performance measures are sensitive to spatial mismatches, which need to be resolved before calculations are done. This paper presents a simple map-matching algorithm that resolves spatial ambiguities by determining the correct roadway centerline on which the vehicle is traveling. The algorithm computes shortest paths between snapped DGPS data points using network topology and turn restrictions. A path is considered viable, and locations for the snapped DGPS data points correct, if similarity exists between values of calculated and recorded vehicle speeds. If a path is not feasible, DGPS points are snapped to alternative roadway centerlines contained within their buffers, shortest paths are recalculated, and speeds are again compared. Examples are presented to illustrate the implementation and effectiveness of the algorithm.
Efficient Map Matching of Large Global Positioning System Data Sets
Authors: Marchal F. , Hackney J. , Axhausen K. W.
Published: May 2018

Speed and location observations from Global Positioning System (GPS) loggers are quickly becoming an important source of data for travel behavior researchers. Postprocessing these data requires identifying the location of the GPS data points on a coded map of the transportation network. The output of the map-matching process is the identification of the routes that were actually taken. This paper presents an innovative map-matching algorithm that relies only on the GPS coordinates and the network topology. Examples are provided on a large data set for the Zürich area. The paper demonstrates the efficiency of the algorithm in regard to accuracy and computational speed.
Lane-Based Network for Flow Analysis and Inventory Management of Transportation Networks
Authors: Malaikrisanachalee Suphawut , Adams Teresa M.
Published: May 2018

The widely accepted link–node centerline network model inhibits lane-based traffic analysis and inventory management, specifically the ability to represent the availability of lanes, individual lane properties, connectivity among parallel lanes and at turns, and lane movement restrictions. A lane-based network overcomes the limitations by maintaining lanes as independent topological objects and thus supports data management, decision making, and network analysis at the lane level. The data model for a lane-based network uses a directed graph approach in which a set of unidirectional lanes and nodes is used to model traffic flow connectivity. The model manages the continuous lateral connectivity between parallel lanes by specifying the relative lateral position of the lanes on their parent roadways. This approach provides an efficient way to maintain lane topology and eliminates the requirement of turntables. This paper presents the model along with guidelines for lane-based inventory management and strategies for discretizing continuous lateral connectivity between parallel lanes to enable the use of existing routing algorithms (e.g., Dijkstra's). Finally, the paper presents a practical implementation built on the linear location referencing system of a state department of transportation.
Use of Microcracking to Reduce Shrinkage Cracking in Cement-Treated Bases
Authors: Sebesta Stephen
Published: May 2018

Shrinkage cracking occurs in cement-treated bases because of desiccation and cement hydration; eventually these cracks start to reflect through the pavement surfacing. Although initially considered cosmetic, these cracks open the pavement to water infiltration and increase the likelihood of accelerated pavement distress. Numerous options exist for minimizing the amount of reflective cracks that appear; microcracking is a promising approach. The microcracking concept can be defined as the application of several vibratory roller passes to the cement-treated base at a short curing stage, typically after 1 to 3 days, to create a fine network of cracks. In addition to the microcracked test sites, the contractor constructed moist-cured, dry-cured, and asphalt membrane–cured sites for comparison. Researchers used falling weight deflectometer (FWD) tests to control the microcracking process, periodic crack surveys to monitor crack performance, and FWD tests through time to track base moduli. Microcracking proved quite effective at reducing shrinkage cracking problems in the base; applying the procedure with three passes of the roller after 2 to 3 days of curing resulted in the best performance. In addition, researchers observed that, without microcracking, excessively high cement contents resulted in problematic cracking in the base even if they were cured according to good construction practice. Microcracking did not result in pavement damage or diminished inservice modulus; thus, microcracking should be considered a viable and inexpensive option to incorporate shrinkage crack control into the construction of cement-treated bases.
Accelerated Strength Improvement of Silty Sand with Nontraditional Additives
Authors: Santoni Rosa L. , Tingle Jeb S. , Nieves Miguel
Published: May 2018

A laboratory experiment was conducted to evaluate the effect of two products used to accelerate strength improvement of a silty sand (SM) material stabilized with nontraditional stabilizers. SM soil samples were mixed with selected products and tested under both “wet” and dry conditions after 1- and 7-day cures. Nine nontraditional stabilizers, including lignosulfonates, polymers, silicates, and tree resins, were evaluated in this experiment. Two accelerator products, an acrylic polymer and Type I portland cement, were evaluated. Samples were also stabilized with either an asphalt emulsion or cement to provide a comparison for traditional stabilizers under the same conditions. The average unconfined compressive strength (UCS) of three replicates of each mixture was compared with the results of the remaining mixtures, the traditional stabilization results, and a series of untreated control samples. The results indicate increased UCS of samples stabilized with Silicate 1 and Polymer 3 compared with both the untreated control series and the traditional stabilization alternatives. Lignosulfonate 1; Polymers 1, 2, 4, 5, and 6; and Tree Resin 1 did not demonstrate significant increased strength over the control series for the conditions of this experiment. The UCS following the 7-day cure provided the maximum UCS of the samples evaluated in both wet and dry conditions. One accelerator, cement, in combination with a nontraditional stabilizer did show significant improvement in early strength gain when compared to the control series.
Geogrid-Reinforced Pile-Supported Railway Embankments
Authors: Huang Jie , Han Jie , Collin James G.
Published: May 2018

Piles or columns have been used successfully in combination with geosynthetics to support embankments over soft soil. The inclusion of geosynthetic reinforcement over piles enhances load transfer from soil to piles, reduces total and differential settlements, and increases slope stability. It creates a more economical alternative than that without the geosynthetic. An existing geosynthetic-reinforced pile-supported embankment in Berlin was selected for numerical modeling and analysis. This embankment was constructed to support railways over deep deposits of peat and soft organic soils. Precast piles and caps were installed with a load transfer platform formed by three layers of geogrid and granular materials installed between the piles and the embankment fill. Instrumentation was installed to monitor the settlements of the embankment and the strains in the geogrid layers over time. A finite difference method, incorporated in the fast Lagrangian analysis of continua three-dimensional software, was used to model this embankment. In the numerical analysis, piles were modeled with pile elements, and caps were modeled as an elastic material. Geogrid elements built in the software were used to represent the geogrid reinforcement. Embankment fill, soft soil, firm soil, and platform fill material were modeled as linearly elastic perfectly plastic materials with Mohr–Coulomb failure criteria. The embankment was built by a number of lifts to simulate its construction. Numerical results and comparisons with field measurements on the vertical and lateral displacements, the tension along the reinforcement, and the axial forces and moments on piles are presented.
Assessment of Driver Fatigue, Distraction, and Performance in a Naturalistic Setting
Authors: Barr Lawrence C. , Yang C. Y. David , Hanowski Richard J. , Olson Rebecca
Published: May 2018

The results of a study to characterize episodes of driver fatigue and drowsiness and to assess the impact of driver fatigue on driving performance are documented. This data-mining effort performed additional analyses on data collected in an earlier study by the Federal Motor Carrier Safety Administration of the effects of fatigue on drivers in local and short-haul operations. The primary objectives of the study were to investigate fatigue as a naturally occurring phenomenon by identifying and characterizing episodes of drowsiness during all periods of driving and to determine the operational or driving environment factors associated with drowsy driving. A total of 2,745 drowsy events were identified in approximately 900 total hours of naturalistic driving video data. Higher levels of fatigue were associated with younger and less experienced drivers. In addition, a strong and consistent relationship was found between drowsiness and time of day. Drowsiness was twice as likely to occur between 6:00 a.m. and 9:00 a.m., and approximately 30% of all observed incidences of drowsiness occurred within the first hour of the work shift. Insights about the relationship between driver fatigue and driver distraction and inattention are provided. This study presents an analytical framework for quantitatively assessing driver fatigue and drowsiness as a function of driver characteristics and the driving environment. It is hoped that the results will help to identify effective countermeasures for drowsy driving that will reduce the number of commercial-vehicle-related fatalities and injuries.
Methods and Metrics for Evaluation of an Automated Real-Time Driver Warning System
Authors: MacCarley C. Arthur
Published: May 2018

There is significant interest among traffic management personnel in the use of automated warning systems to provide drivers with real-time information on hazardous conditions related to traffic, limited visibility, or roadway obstructions. However, the effectiveness of such systems in achieving desired traffic safety improvements has not yet been well quantified. Relative influences on traffic safety can be assessed in many ways, and overall conclusions must be based on an appropriate set of metrics and methodologies for a particular implementation. This work, supported by the California Office of Traffic Safety and the California Department of Transportation (Caltrans), builds on prior research to develop, deploy, and test various metrics and methods to evaluate a large-scale real-time driver warning system, the Caltrans automated warning system, installed on Interstate 5 and State Route 120 near Stockton, California. Methods include the analysis of historical accident data over an 11-year period, a direct assessment of the operational behavior of the system correlated with accident data, and a study of the direct effects of real-time warning messages on driver behavior. Instrumentation deployed to facilitate these detailed analyses is described. The resultant body of data supports the correlation of measurable traffic flow parameters with relative traffic safety.
Research Agenda for the Application of Visualization to Transportation Systems
Authors: Hughes Ronald
Published: May 2018

Critical research needs associated with the effective application of visualization to transportation systems projects are identified. Visualization research needs are discussed within a broader, multidisciplinary context of technology development in the areas of simulation and modeling. Parallels are drawn between the current state of the practice in transportation as compared with that in the military–defense and aerospace areas. Some major differences between those areas and transportation systems development and user environments are noted, in particular ( a) the current absence within the transportation community of a strong government research and development focal point for visual simulation and modeling and ( b) the absence of an economic imperative similar to what prompted the defense community to embrace fully these technologies (i.e., fuel shortages, training system costs, and force readiness).
Virtual Reality Visualization of Microscopic Traffic Simulations
Authors: Zhou Bo , Blum Jeremy , Eskandarian Azim
Published: May 2018

Traditional microscopic traffic simulations visualize simulation results in two dimensions. Visualization in three dimensions provides additional versatility to these simulations and allows the utilization of their results for additional purposes. An approach to visualization of CORSIM simulations in three dimensions with the use of a personal computer–based virtual reality package is presented. The key to this approach is translation of the network geometry and traffic data, which is done by a specially designed middleware program. A practical simulation problem is presented to demonstrate the visualization procedure and its assessment. Potential improvements over the current work are discussed.
Economic Impact of Investments in Bicycle Facilities
Authors: Meletiou Mary Paul , Lawrie Judson J. , Cook Thomas J. , O'Brien Sarah W. , Guenther John
Published: May 2018

The northern Outer Banks coastal area in North Carolina is well suited to drawing bicycle tourism because of its geography, climate, and attractions. In 2003, the North Carolina Department of Transportation commissioned a study to examine the value of public investment in bicycle facilities that have been constructed in this area over the past 10 years at a cost of approximately $6.7 million. A particular challenge in conducting this study was that tourists visited the Outer Banks for a variety of reasons, not just for cycling. Thus, the collection of information on the amount and nature of bicycling activity and on the spending patterns of bicyclists in the area was critical for the development of an economic impact analysis. Researchers surveyed cyclists using the bicycle facilities (shared-use paths and wide paved shoulders) and obtained data from self-administered surveys of tourists at visitor centers during the primary tourist season. The data collected were then used to determine the economic impact of bicycling visitors to the area. Seventeen percent of tourists to the area reported that they bicycled while there; this translates to 680,000 people annually. The economic impact of bicycling visitors is significant: a conservative annual estimate is $60 million, with 1,407 jobs created or supported per year. This is almost nine times greater than the one-time expenditure required to construct the facilities. Continued investment in bicycle facilities is expected to increase this favorable economic impact and is therefore recommended.
Estimating Bicycling Demand
Authors: Barnes Gary , Krizek Kevin
Published: May 2018

Simple and reliable tools for estimating and predicting the amount of bicycling in an area would be useful for a variety of investment and policy decisions. Previous efforts to develop such tools have typically tried to develop demand estimates from basic descriptors of the population, land use, and bicycling facilities of an area. This paper takes an alternative approach by using the idea of deriving estimates of the likely range of total bicycling demand in an area on the basis of census commute-to-work data. The paper makes three contributions. The first is a general discussion of the total amount of bicycling in the United States and how it varies across places, on the basis of a number of surveys and some original data analysis. The second is the development of an argument that predictive models based on land use and transportation factors are unlikely to ever be accurate or useful because of a number of intractable problems. Third, a simple model is developed for estimation of a range of current levels of bicycling in a given geographic area with reasonable and known accuracy and by use of easily available data. While this model stops short of predicting bicycling levels or demand on specific facilities, it is an important first step in reaching these objectives. There is such a high degree of local variation in bicycling rates in the United States that attempts to predict bicycling levels directly without accounting for current levels are unlikely to be consistently successful.
Prediction of Pavement Crack Initiation from In-Service Pavements
Authors: Loizos Andreas , Karlaftis Matthew G.
Published: May 2018

It is widely accepted that the success of pavement management systems largely depends on the quality of the deterioration models embedded in their structure. As such, much research has concentrated on developing a large array of approaches to model and predict pavement distress and deterioration. This study develops surface distress prediction models for pavement failure times (the initiation of cracking on the surface of flexible and semirigid pavements) on the basis of a large (more that 1,000 observations) and recent (1998) data set collected from in-service pavements in 15 European countries by using the principles of stochastic duration (hazard) models. The results indicate that, as expected, construction, traffic, and climatic factors affect pavement distress and that the lognormal functional form, in contrast with the findings of previous studies, best describes the distress initiation process.
Statistical Analysis of Automated versus Manual Pavement Condition Surveys
Authors: McQueen Jason M. , Timm David H.
Published: May 2018

The Alabama Department of Transportation (ALDOT) has used a vendor to perform automated pavement condition surveys for the Alabama pavement network since 1997. In 2002, ALDOT established a quality assurance (QA) program to check the accuracy of the automated pavement condition data. The QA program revealed significant discrepancies between manual and automatically collected data. ALDOT uses a composite pavement condition index called pavement condition rating (PCR) in its pavement management system. The equation for PCR was developed in 1985 for use with manual pavement condition surveys; however, ALDOT continues to use it with data from automated condition surveys. Since the PCR equation was developed for manual surveys, the discrepancies between the manual and automated data led ALDOT to question the continuity between its manual and automated pavement condition survey programs. A regression analysis was completed to look for any systematic error or general trends in the error between automated and manual data. Also, Monte Carlo simulation was used to determine which distress parameters most influence the PCR and whether they require more accuracy. The regression analysis showed the following general trends: automated data overreport outside wheelpath rut depth, under-report alligator severity Level 1 cracking, and overreport alligator severity Level 3 cracking. Through Monte Carlo simulation, it was determined that all severity levels of transverse cracking, block cracking, and alligator cracking data require greater accuracy.
Accuracy of Ground-Penetrating Radar for Estimating Rigid and Flexible Pavement Layer Thicknesses
Authors: Al-Qadi Imad L. , Lahouar Samer , Jiang Kun , McGhee Kevin K. , Mokarem David
Published: May 2018

In this paper, the accuracy of ground-penetrating radar (GPR) for estimating pavement layer thicknesses is studied on the basis of the investigation of 17 pavement sites in Virginia. The considered sites have different types of pavement systems (flexible, continuously reinforced, jointed concretes, and composite) and different ages (0 to 5 years; 10 to 15 years; older than 20 years with a surface less than 10 years; and older than 20 years with a surface older than 10 years). Because of the diversity of the test sections considered, the accuracy of the GPR thicknesses was studied for pavement age for the same type of pavement and against pavement type for sites of the same age category. For flexible pavements, the GPR thickness error was found to increase as the pavement's age increased (4.4% error for pavements 0 to 5 years old versus 5.8% error for pavements older than 20 years with surfaces older than 10 years). Moreover, for the same age category, flexible pavements were found to have a relatively high thickness error (4.4%) compared with the continuously reinforced concrete pavements (3.0%) and with the jointed plain concrete pavements (2.3%) because of the relative homogeneity of concrete for electromagnetic wavelength when compared with the different dielectric profile of aged hot-mix asphalt layer.
Energy Efficiency, Fuel Economy, and Policy Implications
Authors: Lutsey Nicholas , Sperling Daniel
Published: May 2018

In the past 20 years, the acceleration performance of light-duty vehicles in the United States has improved substantially while vehicles have gotten larger and heavier. Over the same period, fuel economy, measured as miles per gallon, has not improved. These data suggest that technological innovation in vehicles is not lagging but is not being used to improve vehicle fuel economy. This paper quantifies vehicle efficiency improvements in U.S. light-duty vehicles since 1975 as they relate to fuel consumption. Energy efficiency improvements have been strongly positive and relatively constant since 1975. The rapid rise in fuel economy in the late 1970s was due to a mix of efficiency improvements and downgrading of utility in the form of reduced size, power, and elimination of accessories and amenities (such as air conditioning). In contrast, since the mid-1980s, fuel economy has remained constant while the benefits of technological innovation were used to satisfy private desires (more power, size, and amenities), instead of the public interest (reduced greenhouse gas emissions and oil imports). An important policy question is how and to what extent future efficiency innovations might be directed to the public interest.
Introduction of Hybrid and Diesel Vehicles
Authors: Santini Danilo J. , Vyas Anant D.
Published: May 2018

The positions of the diesel and hybrid light-duty passenger vehicles in the technology adoption life cycle are examined with a mid-2004 stated preference study of 1,036 households. Implications of the technology life cycle for historical consumer preference estimates obtained for use in prior models of market share are briefly discussed. The hypothetical life-cycle segments addressed in this paper are early adopters, early buyers, and majority buyers. Survey respondents are segmented into subgroups, or markets, in light of hypothesized attributes of consumers within the product life cycle. Emphasis is placed on delineating the preferences of new instead of used vehicle buyer segments. These categories are compared with the five categories in the high-tech technology adoption life-cycle paradigm of G. Moore. One purpose of the analysis is to use the survey as a test of the reasonableness of the three categories used here. The implications of the survey for use of the rational buyer model of consumer trade-offs of incremental new vehicle capital cost (of a diesel or hybrid) against reduced fuel cost are addressed. Competition of desires for fuel efficiency, acceleration, and towing is also addressed, as are the effects of gender, income, education, and age.
Designing On-Road Vehicle Test Programs for the Development of Effective Vehicle Emission Models
Authors: Younglove Theodore , Scora George , Barth Matthew
Published: May 2018

Mobile source emission models for years have depended on laboratory-based dynamometer data. Recently, however, portable emission measurement systems (PEMS) have become commercially available and in widespread use, and make on-road real-world measurements possible. As a result, the newest mobile source emission models (e.g., U.S. Environmental Protection Agency's mobile vehicle emission simulator) are becoming increasingly dependent on PEMS data. Although on-road measurements are made under more realistic conditions than laboratory-based dynamometer test cycles, they introduce influencing variables that must be carefully measured for properly developed emission models. Further, test programs that simply measure in-use driving patterns of randomly selected vehicles will result in models that can effectively predict current-year emission inventories for typical driving conditions. However, when predicting more aggressive transportation operations than current typical operations (e.g., higher speeds, accelerations), the model predictions will be less certain. In this paper, various issues associated with on-road emission measurements and modeling are presented. Further, an example on-road emission data set and the reduction in estimation error through the addition of a short aggressive driving test to the in-use data are examined. On the basis of these results, recommendations are made on how to improve the on-road test programs for developing more robust emission models.
MOBILE6.2 Modeling of Exhaust Air Toxic Emission Factors
Authors: Tang Tianjia , Claggett Michael , Byun Joon , Roberts Mike , Granell Jessica , Aspy Dale E.
Published: May 2018

The newly released MOBILE6.2 has incorporated both air toxic and particulate matter emission factor modeling functions. A series of test runs were performed to gain a better understanding of the air toxic modeling function and overall model behavior. These test runs and scenarios evaluated the changes in emission factors of all six built-in air toxic compounds as affected by vehicle activities, fuel physical properties, fuel chemical compositions, oxygenated fuel additives, and environmental conditions. Results obtained indicate that exhaust emission factors for acrolein, acetaldehyde, benzene, 1,3-butadiene, formaldehyde, and methyl tertiary butyl ether are inversely proportional to freeway and arterial vehicle speeds. This phenomenon follows the trend of total organic gas emission factors. Effects from roadway facility differences indicated that the higher the percentage of vehicle miles traveled on a freeway, the lower the air toxic emission factors on a per vehicle mile traveled basis. Exhaust air toxic emission factors increase when fuel Reid vapor pressure value and sulfur content increase. Diesel sulfur content has no effect on the six toxic compound emission factors. Effects from fuel chemical compositions on all emission factors varied. However, chemical compositions do have significant effects on all air toxic compound emission factors. On the same note, both minimum and maximum temperatures affect all air toxic emissions significantly. The time series evaluation indicates that all six tested air toxic compound emissions decrease linearly from the year 2002 to 2020.
Multi-Agency Permitting Teams
Authors: Smith Jason W. , Weber Sherry L.
Published: May 2018

Over the past several years, the State of Washington has invested substantial time and energy to streamline the environmental regulatory and permit process. The creation of the Multi-Agency Permitting Team (MAP team) pilot is one such strategic investment. The concept is based on the idea that an interagency team composed of diverse disciplines, located within one office, will experience enhanced communication, coordination, and higher-quality, more timely permit decisions. Currently, the MAP team consists of staff from five government agencies: the U.S. Army Corps of Engineers, Washington State Department of Ecology, Washington State Department of Fish and Wildlife, Washington State Department of Transportation, and King County Department of Development and Environmental Services. Fifty-two transportation projects are assigned to the team. After initially defining how to work together, the team began communications with their customer base in an attempt to make permitting processes more consistent and predictable. The team has been using this feedback to initiate streamlining opportunities to define complete applications, to create early project coordination and MAP team permit processes, to identify improvement opportunities within each agency, and to create model business practices that will use existing project experiences to deliver future projects. These investments in early project coordination are being tracked through eight performance measures. The MAP team pilot sunsets on June 30, 2005, and, if successful, Washington State may institute the MAP team concept as a permanent business practice with the potential for growth in other transportation, intergovernmental, and private venture applications.
Measuring and Modeling Emission Effects for Toll Facilities
Authors: Coelho Margarida C. , Farias Tiago L. , Rouphail Nagui M.
Published: May 2018

At conventional pay tolls, vehicles joining a queue must come to a stop and undergo several stop-and-go cycles until payment is completed. As a result, emissions increase because of excessive delays, queuing, and speed change cycles for approaching traffic. The main objective of this research is to quantify traffic and emission impacts of toll facilities in urban corridors. As a result of experimental measurements of traffic and emissions, the impact of traffic and emission performance of conventional and electronic toll facilities is presented. The approach attempts to explain the interaction between toll system operational variables (traffic demand, service time, and service type) and system performance variables (stops, queue length, and emissions). The experimental data for validating the numerical traffic model were gathered on pay tolls located in three main corridors that access the city of Lisbon, Portugal. The emissions model is based on real-world onboard measurements of vehicle emissions. With the appropriate speed profiles of vehicles in pay tolls, onboard emission measurements were carried out to quantify the relationships between vehicle dynamics and emissions. The main conclusion of this work is that there are two different types of stop-and-go driving cycles for vehicles joining the queue at a conventional toll booth: short and long. The length of each cycle depends on the expected queue length at the toll booth and the frequency of each cycle directly affects the level of vehicle emissions. The greatest percentage of emissions for a vehicle that stops at a pay toll is due to its final acceleration back to cruise speed after leaving the pay toll.
Empirical Analysis of the Impact of Security Perception on Intercity Mode Choice
Authors: Srinivasan Sivaramakrishnan , Bhat Chandra R. , Holguin-Veras Jose
Published: May 2018

In the aftermath of the terrorist attacks of September 11, 2001, individuals have become increasingly conscious of travel safety and security issues. Hence, in addition to travel times and costs, perceptions about security levels can be an important factor influencing intercity travel decisions. In the past few years, the Transportation Security Administration (TSA) has implemented several procedures, including rigorous screening, to improve airline security. However, these procedures have increased airline travel times. An empirical analysis is presented of individuals’ mode choice for intercity business trips incorporating trade-offs between improved security levels and increased travel times. Stated-preference data collected in New York City were used to develop a panel rank-ordered mixed logit model. It was found that individuals who held positive impressions about the security measures were more likely to fly but the utility of air mode decreased with increasing inspection and boarding time. The implication of these empirical results is that the TSA should seek both to improve public perceptions of the security arrangements and to ensure fast and efficient screening so as to sustain or increase the demand for air travel. Caution should be administered in generalizing these findings, however, as they are based on a small sample and on data gathered from an area directly affected by the events of September 11. In summary, the importance of research toward understanding the role of security perceptions on intercity travel decisions is reiterated, and a first step in this direction is presented.
Generating Optimal Controlled Prescriptive Route Guidance in Realistic Traffic Networks
Authors: Zuurbier Frank S. , van Zuylen Henk J. , Hoogendoorn Serge P. , Chen Yusen
Published: May 2018

A generic methodology to generate optimal controlled dynamic prescriptive route guidance to be disseminated by means of variable message signs (VMSs) is presented. The methodology is generic in the sense that it can be used on any network topology and network model, with any number of VMSs, for different traffic scenarios (e.g., recurrent congestion, accidents, or special events); is based on a flexible, user-defined objective function; and will work as long as feasible route alternatives exist. The presented methodology calculates prescriptive VMS settings with the objective of minimizing the total generalized travel time. An evolutionary algorithm is used to generate and optimize VMS scenarios. A new traffic model, DSMART, has been developed to assess the quality of the route guidance. A prototype of the guidance system has been developed in Matlab and applied in a case study of Rotterdam, Netherlands, by using a network representation of the motorway with six different VMSs and the connected urban network. Results from the case study prove the generic nature of the methodology and its ability to improve overall network conditions for various traffic scenarios.
Statistical Investigations of Statutory Holiday Effects on Traffic Volumes
Authors: Liu Zhaobin , Sharma Satish
Published: May 2018

Traffic volume fluctuates from time to time and from location to location, with significant variations in demand as a result. The increases in travel during statutory holiday periods are substantial, and some critical traffic problems have been reported. An understanding of this substantial variation in the volume of traffic can assist transportation agencies in developing practical countermeasures in aspects such as traffic control plans, signal timing, safety programs, traffic volume monitoring, and prediction. The literature on holiday traffic is limited, and no effort has been made to examine statistically the significance of changes in traffic volume due to holiday effects. With the past 20 years of data collected by permanent traffic counters on highways in Alberta, Canada, holiday effects on road traffic are shown graphically. Then, the nonparametric Wilcoxon matched pair test is used to test the variation characteristics of normal flow, the Friedman method is applied to investigate the holiday effects on weekly and daily traffic, and the hourly volume pattern changes are examined by a combination of χ2 and binomial tests. The test results reveal that holidays substantially contribute to the variability of traffic. The weekly volume variations during holiday periods are significant in many cases, holiday effects on daily and hourly traffic are evident, and the directional holiday traffic peaking features are strong. Meanwhile, general identifications of the affected holidays for different types of roads are provided. Potential implications of these findings are discussed.
Artificial Neural Network Method for Length-Based Vehicle Classification Using Single-Loop Outputs
Authors: Zhang Guohui , Wang Yinhai , Wei Heng
Published: May 2018

Classified vehicle volumes are important inputs for traffic operation, pavement design, and transportation planning. However, such data are not available from single-loop detectors, the most widely deployed type of traffic sensor in the existing roadway infrastructure. Several attempts have been made to extract classified vehicle volume data from single-loop measurements in recent years. These studies used estimated speed for length calculation and classified vehicles into bins based on the calculated vehicle lengths. However, because of the stochastic features of traffic flow, deterministic mathematical equations based on certain assumptions for speed calculation typically do not work well for all situations and may result in significant speed estimation errors under certain traffic conditions. Such errors accumulate when estimated speeds are used in vehicle-length calculations and degrade the accuracy of vehicle classification. To solve this problem, an artificial neural network method was developed to estimate classified vehicle volume data directly from single-loop measurements. The proposed neural network is three-layered with a back-propagation structure. This method was tested with data collected from several loop stations on I-5 over a long duration. The proposed artificial neural network model produced reliable estimates of volumes of classified vehicles under various traffic conditions.