bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating Effects of Correlated Service Times on System Performance: Implications in Border Crossing Operations
Authors: Cetin Mecit , List George F.
Published: April 2007

Many transportation systems rely on information technology (IT) for effective and efficient system operations. When the IT systems or resources are shared among various processes or servers, the service times of these processes or servers become correlated. Failure to recognize such correlations in model development may lead to significant inaccuracies. The effects of various types of correlation in the context of border crossing operations were investigated. Several possible reasons for correlation among servers and the ways in which such correlations may affect system operations are explained. Three scenarios are investigated through numerical experimentation: correlated tandem queues, correlated parallel queues, and the impact of correlated parallel queues on a downstream service station. Models are developed with and without consideration for the correlation for these three cases. Ignoring correlation in the performance analysis (i.e., assuming that the servers are independent) leads to inaccurate results, especially when system use is great, that is, at high levels of congestion. In the case of parallel queues, independence assumption leads to overestimated system capacity and to underestimated capacity in tandem queues.
Monte Carlo Simulation of Household Travel Survey Data for Sydney, Australia: Bayesian Updating Using Different Local Sample Sizes
Authors: Pointer Graham , Stopher Peter R. , Bullock Philip
Published: April 2007

Interest is increasing in the potential to simulate household travel survey data as an alternative to collecting large sample household travel surveys or as a means to augment sample sizes. In earlier research on simulating such data, it was shown that it was possible to reproduce, within reasonable bounds of accuracy, an actual household travel survey. It has also been found that the procedure for updating the distributions of the simulated variables, by using Bayesian updating with subjective priors, can provide significant improvement in the accuracy with which an actual household travel survey can be simulated. In work performed to date, the optimal size for the update sample to be used in the Bayesian updating has not been determined. Rather, earlier work used a sample of approximately 500 households, primarily because of convenience and cost. In further research that compared different sample sizes for the local update data, it was found that a reasonable updating could be obtained from a sample as small as 300 households, chosen through a stratified sampling procedure, and that results improved substantially when the update sample was increased to 500. However, an increase in the sample to 750 did not produce much improvement, which suggested that samples of this size and larger may not be economically justified. The research suggests that there may be room for a more targeted sampling procedure, which might allow smaller samples to be more cost-effective.
Rules for Assessing Data Quality of Activity-Scheduling Survey Respondents
Authors: Doherty Sean T.
Published: April 2007

The development of standards and guidance for applying quality measures in travel surveys is receiving increased attention. The most commonly reported quality measures are unit nonresponse and trip rates. How such a standard would be applied for assessing the quality of a single respondent's data remains unexplored. Furthermore, new quality indicators are needed for emerging travel survey methods, such as multiday and computerized scheduling surveys that capture observed activity travel patterns as well as information on underlying activityscheduling decision processes. A new set of rules is proposed for assessing data of individual respondents by using results from a recent survey of this type. The use of computers and a focus on decision processes led to developing several new quality indicators related to respondent login durations, data entry delays, entry timing, and recall rates. Analysis of these indicators was used to propose six rules for identifying goodquality data. A combined single rule was also developed by using principal component analysis. Further analysis of this combined indicator revealed that sociodemographic characteristics of the respondents were largely insignificant—people of all ages, genders, marital status, and employment or student status were equally able to provide good data. It also suggests that use of the combined indicator to filter out poorquality data will not necessarily introduce any additional bias into the resulting reduced sample set. The weak correlation of respondent activity or trip rates with the combined indicator implies that their usefulness for assessing data quality at an individual level is questionable.
Pavement Smoothness at Weigh-in-Motion Sites: Developing Specifications for the Long-Term Pavement Performance Program
Authors: Karamihas Steve M. , Rada Gonzalo R. , Ostrom Barbara K. , Simpson Amy L. , Wiser Larry J.
Published: April 2007

Accurate traffic data are vital to the success of the Long-Term Pavement Performance (LTPP) program. To minimize dynamic motions and therefore improve the accuracy of traffic loading data at weigh-in-motion (WIM) scales, pavement smoothness specifications were developed to screen sites for excessive truck dynamic loading that exacerbates scale error beyond ASTM recommended tolerances. WIM scale error was related to pavement profile characteristics by using a large simulation study of the response of virtual trucks over measured profiles. A distribution of error was compiled over the truck population for steer axle, tandem axle, and total vehicle weight at each site. The error distributions were summarized by their 95th percentile absolute error levels. The error levels assigned to each site were then used as a correlation standard for the proposed roughness indices and for the selection of corresponding threshold values. Instead of a single index, two versions of the Butterworth filter were selected for use in the specifications. One addresses short-range roughness and the other long-range roughness. The shortand long-range WIM error indices were then statistically related to WIM scale error to set the threshold values. An overview is presented of the development of the pavement smoothness specifications, including indices and threshold values.
Statistical Methods for Detecting Spatial Configuration Errors in Traffic Surveillance Sensors
Authors: Kwon Jaimyoung , Chen Chao , Varaiya Pravin
Published: April 2007

With large-scale deployment of traffic surveillance sensors becoming commonplace, it becomes critical to maintain correct information about the spatial configuration of the sensors. The problem is burdensome when hundreds or thousands of sensors are deployed. One common configuration error is the switching of directions of highway loop detectors that share the same cabinet. Proposed are semiautomatic and automatic methods for detecting such errors, on the basis of the strong correlations between measurements made by spatially close sensors. The semiautomatic method uses a multidimensional scaling (MDS) map of sensors, which visually displays the similarity between sensor measurements and enables one to easily identify sensor mislabeling. The automatic method uses a scoring scheme that computes the probability of sensor mislabeling from the pairwise distance or similarity matrix. The algorithm, tested on data from a four-lane freeway consisting of 64 sensor locations—10 of which had switched locations—successfully detected all errors with 5.6% false detection rate, even with poor data quality. The MDS map can be used for other applications, such as detection of sensor malfunctions.
Enhancement of Vehicle Speed Estimation with Single Loop Detectors
Authors: Lin Wei-Hua , Dahlgren Joy , Huo Hong
Published: April 2007

Traffic data from single loop detectors are a dominant data source widely used in traffic operation centers and traveler information systems. Speed estimation from single loop detectors is based mainly on occupancy data, a conversion factor from occupancy to density (which is related to vehicle length), and the assumed relationship between flow, speed, and density. The discrepancy between the speed estimated with single loops and the speed measured directly from double loops was investigated. It was found that the inaccuracy of speed estimation done with single loops was caused mainly by the irregular behavior of vehicle pace. Under congested or unstable traffic conditions, the distribution of vehicle pace within a given time interval often exhibits a large variance accompanied by a strong skewness. Accuracy in speed estimation can be improved by computing occupancy in a different way—by using median vehicle passage time over the detector—instead of mean vehicle passage time, often used in the conventional method. The performance of the enhanced speed estimation method is very encouraging. The use of the median vehicle passage time reduces the skewness of pace data.
Application of Regression Analysis for Identifying Factors That Affect Seasonal Traffic Fluctuations in Southeast Florida
Authors: Li Min-Tang , Zhao Fang , Wu Yifei
Published: April 2007

Traffic variations occur at different time scales—time of day, day of week, and season of the year. Among the known temporal fluctuations of traffic stream, seasonal variation is probably of the most concern in traffic monitoring. In the current practice of the Florida Department of Transportation, district offices determine seasonal factor categories from a group of selected permanent telemetry traffic monitoring sites and assign them to short-term traffic count sites for estimating annual average daily traffic. Assignment of short-count sites to factor groups is based largely on their spatial proximity to a permanent traffic count site and engineering judgment. Although location may be an important factor, this process may be oversimplified and somewhat subjective. Regression analyses for estimating seasonal factors shed light on the factors contributing to seasonal changes in traffic volumes. The method could reduce the subjectivity of current practice either by allowing seasonal factors to be estimated directly for each short-count station or by providing guidance for assignment of seasonal groups to short-term counts.
Development of Container Barge Transport on Small Waterways: From Increasing Scale to Increasing Scope
Authors: Konings Rob
Published: April 2007

The container barge sector's challenge of increasing its market share by increasing its geographical scope is addressed. For 30 years, container barge transport has been a strong, growing business in Europe, but a focus on increasing the scale of operations has led to services being mainly developed on large- and middle-sized waterways. Opportunities to develop container barge transport on small waterways have been overlooked, and development has been discouraged by transport policies. The market share of container barge transport can be increased, but doing so would require a penetration into new geographical markets. Small waterways would play an important role in this effort. The possibility of developing and improving the competitiveness of container barge transport on small waterways is discussed, with attention given to the role of small vessels, adapted vessels, and revised network operations. Both technical and logistic innovations provide interesting opportunities to develop container barge transport on small waterways.
Future Utilization and Optimal Investment Strategy for Inland Waterways: New Model from U.S. Army Corps of Engineers to Assist Policy Makers
Authors: Langdon Virgil L. , Hilliard Michael R. , Busch Ingrid K.
Published: April 2007

For nearly three decades, the U.S. Army Corps of Engineers (the Corps) has been measuring incremental system navigation transportation costs for proposed infrastructure investments in search of the National Economic Development (NED) plan: local optimization in a system-level evaluation. The increasingly complex and sophisticated analysis requires the development of additional modeling modules. The traditional analysis assumed a most-likely traffic forecast and a set investment timing. Cost-benefit analyses on various alternatives were compared to determine the without-project condition and the recommended with-project NED plan. Sensitivity analyses of traffic forecasts and investment timing were done on the with-project plan. The second generation of analysis factored in the impacts of scheduled chamber closure differences between alternatives, and the third generation of analysis factored in the impacts of unscheduled ones. The goal is to be able to optimize investments simultaneously across a system (not just investments at one site) under a series of forecast scenarios while capturing structural reliability differences (scheduled and unscheduled closures). As the demands of the analysis increased, there was a need to consolidate and dynamically link the various models and techniques developed over the years and to develop new techniques to simultaneously manage investment permutations and automatically select optimal investment plans; the desire was to perform system optimization in a system-level evaluation. The innovative analysis techniques and relational database management structure of the new Ohio River Navigation Investment Model are introduced, as is a set of flexible, integrated analysis modules that move the Corps closer to these ideals.
Evaluation of Modified German Rotating Flask
Authors: Ramaiah Satish , D'Angelo John , Dongré Raj
Published: April 2007

The rolling thin film oven (RTFO) test has been found to be inadequate for aging polymer-modified binders. A modified German rotating flask (MGRF) was evaluated as a replacement for the RTFO aging method. Evaluation involved three phases by using a wide range of asphalt binders, primarily polymer-modified asphalt binders. Phase I was conducted to evaluate the effects of temperature and rotation speed on aging. Phase II identified off-the-shelf components to facilitate the assembly of MGRF. A fully functional, off-the-shelf MGRF was developed at the completion of Phase II. The cost of this equipment was approximately $3,500. Phase III was conducted to evaluate the effects of the MGRF aging procedure on a wide range of asphalt binders. In Phase III, a full range of binder physical properties was determined to grade all binders according to AASHTO M320 and MP1-a. The MGRF aging procedure did not significantly affect the performance grade of the asphalt binders studied. Therefore, from the available data, MGRF aging appears to be equivalent to RTFO. The advantage of using the MGRF is that it does not have the run-out problems faced by the modified binders in an RTFO oven.
Calibration of Microscopic Traffic Simulation Models with Aggregate Data
Authors: Toledo Tomer , Ben-Akiva Moshe E. , Darda Deepak , Jha Mithilesh , Koutsopoulos Haris N.
Published: April 2007

A framework for the calibration of microscopic traffic simulation models using aggregate data is presented. The framework takes into account the interactions between the various inputs and parameters of the simulator by estimating origin-destination (O-D) flows jointly with the behavioral parameters. An optimization-based approach is used for the joint calibration. Since the calibration of the parameters depends on the estimated O-D flows and vice versa, the proposed framework is iterative. O-D estimation is based on the well-known generalized least squares estimator. A systematic search approach based on the complex algorithm is adopted for calibration of the behavioral parameters. This algorithm is particularly useful for the problem at hand since it does not require calculations of derivatives of the objective function. The applicability of the approach is demonstrated through its application to case studies using MITSIMLab, a microscopic traffic simulation model.
Analysis of Distribution and Calibration of Car-Following Sensitivity Parameters in Microscopic Traffic Simulation Models
Authors: Schultz Grant G. , Rilett L. R.
Published: April 2007

The calibration of microscopic traffic simulation models has been a topic of increased attention in the transportation and traffic engineering profession. These calibration analyses have traditionally been concerned with identifying the "best" parameter set from a range of acceptable values. A methodology to introduce and calibrate a low parameter distribution is examined; it uses measures of central tendency and dispersion (i.e., mean and variance) to generate input parameters for car-following sensitivity factors in microscopic traffic simulation models. The approach is applied to IH-10 in Houston, Texas, with the CORSIM model and subsequently calibrated with an automated genetic algorithm methodology to examine the effectiveness of the distribution alternatives. An overview of car-following sensitivity parameters is provided, parameter distribution alternatives are outlined, and an application of the car-following distribution alternatives is discussed and compared with default distributions. The results of this analysis indicate that the distribution of car-following sensitivity parameters can be modeled in microscopic traffic simulation models and that with automated calibration methodologies such as genetic algorithms, the mean absolute error between simulated and observed traffic volume and travel time data can be minimized. The results further indicate that both lognormal and normal distribution alternatives are very effective at replicating observed conditions and representing the full distribution of car-following sensitivity factors from the calibration of the mean and variance of these parameters.
Calibration and Application of a Simulation-Based Dynamic Traffic Assignment Model
Authors: Mahut Michael , Florian Michael , Tremblay Nicolas , Campbell Mark , Patman David , McDaniel Zorana Krnic
Published: April 2007

The calibration and application of a simulation-based dynamic traffic assignment (DTA) model on a portion of the city of Calgary road network in Alberta, Canada, are discussed. The DTA model iteratively reassigns flow to paths by using the method of successive averages on the basis of travel times obtained with a traffic simulation model. The original subnetwork extracted from a regional planning model was enriched by a great increase in the number of zones. The DTA origin-destination matrix was estimated from an extensive database of turning movement counts via a trip generation/distribution model and a matrix adjustment algorithm. The network topology was enhanced by the addition of an interchange and a more precise representation of arterial intersections, including traffic signal control plans. A set of 1-h turning counts was used to calibrate the DTA model by adjusting local parameters such as gap-acceptance values, as well as global parameters such as average vehicle length. The final model results were compared with an independent set of 15-min turning movement counts. The resulting R2 values, which ranged from .91 to .96, lead to a high degree of confidence in the model results.
Development of a High-Level Algorithm Verification and Validation Procedure for Traffic Microsimulation Models
Authors: Reinke David , Dowling Richard , Hranac Robert , Alexiadis Vassilios
Published: April 2007

The successful acceptance of traffic microsimulation software depends crucially on the verification and validation (V&V) procedures for testing the core behavioral algorithms. These must be sufficient to convince researchers, software developers, and practitioners that the algorithms are accurate and robust. V&V procedures must also be well documented to ensure public acceptance. A suggested V&V procedure is presented. The central theme is that verification and validation are integral parts of the entire algorithm development process. A three-stage algorithm development and V&V procedure for traffic microsimulation algorithms is recommended. Algorithm development includes identifying key variables and setting model parameters. Next, the software implementation of the algorithm is tested during the algorithm-level testing stage with a combination of hypothetical and simple real-world data. Finally, systemlevel testing of the algorithm software is done within a complete microsimulation modeling system. In the last stage, the system with the new algorithm is tested against complex real-world data sets.
Traffic-Signal Group Relamping Model
Authors: Zwahlen Helmut T. , Russ Andrew , Vatan Şahika , Hirth Jessica , Greene Ken
Published: April 2007

A group relamping model was developed and evaluated by using bulb-replacement records from the Ohio Department of Transportation (ODOT) District 4 as a test case for a limited sensitivity analysis. The relatively easy-to-use Excel spreadsheet computes the costs of group relamping as a function of the relamping interval. The model shows a relatively shallow minimum region at about 10 months, with a minimized annual cost of $38,719 to ODOT District 4 for maintaining the bulbs on its 273 signalized intersections. Results will vary somewhat in other districts or states, but the software can be applied to those cases as well. One of the major tasks involved in using the model is the need to input the individual spot relamping distances, including those from the central maintenance facility to each signal and also the distances of travel to and within clusters of signalized intersections, where each cluster takes 1 day to relamp as a group. The other major difficulty is obtaining a bulb-failure curve to use as input; in this evaluation data for the GE-Real bulb were collected over a 2-year period in ODOT District 4. The intersections also need to be clustered before using the spreadsheet. The software will provide a table of overall traffic-signal maintenance cost on an annual basis as a function of the group relamping interval from 1 to 24 months, from which the group relamping interval with the minimum annual cost can be selected.
Estimates of Work Zone Exposure on the National Highway System in 2001
Authors: Ullman Gerald L. , Holick Andrew J. , Scriba Tracy A. , Turner Shawn M.
Published: April 2007

A comprehensive set of data on work zone exposure characteristics does not exist at the national level. Without accurate work zone exposure data, it is impossible to know whether changes in work zone performance measures (safety, congestion, public sentiment) over time are due to true changes in the characteristics of work zones or to changes in external factors. Presented are the results of a study exploring the quality and quantity of work zone data available in the United States. During this study, researchers collected data in five regions across the country. The regional data were then extrapolated to develop national estimates of several work zone exposure characteristics on the National Highway System (NHS) during 2001. Researchers examined constructionmanagement databases, traffic control plans, and project-inspector diaries on projects performed by private contractors in these regions during 2001. Researchers also gathered data on work zone activities that were performed directly by transportation agency in-house personnel in each of the regions. These data were then extrapolated to national estimates of several work zone exposure measures during the 2001 calendar year, including the percentage of NHS that experienced at least 1 day of work zone activity in 2001; length, duration, and frequency of activity in work zones on the NHS; impacts of work zones on available NHS roadway capacity; and vehicle exposure to active and inactive work zones on NHS during the year.
Prediction of Brine Application for Pretreatment and Anti-Icing
Authors: Mitchell Gayle F. , Hunt Christopher L. , Richardson Wallace
Published: April 2007

Highway anti-icing strives to prevent the ice—pavement bond by pre-application of chemicals. An effective anti-icing program requires prediction and estimation of the amount, type, and timing of chemicals needed for the expected precipitation event while compensating for time and traffic decay of the chemical on the highway surface. Development of a sodium chloride brine anti-icing methodology was accomplished with an extensive study of brine residual decay on four pavement types. In October and November 2002, brine residual was monitored for up to 3 days after initial application on five sections of four-lane divided highways in Ohio. Four evenly spaced test stations within each highway section were monitored for residual as time passed and traffic accumulated. An instrument that dissolves salt and measures conductivity was used to measure available salt residual. Efficacy of the brine to prevent ice—surface bonding was estimated by using freeze—thaw cycles of various brines. After freezing, the bonds were held vertically as temperature was raised. The appearance of liquid below the interface indicated release. Field and laboratory data were correlated to estimate freezing temperatures for various salt residuals as a function of brine dilution represented by precipitation in depth of rainfall. Results support estimation of brine application requirements for three specific pavements based on expected precipitation and the salt residual models developed in the study. A set of graphs is included to implement the algorithm.
Pilot Study of Speed-Recovery Duration as a Measure of Winter Maintenance Performance
Authors: Lee Chanyoung , Ran Bin
Published: April 2007

Many state and local governments in the United States are seeking improved methods of providing winter highway maintenance to meet the increasing demands of today's drivers. Winter maintenance activity can improve road conditions for travel in terms of mobility, safety, and economic benefit. The benefits and costs of winter maintenance make it very important that these activities be completed effectively and efficiently. To improve the effectiveness and the efficiency of winter maintenance activities, the performance of the approach taken must be measured. Winter maintenance performance measures were developed on the basis of speed data from automatic traffic recorders (ATRs) and winter storm report data. An attempt was made to combine the ATR speed data and the storm report data to determine both the average vehicle speed reduction during a snow event relative to normal vehicle speeds at a location and the time needed from the minimum value to regain normal or average vehicle speeds. A determination was made related to whether this speed-recovery duration might be an appropriate performance measure for winter maintenance.
Analytical Framework for Prioritizing Bicycle and Pedestrian Investments: New Jersey's Statewide Master Plan Update, Phase 2
Authors: Swords Andrew R. , Goldman Lois M. , Feldman William , Ehrlich Theodore F. , Bird William J.
Published: April 2007

Phase 2 of New Jersey's bicycle and pedestrian master plan is an innovative approach to quantify bicycle and pedestrian needs at the statewide level. In cooperation with New Jersey's three metropolitan planning organizations (MPOs), the New Jersey Department of Transportation developed the new master plan to provide guidance to policy makers and project sponsors on the most promising locations for future bicycle and pedestrian investment. Bicycle and pedestrian priorities are identified along the two dimensions of supply and demand, that is, the suitability of facilities and the potential for nonmotorized trip making in specific locations. In addition, the project includes New Jersey's first statewide inventory of existing and proposed bicycle facilities and geographic information systems (GIS) data on trip attractors such as schools, commercial areas, and transit stations. Although the master plan uses existing analysis methods mainly, it is unique in the way that it combines these methods interdependently and in conjunction with facilities and trip attractor inventories at a statewide level. The inventories and analyses use GIS to create user-friendly tools and to display results. Final products include lists of priority bicycle corridors and pedestrian locations, which are reviewed within the collaborative MPO planning forum. The lists and analyses will be used as sketch-planning tools to evaluate the need for bicycle and pedestrian improvements to existing highway projects and to develop new bicycle and pedestrian projects. Bicycle and pedestrian analysis approaches, role of GIS, and future research needs are discussed in detail.
Evaluation of Pedestrian Countdown Signals in Montgomery County, Maryland
Authors: Eccles Kimberly A. , Tao Ruihua , Mangum Bruce C.
Published: April 2007

Pedestrian countdown signals installed at five intersections in Montgomery County, Maryland, were evaluated with a before-and-after study. The effect of the countdown signals on pedestrian and motorist behavior was determined by observing the signal indication when pedestrians entered the intersection, the number of pedestrians remaining in the intersection at the release of conflicting traffic, conflicts between pedestrians and motor vehicles, and vehicle approach speeds to the intersections. On the basis of the observational study, the pedestrian countdown signals did not have a negative effect on pedestrian behavior. The vehicle speed observations found that pedestrian countdown signals had no effect on vehicle approach speeds during the pedestrian clearance interval (i.e., flashing "Don't Walk" indication). Pedestrian behavior observations found that although 2 of the 20 crosswalks experienced a statistically significant decrease in the number of pedestrians who entered on "Walk," 6 crosswalks experienced a significant increase. Additionally, none of the intersections had a significant increase in the number of phases with pedestrians remaining in the intersection at the release of conflicting traffic. The observational study of conflicts found a significant decrease in pedestrian-motor vehicle conflicts after the installation of the pedestrian countdown signals at four of the intersections at which conflicts were observed. A survey of pedestrians was also conducted. Results of the survey indicated that, generally, pedestrians are aware of the countdown signal and understand the countdown indication.
Methodology to Assess Design Features for Pedestrian and Bicyclist Crossings at Signalized Intersections
Authors: Steinma Norm , Hines David Keith
Published: April 2007

The Department of Transportation of the city of Charlotte, North Carolina, has developed a methodology to assess the important design features that affect pedestrians and bicyclists crossing signalized intersections. Referred to as level of service, this methodology identifies and evaluates features according to their influence on the comfort and safety of pedestrians and bicyclists. Among the key features identified and rated are crossing distance, roadway space allocation (i.e., crosswalks, bike lanes), corner radius dimension, and traffic signal characteristics. This methodology can be used as a diagnostic tool to assess and improve pedestrian and bicyclist levels of comfort and safety by modifying design and operational features of intersections. Results can be compared with those for traffic levels of service of an intersection and weighed according to user priorities. This methodology will be included in Charlotte's new street design guidelines and will be used to select design and operational features that can help achieve desired levels of service for pedestrians and bicyclists.
Space Syntax: Innovative Pedestrian Volume Modeling Tool for Pedestrian Safety
Authors: Raford Noah , Ragland David
Published: April 2007

An innovative pedestrian modeling technique known as Space Syntax is described. The technique was used to create estimates of pedestrian volumes for the city of Oakland, California. Pedestrian exposure rates were calculated, and a relative risk index for the city's first pedestrian master plan was created with those estimates. A major challenge facing planners, transportation engineers, and pedestrian-safety advocates is the lack of detailed, high-quality pedestrian-exposure data. Exposure is defined as the rate of contact with a potentially harmful agent or event. Pedestrian exposure is therefore defined as the rate of pedestrian contact with potentially harmful situations involving moving vehicles (e.g., crossing an intersection). Pedestrian risk is defined as the probability that a pedestrian-vehicle collision will occur, based on the rate of exposure. To estimate exposure, pedestrian volume measurements must be made, but such measurements are not easily obtainable. In the absence of accurate exposure data, pedestrian-safety decisions are often made by estimation, rule of thumb, or political influence and result in mixed and potentially less effective outcomes. The value of the Space Syntax volume-modeling approach for generating estimates of pedestrian exposure is explored with the city of Oakland as a case study. The method's theoretical background, data requirements, implementation, and results are discussed. It is suggested that the output of the model—citywide pedestrian volume estimates—is useful to pedestrians, planners, and transportation engineers. The value of the pedestrian-exposure concept for the planning professional is discussed.
Pedestrian Flow Modeling by Adaptive Control
Authors: Hoogendoorn Serge P.
Published: April 2007

Assessment tools for pedestrian walking speeds, comfort, and travel times are important for the planning and geometric design of infrastructural facilities under regular and safety-critical circumstances (evacuations). This contribution focuses on pedestrian walking behavior theory and modeling. It is assumed that pedestrians are adaptive controllers who minimize the subjective predicted cost of walking, given changing walking objectives and pedestrian attitudes. The theory asserts that pedestrians predict the behavior of other pedestrians on the basis of their observations and the assumed walking strategies of nearby pedestrians. The approach yields closed-form mathematical expressions predicting the acceleration and directional change of a pedestrian. It was found that the model was able to predict the behavior of pedestrians accurately (lane formation, walking positions, faster-is-slower effect, etc.), as shown by several application examples.
Logistic Model for Rating Urban Bicycle Route Safety
Authors: Allen-Munley Cheryl , Daniel Janice , Dhar Sunil
Published: April 2007

In response to renewed appreciation of the benefits of bicycling to the environment and public health, public officials across the nation are working to establish bicycle routes. During the past two decades a number of methods have been endorsed for the selection of "suitable" bicycle routes. These methods are limited in that they do not explicitly address bicycle safety nor do they reflect urban conditions. The purpose of this research is to develop an objective bicycle route safety rating model based on injury severity. The model development was conducted with a logistic transformation of bicycle crash data from Jersey City, New Jersey, for the period 1997 to 2000. The resulting model meets a 90% confidence level by using various operational and physical factors (traffic volume, lane width, population density, highway classification, and presence of vertical grades, one-way streets, and truck routes) to predict the severity of an injury that would result from a motor vehicle crash that occurred at a specific location. The modeled rating of the bicycle route's relative safety is defined as the expected value of the predicted injury severity. This rating is founded on the premise that safe routes produce less-severe crashes than do unsafe routes. The contribution of this research goes beyond the model's predictive capacity in comparing the safety of alternative routes by providing planners with an understanding, derived from objective data, of the factors that add to the route's safety, factors that reduce safety, and factors that are irrelevant.
Commute Rates on Urban Trails: Indicators from the 2000 Census
Authors: Morris Hugh
Published: April 2007

During the past 10 years the U.S. Department of Transportation has spent $3.9 billion on bicycle and pedestrian facilities through the Transportation Enhancements Program. These funds have been distributed to 11,456 projects. Of these funds $2.53 billion has been spent on off-road trails, for 6,537 projects. Many of these projects have been built, and the question of the degree to which these trails are being used for transportation can be asked. The term "transportation trip" means that a person riding a bicycle on a trail is headed for a destination, such as work, shopping, or school. To explore the question, a geographic information system-based analysis using the block-group level of journey-to-work data from the 2000 census was performed on 13 trails in urban areas. The research explores the overall bike-to-work rate for households in the county in which the trail is located and compares that rate with that of the subset of households that are within 0.5 mi of the trail. The hypothesis that households closer to the trail would have a greater bike-to-work rate is supported by the data in 9 of the 13 analyzed trails. For those 9 trails, households within 0.5 mi of the trail show an average bike-to-work rate of 1.55% as compared with the average of the whole county of 0.52% and a national average of 0.4%. Additionally, fully 25% of bike commuters in those counties live within 0.5 mi of the trail. Factors that influence bicycle commute rates on trails are also reviewed.
Characteristics of Emerging Road and Trail Users and Their Safety
Authors: Landis Bruce W. , Petritsch Theodore A. , Huang Herman F. , Do Ann Hong
Published: April 2007

In recent years the number of kick scooters, hand cycles, wheelchairs, and other emerging user types has increased on roads and shared use trails. FHWA recognized that because AASHTO's design recommendations are based on the characteristics of bicyclists, they may not adequately accommodate other users. Further, some emerging user groups have been petitioning state legislatures throughout the United States for legal access to public roads. Consequently, determining the operating and safety characteristics of these emerging users has become important for the safe accommodation of all nonmotorized users of the transportation system. Some of the findings of research undertaken to examine the characteristics of bicyclists and emerging users are reported. Three "Ride for Science" data collection events were conducted to obtain the physical dimensions, turning capabilities, acceleration, speed, lateral operating space, and stopping sight distance of trail users. Results show that there is great diversity in the operating characteristics of various road and trail user types. AASHTO's design bicycle length of 6 ft and width of 30 in. were adequate for the majority of observed users. However, bicycle trailers and recumbent bicycles exceeded the design length. Power wheelchairs exceeded the design width. The recommended two-way trail width of 10 ft gave most users traveling single file in opposite directions enough room to pass each other, though some only barely. Results of this research will be valuable in either updating or developing new design guidelines for road and shared use path design to better accommodate emerging user groups.
Investigation of Extraction, Transformation, and Loading Techniques for Traffic Data Warehouses
Authors: Smith Brian L. , Babiceanu Simona
Published: April 2007

Archived data management systems (ADMSs) are data warehouses created to support analyses that are based on data collected by transportation operations systems. Whereas many believe that an ADMS can be created by simply exporting data from an operations system, experience in developing the Virginia ADMS illustrates that the creation of an effective ADMS requires careful attention to the extraction, transformation, and loading (ETL) process. This process refers to the activities conducted when a data warehouse is created from an operational data store. Four critical elements of an ADMS ETL process are addressed: data aggregation, data quality assessment, data imputation, and data characterization. For each element the purpose and need are documented, a review of available alternative implementation methods is presented, and, finally, a description of the approach used in the Virginia ADMS is detailed.
Hybrid Model-Based and Memory-Based Traffic Prediction System
Authors: Alecsandru Ciprian , Ishak Sherif
Published: April 2007

Short-term traffic forecasting capabilities on freeways and major arterials have received special attention in the past decade primarily because of their vital role in supporting various traveler trip decisions and traffic management functions. A hybrid model-based and memory-based methodology used to improve freeway traffic prediction performance is presented. The proposed methodology integrates both approaches to strengthen predictions under both recurrent and nonrecurrent conditions. The model-based approach relies on a combination of static and dynamic neural network architectures to achieve optimal prediction performance under various input and traffic condition settings. Concurrently, the memory-based component is derived from the data archival system that encodes the commuters' travel experience in the past. The outcomes of the two approaches are two prediction values for each query case. The two values are subsequently processed by a prediction query manager, which ultimately produces one final prediction value by using an error-based decision algorithm. It was found that the hybrid approach produced speed estimates with smaller errors than those produced when the two approaches were used separately. The proposed prediction approach could be used to derive travel times more reliably for advanced traveler information systems applications.
Modal Emissions Model for Heavy-Duty Diesel Vehicles
Authors: Barth Matthew , Scora George , Younglove Theodore
Published: April 2007

There have been significant improvements in recent years in transportation and emissions modeling to allow better evaluations of transportation operational effects and associated vehicle emissions. In particular, instantaneous or modal emissions models have been developed for a variety of light-duty vehicles. To date, most of the effort has focused primarily on developing these models for light-duty vehicles with less effort devoted to heavy-duty diesel (HDD) vehicles. Although HDD vehicles currently make up only a fraction of the total vehicle population, they are major contributors to the emissions inventory. A description is provided of an HDD truck model that is part of a larger comprehensive modal emissions modeling (CMEM) program developed at the University of California (UC), Riverside. Several HDD truck submodels have been developed in the CMEM framework, each corresponding to a distinctive vehicle-technology category. The developed models use a parameterized physical approach in which the entire emission process is broken down into different components that correspond to physical phenomena associated with vehicle operation and emission production. A variety of trucks were extensively tested under a wide range of operating conditions at UC Riverside's Mobile Emissions Research Laboratory. The collected data were then used to calibrate the HDD models. Particular care was taken to investigate and implement the effects of varying grade and the use of variable fuel injection strategies. Results show good estimates for fuel use and the regulated emission species including nitrogen oxides, one of the key targets for HDD vehicles.
Microframework for Modeling of High-Emitting Vehicles
Authors: Ahn Kyoungho , Rakha Hesham , Trani Antonio
Published: April 2007

High emitters represent a small fraction of the vehicle fleet, yet they are responsible for a large portion of the total mobile source emissions. Drive-cycle-specific high-emitter cut points for the identification of high-emitter vehicles are first developed. A microscopic model for estimating high-emitter vehicle emissions by using second-by-second emission data is developed subsequently. The proposed model estimates vehicle emissions with a margin of error of 10% when compared with in-laboratory bag emission measurements. The model was incorporated in the INTEGRATION traffic assignment and simulation software for the environmental assessment of alternative traffic operational projects, including emerging intelligent transportation system initiatives.
Particulate Matter 2.5: Next Challenge for Transportation Conformity
Authors: Makler Jonathan
Published: April 2007

For transportation planners, the promulgation of a new national ambient air quality standard for 2.5-micron particulate matter (PM2.5) in July 1997 will culminate approximately in December 2005. That is the time, one year after the expected date for designation of new PM2.5 nonattainment areas, when conformity determinations corresponding to the new standard will be due. Because PM2.5 is significantly different from pollutants with which most transportation planners have had experience (ozone and its associated precursors), this discussion attempts to present a useful explanation of PM2.5 science, the role and contribution of mobile source emissions, the types of probable control measures, and, most important, the implications of this for transportation planning. Although only 10% of PM2.5 emissions come from on-road mobile sources, nonattainment status and the transportation conformity requirement in particular will have specific implications for transportation planners. Representatives of prospective nonattainment areas, especially those without previous experience with nonattainment or conformity, may benefit from several recommendations for preparatory efforts drawn from the experiences of conformity veterans around the country.
Application of Small Sampling Approach to Estimating Vehicle Mileage Accumulations for Beijing
Authors: Yang Fang , Yu Lei , Song Guohua , Wang Lishui
Published: April 2007

The MOBILE emission factor model (the newest version MOBILE6) has been widely used in China to estimate its mobile source emissions. Because MOBILE was developed in the United States, most of its default input parameters represent the average traffic characteristics and environmental conditions of the United States. Hence, it is necessary to adjust the values of the input parameters of MOBILE to accommodate local conditions and improve the accuracy of the emission estimation in China. An application is presented of the small sampling approach to adjusting the default mileage accumulation rates (MARs) for Beijing. A small-sized survey was conducted in Beijing to collect the mileage information. The adjustment factors for the MARs were then generated by using the small sampling approach for a variety of vehicle types. Finally, the MOBILE emission factors were generated by using the adjusted MARs. Results show that the emission factors generated by adjusted local mileage accumulation rates are significantly different from those generated by the default rates.