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.

This paper documents the calibration of the Highway Safety Manual (HSM) safety performance function (SPF) for rural two-lane two-way roadway segments in Utah and the development of new SPFs through negative binomial regression. Crash data from 2005 to 2007 on 157 selected study segments in Utah provided a 3-year frequency of observed crashes to calibrate the HSM SPF and develop new models. The calibration factor for the HSM SPF for rural two-lane two-way roads in Utah is 1.16, indicating that the original HSM model under predicts crashes in Utah. The HSM suggests that jurisdiction-specific SPFs may predict crashes with greater reliability than calibrated SPFs. The following variables were significant in each of the four models developed by this research: annual average daily traffic (AADT), segment length, speed limit, and the percentage of AADT composed of multiple-unit trucks. AADT and segment length are used in the HSM SPF; speed limit and the percentage of AADT composed of multiple-unit trucks were found to correlate significantly with observed crash frequencies. The fourth negative binomial model developed in the study would be the best SPF to predict crashes on rural highways in Utah. As encouraged by the HSM and contemporary research, the empirical Bayes method can be applied with each jurisdiction-specific SPF because the analysis provided an overdispersion parameter for each model.

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As urbanization accelerates in Shanghai, land continues to develop along suburban arterials which results in more access points along the roadways and more congested suburban arterials; all these changes have led to deterioration in traffic safety. In-depth safety analysis is needed to understand the relationship between roadway geometric design, access features, traffic characteristics, and safety. This study examined 161 road segments (each between two adjacent signalized intersections) of eight suburban arterials in Shanghai. Information on signal spacing, geometric design, access features, traffic characteristics, and surrounding area types were collected. The effect of these factors on total crash occurrence was investigated. To account for the hierarchical data structure, hierarchical Bayesian models were developed for total crashes. To identify diverse effects on different crash injury severity, the total crashes were separated into minor injury and severe injury crashes. Bivariate hierarchical Bayesian models were developed for minor injury and severe injury to account for the correlation among different severity levels. The modeling results show that the density of signal spacing along arterials has a significant influence on minor injury, severe injury, and total crash frequencies. The non-uniform signal spacing has a significant impact on the occurrence of minor injury crashes. At the segment-level, higher frequencies of minor injury, severe injury, and total crashes tend to occur for the segments with curves, those with a higher density of access points, those with a higher percentage of heavy vehicles, and those in inner suburban areas. This study is useful for applications such as related engineering safety improvements and making access management policy.

Traffic volumes and congestion across Utah have continued to increase in recent years, particularly on arterial streets. This increased traffic volume has amplified the emphasis on implementing access management techniques (i.e., raised medians or driveway consolidation) to alleviate some of the safety concerns associated with access on arterial streets. To determine the safety benefits provided by access management techniques in Utah, an evaluation of the safety performance of arterials in which access management techniques have been implemented within the state was performed. To complete the evaluation, a unique, yet proven, tool available through the Utah Department of Transportation was used. This tool is a geographic information system–enabled, web-delivered data almanac that allows researchers to establish specific filters that can be used to sort crash data, identifying high crash locations and establishing crash trends. Several locations where access management techniques have been implemented in Utah were selected for the safety analysis. Although crash rates were not reduced in every case as a result of the access management techniques, other safety improvements were observed. For example, the access management techniques generally reduced the more serious collision types; this resulted in a decrease in the crash severity. Because the overall severity of crashes decreased, the overall economic cost of crashes was reduced. The cost of installing the access management techniques was more than offset by this reduction in the cost of crashes.