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.

In the past, one of the primary focus areas for access management research has been on the physical characteristics of a roadway (i.e., signal spacing, unsignalized access spacing, and median openings) and their associated safety benefits. Although the literature has documented these characteristics as a function of safety, previous research has not investigated the specific relationships between the various other physical characteristics of the arterial roadway network and safety. The objective of this research was to examine the relationships between physical characteristics of the arterial roadway network (including access management related characteristics) and safety. Additionally, a process whereby these relationships could be identified not only for crash rates, but for collision type and crash severity (as a function of crash frequency) was developed. Statistical analyses showed that the specific access management related characteristics were positively related with increased crash rate and severi...

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.

Because traffic safety studies are not performed in a controlled environment such as a laboratory, but rather in an uncontrolled real-world setting, traditional analysis methods often lack the capability to evaluate the effectiveness of roadway safety measures adequately. In recent years, however, advanced statistical methods have been used in traffic safety studies to determine the effectiveness of such measures more accurately. These methods, especially Bayesian statistical techniques, can account for the shortcomings of traditional methods. Hierarchical Bayesian modeling is a powerful tool for expressing rich statistical models that more fully reflect a given problem than traditional safety evaluation methods could. This paper uses a hierarchical Bayesian model to analyze the effectiveness of raised medians on overall and severe crash frequency in Utah by determining the effect each newly installed median has on crash frequency and frequency of severe crashes at study sites before and after installation of the medians. Several sites at which raised medians have been installed in the past 10 years were evaluated with available crash data. The results show that the installation of a raised median is an effective technique to reduce the overall crash frequency and frequency of severe crashes on Utah roadways, with results showing a reduction in overall crash frequency of 39% and frequency of severe crashes of 44% along corridors where raised medians were installed. The results also show that hierarchical Bayesian modeling is a useful method for evaluating effectiveness of roadway safety measures.

Traffic volumes and congestion continue to increase on arterial roads. Safety and performance on those roads are continual concerns. Transportation systems must be evaluated on an ongoing basis to ensure that people and goods can be moved as efficiently and safely as possible. Safety and performance indices provide a method to numerically measure given data about a system so that comparisons and rankings on safety and performance can be made as objectively as possible. One of the sets of tools that have proved successful in improving the safety and efficiency of arterial roads are access management techniques. To determine which roads can most benefit from access management techniques, a prioritization process was developed to guide decision makers in the implementation process. Recommendations were given in the form of a decision tree classifying existing or future road segments into subcategories based on volume, signal spacing, adjacent land use, and other criteria. The objective of this paper is to document the steps followed to develop a performance index-based prioritization process to target arterial roads that would benefit from the implementation of access management techniques. Using the results of the research, decision makers can better determine which sections of roadway may benefit from controlling driveway access, installing raised medians, providing future planning, or looking to a solution other than access management.

Over the past few years, the Utah Department of Transportation has developed the signal performance metrics (SPMs) system to evaluate the performance of signalized intersections dynamically. This system currently provides data summaries for several performance measures, one of them being turning movement counts collected by microwave sensors. As this system became public, there was a need to evaluate the accuracy of the data placed on the SPMs. A large-scale data collection was carried out to meet this need. Vehicles in the Hi-resolution data from microwave sensors were matched with the vehicles by ground-truth volume count data. Matching vehicles from the microwave sensor data and the ground-truth data manually collected required significant effort. A spreadsheet-based data analysis procedure was developed to carry out the task. A mixed model analysis of variance was used to analyze the effects of the factors considered on turning volume count accuracy. The analysis found that approach volume level and number of approach lanes would have significant effect on the accuracy of turning volume counts but the location of the sensors did not significantly affect the accuracy of turning volume counts. In addition, it was found that the location of lanes in relation to the sensor did not significantly affect the accuracy of lane-by-lane volume counts. This indicated that accuracy analysis could be performed by using total approach volumes without comparing specific turning counts, that is, left-turn, through and right-turn movements. In general, the accuracy of approach volume counts collected by microwave sensors were within the margin of error that traffic engineers could accept. The procedure taken to perform the analysis and a summary of accuracy of volume counts for the factor combinations considered are presented in this paper