Grant G Schultz

Calibration of "Highway Safety Manual" Safety Performance Function: Development of New Models for Rural Two-Lane Two-Way Highways

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.

Safety Impacts of Access Management Techniques in Utah

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.

Relationship between Access Management and Other Physical Roadway Characteristics and Safety

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 severity. Furthermore, land use was identified to play a significant role in the safety of arterial roadways as arterial roadway segments with adjacent commercial land use tended to have higher crash rates and severity.

Analyzing Raised Median Safety Impacts Using Bayesian Methods

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.

Prioritizing Access Management Implementation

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.

Calibration of Distributions of Commercial Motor Vehicles in CORSIM

One of the most critical aspects of effective microscopic traffic simulation models is proper calibration for accurate replication of both supply and demand characteristics, as well as their interaction. Recent research has begun automating the calibration process by using intelligent transportation system data. This research, however, has targeted automobile traffic and has not generally included commercial motor vehicle (CMV) impacts. Because CMVs are a significant part of the traffic stream and tend to have a disproportionate effect on the transportation system, it is theorized that these vehicles should be included in the calibration process. The objective of this research, therefore, is (a) to outline calibration parameters and network properties available (including site-specific vehicle distributions with weigh-in-motion and automatic vehicle classification data) for a freeway simulation of both passenger cars and CMVs and (b) to apply these parameters and network properties on an urban freeway sys...

Investigating the safety impact of roadway network features of suburban arterials in Shanghai

With rapid changes in land use development along suburban arterials in Shanghai, there is a corresponding increase in traffic demand on these arterials. To accommodate the local traffic needs of high accessibility and efficiency, an increased number of signalized intersections and accesses have been installed. However, the absence of a defined hierarchical road network, together with irregular signal spacing and access density, tends to deteriorate arterial safety. Previous studies on arterial safety were generally based on a single type of road entity, either intersection or roadway segment, and they analyzed the safety contributing factors (e.g. signal density and access density) on only that type of road entity, while these suburban arterial characteristics could significantly influence the safety performance of both intersections and roadway segments. Macro-level safety modeling was usually applied to investigate the relationships between zonal crash frequencies and demographics, road network features, and traffic characteristics, but the previous researchers did not consider the specific arterial characteristics of signal density and access density. In this study, a new modeling strategy was proposed to analyze the safety impacts of zonal roadway network features (i.e., road network patterns and road network density) along with the suburban arterial characteristics of signal density and access density. Bayesian Conditional Autoregressive Poisson Log-normal models were developed for suburban arterials in 173 traffic analysis zones in the suburban area of Shanghai. Results identified that the grid pattern road network with collector roads parallel to arterials was associated with fewer crashes than networks without parallel collectors. On the other hand, lower road network density, higher signal density and higher access density tended to increase the crash occurrence on suburban arterials.

Advance Warning Signals: Long-Term Monitoring Results

A driver approaching a signalized intersection at which the light has turned yellow must make a decision whether to stop or proceed. A signal that is properly timed will generally provide an opportunity for a safe and legal maneuver. As approach speeds increase, however, executing a safe maneuver becomes more difficult. One countermeasure used to provide advance warning of an approaching intersection or an impending signal change at such an intersection is an advance warning signal (AWS). Several AWS systems have been installed throughout the United States, including four in Utah. The effectiveness of the Utah systems has been evaluated as a function of intersection safety by using crash history, speed distribution, and red-light running (RLR) metrics. The results of the research suggest that the contribution of the AWS systems to the safety and operation of the intersections can be interpreted as both positive and negative. The AWS systems have helped to maintain higher operating speeds and may also have improved capacity when vehicles do not need to stop. Meanwhile, speeds have been reduced in the time just before the onset of the yellow interval. However, the additional information provided to drivers may have encouraged some drivers to attempt to beat the light, as evidenced by an increase in RLR even with shortening of the lead flash time. The increase in RLR, however, has not led to an increase in the overall crash frequency or crash rate at these intersections.

Making the Most of an Existing System Through Access Management at Major Arterial Intersections

The intersections of major arterials are designed to facilitate the conflicting movements of numerous vehicles in a manner that is both safe and efficient. Accesses located within the functional area of major arterial intersections complicate intersection activity because additional conflicts arise from ingressing and egressing movements at the accesses. This research analyzed the impact of accesses on crashes within the functional area of major arterials. The effects of access spacing within functional areas and access setback from intersections were addressed. The functional areas of 144 signalized major arterial intersections across the state of Utah were examined. A database was developed and contained the frequency, type, and severity of functional area crashes as well as the intersection and roadway characteristics within the functional area. Statistical analyses were conducted to determine the influence of accesses on crashes within the functional area of intersections. The statistical analyses showed that the existence of accesses within the functional area was correlated with increased crashes and crash severity costs. In particular, an increase in commercial access density was associated with increases in crash totals, crash rates, and rear-end crashes in intersection functional areas. The analyses also showed that study intersections meeting Utah Department of Transportation corner clearance standards exhibited fewer right-angle crashes and lower crash severity costs. Adherence to such standards improves safety and increases efficiency of the transportation network and thus aids jurisdictions throughout the nation in making the most of the existing infrastructure.

Heuristic Approach to Identifying Horizontal Curves and Their Parameters Given Lidar Point Cloud Data

Information on the location and characteristics of highways has many applications to highway engineering, such as highway safety analysis, asset management, and highway improvement planning. However, the task of creating an inventory of highway curves in a state is a daunting task, which cannot be done efficiently by field visits. The alternative approach that processes light detection and ranging or GPS data sets to identify highway curves has shown promise as a more efficient method but has also proved to be a difficult task. This paper presents a procedure for curve detection and analysis and also examines the success rate for identification and classification of those curves identified by this method. The basic process began with the roadway divided into segments, each with assigned attributes. The segments with similar attributes were combined into larger sections, each classified as either a curve or a tangent. Segments that were too short to be a true curve were removed. The heuristic analysis used to optimize threshold values for the analysis of these curves was also discussed. It was found that the curve identification success rate of this process, depending on calibration, ranged from 84.4% to 92.9% accuracy (e.g., the segment identified correctly as a curve or tangent), and curve geometries (e.g., points of curvature or points of tangency location correctly found) could be expected to have an accuracy rate of 78.7% to 89.9%.