Search

This simulator experiment compares driver behavior in the Dilemma Zone (DZ) on a 4-lane divided highway using three types of warnings of impending traffic signal end of green to no advance warning (control). The DZ occurs when onset of a yellow signal occurs at a temporal interval before an intersection such that stopping or proceeding through the intersection has roughly equal perceived risk. Two of the systems allowed lane specific warnings and one did not. Sixty-nine participants drove a total of 45 minutes in the right lane of on a multilane highway with 36 intersections. On approach to 10 of the intersections, participants were placed in the DZ. For 6 other intersections drivers (still in the right lane) were exposed to a warning not intended for them but for a driver behind them in the left lane. Participants in all warning conditions received warnings 1.5 s or 3.0 s in advance of the end of green. Drivers in all of the advanced warning conditions stopped at the DZ intersections significantly more often than control condition drivers. When stopping at intersections, drivers given an advanced warning decelerated more gradually than those that had no warning. One exception was when drivers misinterpreted the left lane warning as intended for them and therefore decelerated rapidly to stop at the intersection.

High-speed signalized intersections present a grave hazard to the traveling public. An important component of this hazard is variation in the process of deciding whether to stop or proceed that occurs in the dilemma zone. To mitigate the dilemma zone problem, an innovative vehicle-specific detection, control, and warning system (DCWS) is being developed. To reduce dilemma zone conflicts, DCWS uses detection of individual vehicle speeds to provide unique, speed-specific dilemma zone protection for each vehicle as it approaches a signalized intersection. Although protecting all vehicles would be ideal, under some situations such protection is not possible. To account for these situations, DCWS also uses a vehicle-specific in-pavement system to give advance warning to drivers who are going to be trapped in the dilemma zone. With hardware-in-the-loop simulations, the new DCWS outperforms conventional dilemma zone warning systems in terms of the number of vehicles in the dilemma zone, the number and percentage of vehicles requiring warning, and the number of warning events per hour.

Horizontal curves have been identified as a target area for improving safety on rural two-lane highways in Texas. This study involved the development of multinomial logit models to assess driver injury severity resulting from single-vehicle crashes on such roads. Likelihood ratio tests warranted the development of separate injury severity models for curves of small, medium, and large radius. Various driver, vehicle, roadway, and environmental characteristics were found to affect injury severity among the 10,029 crashes analyzed. Run-off-the-road crashes, particularly those resulting in collisions with roadside objects, were found to increase injury severity significantly. Females were more likely to sustain injury and older drivers to be critically injured, particularly on curves of smaller radius. Various driver actions and behaviors were also significant determinants of injury severity. Unbelted drivers were up to 10 times more likely to suffer fatal injuries, and drivers who were uninsured, fatigued, or under the influence of drugs or alcohol were more likely to be seriously injured. Several of these behavioral factors were more pronounced on sharper curves.

The research on the effects of roadway geometry on truck crashes is relatively limited in comparison with predictive models developed for total vehicle crashes. The most common predictive models currently used are Poisson and negative binomial models. This study uses a negative binomial model but applies the full Bayes’ methods for improving model performance. To use Bayes’ methods successfully, a learning process was used to develop a final model, which was then compared with a separate validation data set to verify its accuracy. The data set used for this study is based on rural two-lane collector and arterial horizontal curves in Ohio, comprising 15,390 observations from crash records between 2002 through 2006. Specific areas of interest in this study include the impact of shoulder width, horizontal curve radius, curve length, and other traffic parameters. The final results indicate a significant increase in truck crashes due to both horizontal curvature and passenger vehicle volumes. The final model's predictions were improved compared with the initial model, indicating that the learning process is a viable tool for future crash model development.

The problem of red light running is widespread and growing; its cost to society is significant. However, the literature is void of quantitative guidelines that can be used to identify and treat problem locations. Moreover, there has been concern voiced over the validity of various methods used to identify problem locations, especially when automated enforcement is being considered. This paper documents the development of a procedure for identifying and ranking intersection approaches with the potential for improvement in the area of crashes related to red lights. One component of this procedure is a safety prediction model. A sensitivity analysis of this model indicates that red light–related crashes decrease with an increase in duration of the yellow interval and a reduction in the speed limit.

An innovative detection–control system was developed for the Texas Department of Transportation to reduce both delay and crash frequency at rural intersections. This system was implemented at several intersections in Texas, and its safety and operational benefits were evaluated. This report documents findings and conclusions reached after a 3-year implementation project. The detection–control system was installed and evaluated at each of five intersections in Texas during the 3-year period. Evaluation of before-and-after data indicates that the new detection–control system was able to reduce approach delay by 14%, stop frequency by 9%, red light violations by 58%, heavy-vehicle red light violations by 80%, and severe crash frequency by 39%.

This paper describes a research effort to determine the time into red of 63 red light–related crashes. From these 63 crashes, the relationship of time into red and the red light–related crash type is explored, as are relationships to other factors. From the red light–related crashes investigated, it was found that red light–related crash type was related to time into red. Other factors were not found to be related to time into red, although the sample size and selection method prevented any definitive findings. A brief discussion of the possible safety effectiveness of the all-red interval is also included. The time into red of red light–related crashes is related to the time into red of red light violations, so a characterization of red light violations and crashes is provided, along with suggested red light violation countermeasure classifications for each type of red light violation.

A procedure that can be used to compare a variety of common interchange types or make decisions about their design is described. The technique is based on the critical movement analysis approach traditionally used for signalized intersection analysis. This approach defines the rules for quantifying the sum of critical flow ratios for various interchange types. The concept of interchange delay is defined, and an equation for quantifying it is described. Simulation data are used to calibrate a series of models that relate the sum of critical flow ratio to interchange delay. A procedure that describes how these models can be used to obtain a quick estimate of the delay associated with a particular interchange type, given specific volume levels, lane assignments, and ramp separation distances, is documented.