Laurence R. Rilett’s research while affiliated with Auburn University and other places

Highway-rail grade crossing (HRGC) safety is one of the priority areas in the United States transportation system that requires for greater research efforts not just limited to crash analysis, but also to gain a deeper understanding of surrogate safety measures such as driver behavior-based traffic violations at HRGCs. This paper uses vehicle profile data to identify the key variables and develop prediction models for gate violations and examine the relationship between model accuracy and the key input variables. A data set of 256 vehicle-train events was collected at two HRGC testbeds in Lincoln, Nebraska. Among them, 76 events are gate violations, and 180 events are non-violations. Two tree-based ensemble techniques, the bootstrap forest and the boosted tree, were applied to the data set. It was found that once a vehicle is within 190 feet from the HRGC stop line, the model was approximately 80 percent accurate in predicting a gate violation. It was also found that as vehicles came closer to the HRGC, the prediction error decreased. With the advent of vehicle profile data collection, tree-based ensemble techniques are ideal for safety studies as they can utilize the highly non-linear vehicle profiles and relate these to safety surrogate metrics.

Work zones pose mobility issues to the traveling public and safety challenges to travelers and road maintenance workers. These safety and mobility issues may be exacerbated by the presence of heavy vehicles. Connected and automated vehicle (CAV) technologies have been identified as a potential solution for these issues. This paper investigates the operational impacts of connected and automated heavy vehicles (CAHV) on freeway work zone operations on interstate highways. A microsimulation model, calibrated to empirical work zone field data, was used to study the operational impacts of CAHV platoons under various work zone and traffic conditions. It was found that, as the CAHV market penetration rate increases, the average work zone delay and queue length decreases. In addition, as the demand and heavy vehicle percentage increases, so do the benefits of using CAHV technology. For example, it was found that, when all heavy vehicles are classified as CAHV, the average flow rate is approximately 67% higher, and the maximum queue size and average delay decrease by approximately 97%. The methodology used in this paper will help transportation agencies as they design work zones to accommodate heavy vehicles equipped with CAV technologies.

Lane closure on a two-lane work zone can negatively affect operational performance. Although a microsimulation model is often used to quantify and predict these negative impacts, it requires proper calibration to produce meaningful results. The sixth edition of the Highway Capacity Manual (HCM-6) proposed a microsimulation model using limited empirical data from King County, Washington. Based on the authors’ knowledge, this paper is the first to examine the applicability of the HCM-6 two-lane work zone model in a different geographical area. A preliminary application of the HCM-6 model to two test sites in Nebraska found that the HCM-6 estimation of the mean headways and travel times were statistically different from observed data at the 5% significance level. Therefore, this paper proposed an automatic microsimulation calibration methodology for identifying parameters that can match the distribution or the mean value of observed traffic data. To the best of the authors’ knowledge, this is the first paper to show that a two-lane work zone microsimulation model calibrated using the empirical distributions of traffic measures can replicate the corresponding distributions at the 5% significance level. However, if the model was calibrated using the mean value of traffic measures, it could not replicate empirical distributions. This model was also validated using field data not used for calibration. The methodology proposed in this paper will benefit those who design and operate work zones because traffic agencies are interested in the variety of traffic conditions, not just the average. This paper concludes with a discussion on model transferability.

This paper develops a microsimulation-based methodology to analyze the design and operations of arterial roadway corridors, commonly known as entry control facilities (ECF), at Department of Defense (DOD) installations. These facilities serve as a means of ingress and egress to the installations and provide the first level of security. ECFs are relatively expensive to construct, averaging $12 million; therefore, it is imperative to design and operate them efficiently. Current practice is to use a simplified deterministic, macroscopic methodology when designing the physical layout (e.g., number of lanes, length of arterial, etc.) as well as the operations (e.g., single and tandem processing, etc.) of the ECF. This paper will develop a simulation-based methodology that is better adapted for capturing the intricacies of ECF design and operations. The paper proposes a general simulation-based methodology that affords ECF designers the opportunity to make realistic trade-offs between construction costs and operation costs (e.g., personnel, travel time, delay, etc.). A test case at Fort Gordon, Georgia using the VISSIM TM 2020 simulation software is used to illustrate the methodology. A variety of geometric and operational strategies were examined, and it was found that the six-lane configuration operating with tandem processing gave the best results. The improvements in delay and queue length were statistically significant compared with the other alternatives. In summary, the proposed methodology introduces a viable means to simulate real-world traffic conditions at ECFs. It is hypothesized that the methodology developed in this paper will be a valuable tool for the design and operation of ECFs.

Intelligent work zones have been widely adopted in the United States because they have been proven to improve traffic safety and operations. One specific intelligent work zone system, known as automatic queue detection (AQD), is designed to measure work zone-related queueing in real time, and inform drivers upstream so they may be prepared to slow down or stop. This paper describes an evaluation of the performance and efficacy of four AQD systems implemented at work zones on Interstate 80 in Nebraska. Specifically, (i) the system performance was verified by examining whether the messages displayed on the portable dynamic message signs (PDMS) were consistent with the underlying AQD logic, and (ii) the system efficacy was measured by determining whether the overall speeds of individual vehicles and the space mean speed (SMS) were reduced when warning messages were provided. It was found that the AQD systems were functioning well as evidenced by an error rate of 0.7 to 2.3%. It was concluded that the SMS was reduced in response to the PDMS warning display indicating that there was slow or stopped traffic ahead. The decrease in SMS was found to be statistically significant and in the range of 3.5 to 7 mph. This was approximately 47% greater than the reduction in SMS that occurred when the PDMS did not display any message. In summary, it was found that the AQD systems were operating correctly and, more importantly, they were effective in reducing the speeds of the traffic stream downstream of the PDMS.