Bruce Hellinga

Real-Time Crash Prediction Model for Application to Crash Prevention in Freeway Traffic

The likelihood of a crash or crash potential is significantly affected by the short-term turbulence of traffic flow. For this reason, crash potential must be estimated on a real-time basis by monitoring the current traffic condition. In this regard, a probabilistic real-time crash prediction model relating crash potential to various traffic flow characteristics that lead to crash occurrence, or “crash precursors,” was developed. In the development of the previous model, however, several assumptions were made that had not been clearly verified from either theoretical or empirical perspectives. Therefore, the objectives of the present study were to (a) suggest the rational methods by which the crash precursors included in the model can be determined on the basis of experimental results and (b) test the performance of the modified crash prediction model. The study found that crash precursors can be determined in an objective manner, eliminating a characteristic of the previous model, in which the model results were dependent on analysts’ subjective categorization of crash precursors.

Analysis of Crash Precursors on Instrumented Freeways

Traffic flow characteristics that lead to crashes on urban freeways are examined. Since these characteristics are observed prior to crash occurrence, they are referred to as “crash precursors.” The objectives are (a) to explore factors contributing to changes in crash rate for individual vehicles traveling over an urban freeway and (b) to develop a probabilistic model relating significant crash precursors to changes in crash potential. The data used to examine crash precursors were extracted from 38 loop detector stations on a 10-km stretch of the Gardiner Expressway in Toronto for a 13-month period. An aggregate log-linear model was developed relating crash rates to the selected crash precursors observed upstream of the crash site. The results of this analysis suggest that the variation of speed and traffic density are statistically significant predictors of crash frequency after controlling for road geometry, weather, and time of day. With the model, crash potential can be established based on the precursors obtained from real-time traffic data.

Reducing bias in probe-based arterial link travel time estimates

Advanced traveler information systems and advanced traffic management systems require the ability to obtain accurate estimates of travel times within signalized networks. Probe vehicles have been suggested as a means of obtaining these travel times, but previous research has shown that bias in arrival time distributions of probe vehicles will lead to a systematic bias in the sample estimate of the mean. This paper proposes a methodology, based on stratified sampling techniques, for reducing the effect of this bias. The arrival time distribution of all vehicles, obtained from a traffic surveillance method such as an in-road loop detector, is used to weight each probe travel time report. Simulation results for a single intersection approach and for an arterial corridor illustrate the effectiveness of this method. The results for the single intersection approach indicate a correlation between the biased estimate and the population mean of 0.61, and an improved correlation between the proposed estimation method and the population mean of 0.81. Application of the proposed method to the arterial corridor resulted in a reduction in the mean travel time error of approximately 50%. The proposed method is easy to implement in field conditions and is shown to represent an improvement over traditional biased methods.

Variable Speed Limits: Safety and Operational Impacts of a Candidate Control Strategy for Freeway Applications

Variable-speed limit sign (VSLS) systems enable transportation managers to dynamically change the posted speed limit in response to prevailing traffic and/or weather conditions. Although VSLSs have been implemented in a limited number of jurisdictions throughout the world, there is currently very limited documentation that describes quantitative safety and operational impacts. Furthermore, the impacts reported are primarily from systems in Europe and may not be directly transferable to other jurisdictions such as North America. This paper presents the results of an evaluation of a candidate VSLS system for an urban freeway in Toronto, ON, Canada. The evaluation was conducted using a microscopic simulation model combined with a categorical crash potential model for estimating safety impacts.

Assessing safety benefits of variable speed limits

A method is suggested for evaluating the effectiveness of variable speed limits in reducing freeway crash potential. The real-time crash prediction model that was developed in earlier studies was used to estimate crash potential for different control strategies of variable speed limits. To mimic realistic responses of drivers to changes in speed limits, a microscopic traffic simulation model was used. The simulation results indicate that total crash potential over the entire freeway segment could be significantly reduced under variable speed limit control with a minimal increase in travel time compared to the fixed speed limit. The methodology for assessing safety benefits of variable speed limits is illustrated, and findings from the experiment that used a simple freeway segment are presented.

A RULE-BASED REAL-TIME TRAFFIC RESPONSIVE SIGNAL CONTROL SYSTEM WITH TRANSIT PRIORITY: APPLICATION TO AN ISOLATED INTERSECTION

Previous experience has shown that real-time, traffic-responsive signal control has the ability to improve traffic operations in urban areas when compared to traditional fixed-time control. However, most of these experiences have focused primarily on the impact on private automobiles. This paper describes the development and evaluation of a fully distributed, real-time, traffic-responsive model named Signal Priority Procedure for Optimization in Real-Time (SPPORT) that explicitly considers the impacts of transit vehicles. This model is unique in two ways. First, the model explicitly considers the interference caused to the general traffic by transit vehicles stopping in the right of way to board and discharge passengers. Second, when considering priority passage for transit vehicles, the potential effects that such preferential treatment might have on other traffic are explicitly quantified. This paper describes the structure of the model and demonstrates its capabilities on an isolated intersection for a range of traffic demands and with and without transit vehicles. The rule-based signal optimization procedure provided delay reductions for most of the traffic conditions examined when compared to both fixed-time and traffic actuated control. While the results reported in this paper are limited to an isolated intersection, the model is capable of being applied to a network of signals. Evaluation of its performance on a corridor has been conducted and will appear in the literature in the near future.

Delay Variability at Signalized Intersections

Delays that individual vehicles may experience at a signalized intersection are usually subject to large variation because of the randomness of traffic arrivals and interruption caused by traffic signal controls. Although such variation may have important implications for the planning, design, and analysis of signal controls, currently no analytical model is available to quantify it. The development of an analytical model for predicting the variance of overall delay is described. The model is constructed on the basis of the delay evolution patterns under two extreme traffic conditions: highly undersaturated and highly oversaturated conditions. A discrete cycle-by-cycle simulation model is used to generate data for calibrating and validating the proposed model. The practical implications of the model are demonstrated through its use in determining optimal cycle times with respect to delay variability and in assessing level of service according to the percentiles of overall delay.

Impact of Driver Compliance on the Safety and Operational Impacts of Freeway Variable Speed Limit Systems

Variable speed limit (VSL) systems enable freeway system managers to change the posted speed limit on a section of roadway in response to varying conditions. VSL system goals may include homogenizing traffic flow, improving safety, and/or reducing driver stress. Although it is understood that the effectiveness of VSL systems is impacted by the level of driver compliance, which itself is influenced by the extent of speed limit enforcement, very little is known about the strength of these impacts. This paper uses a simulation model to evaluate the sensitivity of the safety and operational impacts of VSL to driver compliance. Several scenarios for driver compliance were modeled using the PARAMICS microscopic traffic simulator. Findings indicated that VSL impacts are very sensitive to the level of driver compliance. Safety was shown to be positively correlated with the level of compliance, and travel time was shown to be negatively correlated. However, it was also found that the magnitude of the impact is strongly influenced by the VSL control strategy (i.e., set of rules for incrementing and decrementing the speed limits) being used. Therefore, selection of the VSL control strategy cannot be done independently of the decision regarding speed limit enforcement.

Analytical Method for Estimating the Impact of Transit Signal Priority on Vehicle Delay

Transit agencies seeking to improve transit service delivery are increasingly considering the deployment of transit signal priority (TSP). However, the impact of TSP on transit service and on the general traffic stream is a function of many factors, including intersection geometry, signal timings, traffic demands, TSP strategies and parameters, transit vehicle headways, timing when transit vehicles arrive at the intersection, etc. Previous studies have shown that depending on these factors, the net impact of TSP in terms of vehicle or person delay can be positive or negative. Furthermore, because of financial constraints, transit agencies are often able to deploy TSP at only a portion of all of the candidate intersections. Consequently, there is a need to estimate the impact of TSP before implementation to assist in determining at which intersections TSP should be deployed. Currently, the impacts of TSP are often estimated by using microscopic simulation models. However, the application of these models is...

Automatic Vehicle Identification Technology-Based Freeway Incident Detection

The recent emergence of automatic vehicle identification technology (AVI) for use in electronic toll collection has provided an opportunity to develop automatic incident detection (AID) methods that rely on individual vehicle travel time data instead of loop detector data. The performances of three AVI-based AID algorithms are examined. Travel time data for testing of the algorithms were obtained by simulating a 12-km section of the collector facility of Highway 401 in Toronto, Ontario, Canada. The performances of the three AVI-based AID algorithms are compared with the performance of a leading loop detector–based algorithm, which was independently tested with similar simulated data. The AID performance results indicate that AVI-based AID algorithms can provide incident detection performance similar to that of existing loop detector-based AID methods.