Variable Speed Limit Control Strategy with Collision Probability Assessments Based on Traffic State Prediction

Abstract

An increasing number of vehicles on roadways has made traffic safety a serious challenge for transportation engineers. For the mitigation of traffic safety concerns, a variety of active traffic control measures, such as the variable speed limit (VSL), have been intensively investigated and deployed. VSL is usually adopted to advise drivers of a lower speed limit that is more appropriate to a congested traffic condition and takes advantage of the homogeneous traffic flow effect. However, in earlier studies, because of the absence of traffic state prediction, the impact of applied VSL control was not quantitatively analyzed. In this study, a model predictive control framework was adopted for predicting and assessing future traffic states. Taking into consideration the impact of VSL control, the study used a macroscopic traffic flow model. The collision probabilities of the predicted traffic states were assessed with a precursor-based collision prediction model to determine the optimized control signal. With this design, the proposed algorithm controller provided a robust method for determining the VSL control plan to optimize safety performance over a traffic network. The proposed control algorithm was evaluated with a simulation study based on field data that was conducted to reproduce a major ring road in Edmonton, Alberta, Canada. The proposed algorithm was used to implement VSL control on the studied 11-km freeway stretch. The proposed algorithm control scenario was then compared with the uncontrolled scenario. The evaluation proved that the proposed VSL control algorithm could effectively reduce the probability for collisions in a congested traffic network without significantly compromising mobility.Transportation engineers have been working for decades to resolve traffic-related problems. Because of the growing number of automobiles on roadways, traffic congestion causes loss of productivity and mobility. Furthermore, because of increased traffic incidents, the amount of property damage and loss is growing. A variety of active traffic control measures, such as the variable speed limit (VSL), ramp metering, and manageable lanes, have been investigated and deployed.VSL control provides drivers with an appropriate operating speed, one lower than the posted static speed limit, in response to dynamic road conditions. The posted speed limit on highways suggests the standard operating speed for road users in ideal conditions. However, during adverse traffic conditions, such as excessive demand or reduced roadway capacity (such as with construction), the posted speed limit may not be the optimal operating speed (1). Through field implementations and simulations, earlier studies reported that by enhancing the speed homogeneity effects, VSL improves traffic flow in terms of safety (1-3) and, potentially, mobility (4, 5). A statistical crash probability model is usually used to assess the safety benefits of a VSL control. Abdel-Aty et al. developed a crash probability model for formulating incident likelihood by examini...

Predicting Traffic Dynamics with Driver Response Model for Proactive Variable Speed Limit Control Algorithm

“…In order to evaluate the performance of the proposed driver response model, an enhanced prediction-based active traffic control algorithm previously proposed by the authors in [3,20] was adopted in this study. For the readers' convenience, here the authors briefly introduce the basic concept of the control algorithm and where the driver response model proposed in this paper fits in.…”

“…Lu et al 's and a couple of other later research works [3,7,18] replaced the desired speed directly with the advised VSL value ( ), assuming that traffic will follow the advised VSL value strictly. As explained before, to more accurately reflect the real-world situation, this anticipation term should be qualified to treat driver responses differently under different traffic conditions.…”

“…), or high traffic demand generated by large events. Earlier studies reported that, by implementing VSL to enhance speed homogeneity, traffic conditions can be improved in terms of both safety [1][2][3] and mobility [4,5].…”

“…Instead, the response of flow speed to the VSL should vary according to the current traffic conditions. Moreover, such a dynamic response mechanism needs to be taken into consideration while anticipating future traffic states in prediction-based VSL control algorithms, such as [3,8]. Therefore, in this study, the authors propose to establish a macroscopic VSL response model, which describes the change in drivers' responses to the implemented VSL dynamically, according to the current traffic conditions.…”

“…The model was conducted through a regression of field experiment data. For model evaluation, this paper adopts the prediction-based VSL control algorithm described in the authors' earlier article [3] and has further improved its traffic state prediction module.…”