Abstract
Aiming at solving a typical problem of past research using accident experience statistics of being unable to adapt to changing traffic flows, this paper provides an evaluation method of the risk of vehicle rear-end collisions at red-light-camera (RLC) intersections based on theoretical probabilities. Taking advantage of trajectory data of vehicles at the two similar intersections, which are Cao’an Road and Lvyuan Road with RLCs and Cao’an Road and Anhong Road without RLCs in Shanghai, a binary logit (BL) model of stop-and-go decision-making is established. Using the model and adjusting the headway and potential travel time, we can perform simulation and analysis of rear-end collisions. The result shows that this method is feasible to analyse the influence of RLCs on rear-end collisions. The analysis indicates that RLCs can cause higher speeds for vehicles passing the RLC intersection and more abnormal driving behaviors, which increase the difficulty of stop-and-go decision-making. RLCs do not always lead to an increase of rear-end collisions. For vehicles close to or far from intersection at the decision-making time, RLCs will significantly reduce the possibility of rear-end collisions; however, for vehicles in the potential travel time of 2 s∼3 s, RLCs will increase the probability of rear-end collisions.
Highlights
In the past, running a red light during signal changes was a common phenomenon at intersections, which had a significant impact on the traffic safety of intersection
redlight cameras (RLCs) affect the driver’s driving state and decision-making behavior at the intersection, and many potential safety problems that may be caused by RLCs have not been fully explored. erefore, it is important to evaluate the impact of RLC installation on vehicle operation safety
Past research on RLCs mainly has the following two problems: First, the safety impact analysis of RLCs is mostly based on accident experience statistics, where the accident data collection cycle is long and the time span is large, during which changes in other road traffic parameters will lead to reductions in the credibility of the final evaluation result. us, the RLC evaluation method based on accident experience statistics has serious defects
Summary
In the past, running a red light during signal changes was a common phenomenon at intersections, which had a significant impact on the traffic safety of intersection. Using driving characteristic data of vehicles at the intersection decisionmaking time, the impact analysis and evaluation of RLCs on drivers’ stop-and-go decision-making and rear-end hazards can be realized, therein avoiding the error and cost brought by accident statistics. RLCs can reduce the red-light violation rates of vehicles, their effect on rear-end accidents at intersections is more complex. Past research on RLCs mainly has the following two problems: First, the safety impact analysis of RLCs is mostly based on accident experience statistics, where the accident data collection cycle is long and the time span is large, during which changes in other road traffic parameters will lead to reductions in the credibility of the final evaluation result. Erefore, it is necessary to make a systematic analysis of the driver’s behavior characteristics, the stop-and-go decision-making behavior, and the risk of traffic safety in the case of RLCs
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