In order to study the effect of crossing pedestrians on traffic performance at crosswalk without signal control, the work develops a game theory-based description of pedestrian–vehicle interactions, considering the decision-making uncertainty. The hybrid strategy of the game is obtained. The relevant parameters of the game model are calibrated by collected video data. The cellular automaton simulation system composed of a two-way four-lane traffic flow and pedestrian flow is constructed with the game model imbedded for identifying the effect of crossing pedestrians on traffic performance. The influencing factors are identified with their correlation analyzed by numerical simulation of different traffic conditions. According to the simulation results, the arrival rate of pedestrians has a great impact on traffic volume and pedestrian delay. The severity of conflicts between vehicles and pedestrians is classified and the causes are identified by analyzing the arrival rate of pedestrians and vehicles, respectively, and their relationship between one another. In addition, the threshold of traffic flow and pedestrian flow causing traffic conflicts and delay is proposed, also including the threshold of pedestrian arrival rate which will induce force crossing behaviors. The results show that the proposed model reconstructs the traits of traffic and pedestrian flow and their conflicts phenomenon at crosswalks. It provides some practical references for transportation agencies to meet pedestrians time-cost and comfort needs in crossing streets when they design pedestrian crossing facilities.
Emerging connected autonomous vehicle (CAV) technologies provide an opportunity to the vehicle motion control to improve the traffic performance. This study simulated and evaluated the CAV-based speed and lane-changing (LC) control strategies at the expressway work zone in heterogeneous traffic flow. The control strategies of CAV are optimized by the multi-layer control structure based on model predictive control. The heterogeneous traffic flow composed of human-driven vehicles and CAVs is constructed based on cellular automata by the proposed Expected Distance-based Symmetric Two-lane Cellular Automate (ED-STCA) LC model and CAV car-following model. The six control strategies composed of variable speed limits (VSL), LC and their coordinated control strategies are experimented. The average travel time and throughput are selected to assess the advantages and disadvantages of each strategy under each combination of vehicles’ arrival rates and CAV mixed ratios. The numerical results show that: (i) the effect of the control strategy on the traffic is not obvious under free flow, and the control strategy may worsen the traffic under medium traffic. (ii) Early lane-changing control (ELC) is better than late lane-changing control (LLC) under medium traffic, and LLC is better under heavy traffic. (iii) [Formula: see text] is the best choice under heavy traffic and the mixed rate of CAVs is high. The simulation results obtained in the paper would provide some practical references for transportation agencies to manage the traffic in work zone under networking environment in the future.
In order to analyze the effect of U-turn vehicle on traffic performance, the work develops a game theory-based description of drivers’ interactions in U-turn scene, considering the decision-making uncertainty. The hybrid strategy of the game is obtained. The relevant parameters of model are calibrated by collected video data in Changchun, China. A two-way four-lane cellular automaton model with the game model imbedded is constructed for identifying the effect of U-turn vehicle on traffic performance. The influencing factors are identified with their correlation analyzed by numerical simulation of different traffic conditions. According to the simulation results, U-turn traffic has a significant influence on traffic delay in the lane of same direction, compared with opposite direction. The severity of conflict between vehicles is classified and the causes are identified by analyzing the arrival rate of the U-turn vehicle and the conflicting straight vehicle and the relationship with one another. In addition, the threshold of traffic flow causing traffic conflict and traffic delay are proposed. The results show that the proposed models reconstructed the traits of traffic flow and conflict phenomenon in the presence of U-turn vehicles on road section.
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