The pedestrians can only avoid collisions passively under the action of forces during simulations using the social force model, which may lead to unnatural behaviors. This paper proposes an optimization-based model fo...The pedestrians can only avoid collisions passively under the action of forces during simulations using the social force model, which may lead to unnatural behaviors. This paper proposes an optimization-based model for the avoidance of collisions, where the social repulsive force is removed in favor of a search for the quickest path to destination in the pedestrian＇s vision field. In this way, the behaviors of pedestrians are governed by changing their desired walking direction and desired speed. By combining the critical factors of pedestrian movement, such as positions of the exit and obstacles and velocities of the neighbors, the choice of desired velocity has been rendered to a discrete optimization problem. Therefore,it is the self-driven force that leads pedestrians to a free path rather than the repulsive force, which means the pedestrians can actively avoid collisions. The new model is verified by comparing with the fundamental diagram and actual data. The simulation results of individual avoidance trajectories and crowd avoidance behaviors demonstrate the reasonability of the proposed model.展开更多
为探索基于车联网V2P(Vehicle to Pedestrian)通信技术的行人碰撞风险辨识方法,首先,在车联网环境下实时获取了目标位置、速度、运动方向等信息,并分析了典型人—车相对运动场景中交通参与者的行为不确定性,进而提出了人—车碰撞区域随...为探索基于车联网V2P(Vehicle to Pedestrian)通信技术的行人碰撞风险辨识方法,首先,在车联网环境下实时获取了目标位置、速度、运动方向等信息,并分析了典型人—车相对运动场景中交通参与者的行为不确定性,进而提出了人—车碰撞区域随机几何模型;然后,综合考虑了车联网系统的通信延时、定位误差、人—车相对运动不确定性等多因素的影响,建立了人—车碰撞事故概率和冲突风险程度模型;最后,通过仿真实验分析了行车速度、通信延时、定位精度等因素对行人碰撞风险辨识模型效果的影响,以及各因素间的相关性关系.本文提出的方法对行人安全保护研究具有一定的参考价值,研究结果同时指出了车联网系统通信延时与定位精度的技术要求.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.61233001 and 61322307)the Fundamental Research Funds for Central Universities of China(Grant No.2013JBZ007)
文摘The pedestrians can only avoid collisions passively under the action of forces during simulations using the social force model, which may lead to unnatural behaviors. This paper proposes an optimization-based model for the avoidance of collisions, where the social repulsive force is removed in favor of a search for the quickest path to destination in the pedestrian＇s vision field. In this way, the behaviors of pedestrians are governed by changing their desired walking direction and desired speed. By combining the critical factors of pedestrian movement, such as positions of the exit and obstacles and velocities of the neighbors, the choice of desired velocity has been rendered to a discrete optimization problem. Therefore,it is the self-driven force that leads pedestrians to a free path rather than the repulsive force, which means the pedestrians can actively avoid collisions. The new model is verified by comparing with the fundamental diagram and actual data. The simulation results of individual avoidance trajectories and crowd avoidance behaviors demonstrate the reasonability of the proposed model.
文摘为探索基于车联网V2P(Vehicle to Pedestrian)通信技术的行人碰撞风险辨识方法,首先,在车联网环境下实时获取了目标位置、速度、运动方向等信息,并分析了典型人—车相对运动场景中交通参与者的行为不确定性,进而提出了人—车碰撞区域随机几何模型;然后,综合考虑了车联网系统的通信延时、定位误差、人—车相对运动不确定性等多因素的影响,建立了人—车碰撞事故概率和冲突风险程度模型;最后,通过仿真实验分析了行车速度、通信延时、定位精度等因素对行人碰撞风险辨识模型效果的影响,以及各因素间的相关性关系.本文提出的方法对行人安全保护研究具有一定的参考价值,研究结果同时指出了车联网系统通信延时与定位精度的技术要求.
