无信控交叉口网联车辆动态碰撞风险检测与预警策略OA北大核心CSTPCD

In view of the frequent collision accidents at unsignalized intersections,a dynamic risk detection and early warning strategy for networked vehicle collision at unsignalized intersections based on vehicle-vehicle communication is studied and proposed in the connected artificial driving environment.Firstly,a vehicle trajectory model based on polyno-mial fitting is designed by constructing a typical unsignalized intersection scene.Secondly,using time-to-collision and time exposed time-to-collision as risk detection indicators,a circular-bicircular vehicle model is constructed to realize vehi-cle collision risk detection.Thirdly,considering the heterogeneity of drivers and their interaction behavior,a two-level col-lision warning strategy based on game theory and genetic algorithm is proposed.Finally,a simulation environment is built based on SUMO to test and analyze the effectiveness and applicability of the early warning strategy.The results show that the proposed strategy can accurately identify all collision events and trigger early warning,and the success rate of early warning reaches 100% .Under different proportions of drivers in test conditions,the proposed early warning strategy can significantly reduce the collision rate and average collision kinetic energy.