异质车型影响下智能汽车二维碰撞风险预测

Accurate prediction of collision risk is crucial for ensuring the driving safety of intelligent vehicles. However,the risk differentiation among heterogeneity vehicle types and its coupled effect in longitudinal and lateral directions has rarely been considered in existing driving risk assessment methods. Therefore,firstly,the behavior patterns of drivers of heterogeneous vehicle types are explored to analyze the influence of vehicle types on drivers' sensitivity to risk in this paper. Secondly,the heterogeneous risk thresholds for different combinations of vehicle types are identified,and the risk differentiation in such traffic surroundings is further quantified based on two-dimensional indicators. Finally,the coupled two-dimensional collision risk prediction model considering vehicle types is proposed,and the effectiveness of the model is validated through comparative analysis. This research helps to enhance the driving safety of intelligent vehicles,which also can provide a theoretical foundation for the development of collision warning systems for human-driven vehicles.