异质车型影响下智能汽车二维碰撞风险预测

Two-Dimensional Collision Risk Prediction for Intelligent Vehicles Considering the Influence of Heterogeneous Vehicle Types

行车碰撞风险的准确预测是保证智能汽车安全行驶的关键,但目前评估方法鲜有考虑异质车型风险差异性及横纵向二维风险耦合。为此,本文首先挖掘异质车型驾驶人的行为规律,解析车型对驾驶人风险敏感度的影响;其次,辨识获得不同车型组合的异质风险阈值,利用二维指标量化交通风险差异性;最终提出考虑车辆类型的二维碰撞风险耦合预测模型,并通过对比验证模型的准确性。该研究有助于提升智能汽车的行驶安全性,且可为人类驾驶汽车的碰撞预警系统开发提供理论依据。

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 twodimensional 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.