不同险态情景下共驾型智能车辆接管行为特征分析

Analysis of characteristics of the takeover behavior of co⁃driving intelligent vehicles under different dangerous scenarios

为提高驾驶人在不同险态交通情景下接管智能车辆的安全性,在模拟驾驶平台上分别研究了高速公路、山区道路和城市道路3类典型险态环境下驾驶人接管行为的特征和差异性。试验采集并分析了16名驾驶人在3类典型险态环境下的驾驶行为数据。结果表明:①驾驶人在接管车辆时采取的应急操作包括制动、转向、同时转向制动3种,各行为占比分别为71.4%、16.7%和11.9%。②不同险态交通情景下驾驶人接管反应时间无显著差异(P>0.05);在高速-城市险态情景下车辆最大纵向减速度存在显著差异(P=0.002<0.05),在山区-城市险态情景下车辆最大纵向减速度存在显著差异(P=0.048<0.05);在城市-山区险态情景下车辆最大转向盘转角存在显著差异(P=0.015<0.05);在山区-高速险态情景下车辆最大转向盘转角存在显著差异(P=0.000<0.05)。说明在不同险态交通情景下应采用不同的接管措施以提升接管的安全性和有效性。本文研究结果可为不同险态环境下的智能车辆接管系统研发提供参考。

In order to improve the safety of drivers taking over intelligent vehicles under different risky traffic scenarios,the characteristics and differences of drivers'taking over behaviors under three typical risky environments,namely highway,mountain road and city road,were studied in a simulated driving platform.The test collected and analyzed the driving behavior data of 16 drivers in three types of typical risky environments.The results showed that:①The emergency actions taken by the drivers when taking over the vehicle included braking,steering and simultaneous steering and braking,with the percentages of each action being 71.4%,16.7%and 11.9%respectively.②There was no significant difference(P>0.05)in the reaction time of driver taking over in different dangerous traffic scenarios;There was a significant difference in the maximum longitudinal deceleration between highway and city road(P=0.002<0.05),and a significant difference in the maximum longitudinal deceleration between mountain road and city road(P=0.048<0.05).There was a significant difference in the maximum steering wheel Angle between city road and mountain road(P=0.015<0.05),and there was a significant difference in the maximum steering wheel Angle between mountain road and highway(P=0.000<0.05).It shows that different takeover measures should be used to improve the safety and effectiveness of takeover in different risky traffic scenarios.The results of the proposed method can provide reference for the development of intelligent vehicle takeover systems in different risky environments.