【作者】 朱乃宣； 高振海； 胡宏宇； 吕颖； 赵伟光；

【Author】 Zhu Naixuan;Gao Zhenhai;Hu Hongyu;Lv Ying;Zhao Weiguang;Jilin University,State Key Laboratory of Automobile Simulation and Control;Intelligent Connected Vehicle Development Institute,China FAW Group Co.,Ltd.;

【机构】 吉林大学汽车仿真与控制国家重点实验室； 中国第一汽车集团有限公司智能网联开发院；

【摘要】 基于风险评估的结果,如何实现智能车安全、合理、个性化的自主换道触发,是当下自主驾驶领域的研究热点。本文中基于人工势场理论,建立了障碍物的静态和动态风险场,从而对车辆周围的风险进行评估。之后对驾驶员日常驾驶数据中的换道数据进行提取和分析,而得到个性化的换道触发。实车试验验证结果表明,采用本方法可很好地评估交通环境中的风险,实现个性化的换道触发。更多还原

【Abstract】 Based on the results of risk assessment,how to trigger a safe,reasonable and personalized autonomous lane change is a research hotspot in the field of autonomous driving.In this paper,based on the theory of artificial potential field,the static and dynamic risk fields of obstacles are established to evaluate the risks around the vehicle.Then,the lane change data in the daily driving data of driver is extracted and analyzed to get the personalized lane change triggering.The results of real vehicle test show that using this method can well evaluate the risks in traffic environment and achieve the personalized lane change triggering.更多还原