文献类型：会议论文

英文题名：Regression Model of Autonomous Lateral Rectification with Driver Perception

作者：Qiao, Liang[1];Bao, Hong[1];Xuan, Zuxing[1];Yang, Qing[2]

通讯作者：Bao, H[1]

机构：[1]Beijing Union Univ, Beijing Key Lab Informat Serv Engn, Beijing, Peoples R China;[2]Beijing Union Univ, Coll Robot, Beijing, Peoples R China

第一机构：北京联合大学北京市信息服务工程重点实验室

通讯机构：[1]corresponding author), Beijing Union Univ, Beijing Key Lab Informat Serv Engn, Beijing, Peoples R China.|[11417103]北京联合大学北京市信息服务工程重点实验室;[11417]北京联合大学;

会议论文集：13th International Conference on Computational Intelligence and Security (CIS)

会议日期：DEC 15-18, 2017

会议地点：Hong Kong, HONG KONG

语种：英文

外文关键词：regression model; autonmous vehicle; logarithmic relationship; Driver Perception Model(DPM); preview point; lateral rectification

摘要：It is usually hard for autonomous vehicle to perform human-likely in lateral rectification between desired path and ego-vehicle, since those methods choose linear preview point according to speed. This paper presents a regression model of autonomous lateral rectification with driver perception to describe relationship between preview point and speed. It is shown in Driver Perception Model( DPM) that logarithmic relationship between speed and preview point distance. Experimental results show that compared with lateral rectification of Stanley method, regression model of autonomous lateral rectification with driver perception can 1) acquire lower lateral acceleration, which enhances comfort; 2) promote robustness of algorithm on parameter tuning.