Curve Trajectory Model for Human Preferred Path Planning of Automated Vehicles  

作　　者：Gergo Ferenc Igneczi Erno Horvath Roland Toth Krisztian Nyilas 

机构地区：[1]Vehicle Research Center,Szechenyi Istvan University,Egyetem ter 1,Gyor 9026,Hungary [2]Institute for Computer Science and Control,Kende str.13-17.,Budapest 1111,Hungary [3]Robert Bosch Kft,Gyomroi str.104-120,Budapest 1103,Hungary

出　　处：《Automotive Innovation》2024年第1期59-70,共12页汽车创新工程（英文）

基　　金：supported by the European Union within the framework of the National Laboratory for Autonomous Systems.(RRF-2.3.1-21-2022-00002).

摘　　要：Automated driving systems are often used for lane keeping tasks.By these systems,a local path is planned ahead of the vehicle.However,these paths are often found unnatural by human drivers.In response to this,this paper proposes a linear driver model,which can calculate node points reflective of human driver preferences and based on these node points a human driver preferred motion path can be designed for autonomous driving.The model input is the road curvature,effectively harnessed through a self-developed Euler-curve-based curve fitting algorithm.A comprehensive case study is undertaken to empirically validate the efficacy of the proposed model,demonstrating its capacity to emulate the average behavioral pat-terns observed in human curve path selection.Statistical analyses further underscore the model's robustness,affirming the authenticity of the established relationships.This paradigm shift in trajectory planning holds promising implications for the seamless integration of autonomous driving systems with human driving preferences.

关 键 词：Naturalistic driving Identification Driver models Path planning 

分 类 号：R73[医药卫生—肿瘤]