Brain-like Intelligent Decision-making Based on Basal Ganglia and Its Application in Automatic Car-following  

作　　者：Tianjun Sun Zhenhai Gao Zhiyong Chang Kehan Zhao 

机构地区：[1]State Key Laboratory of Automotive Simulation and Control,Jilin University,Changchun130022,China [2]College of Automotive Engineering,Jilin University,Changchun130022,China [3]College of Biological and Agricultural Engineering,Jilin University,Changchun130022,China [4]College of Materials Science and Engineering,Jilin University,Changchun130022,China

出　　处：《Journal of Bionic Engineering》2021年第6期1439-1451,共13页仿生工程学报（英文版）

基　　金：supported by the National Key Research and Development Program of China(2017YFB0102601);the National Science Foundation of China(51775236).

摘　　要：The anthropomorphic intelligence of autonomous driving has been a research hotspot in the world.However,current studies have not been able to reveal the mechanism of drivers'natural driving behaviors.Therefore,this thesis starts from the perspective of cognitive decision-making in the human brain,which is inspired by the regulation of dopamine feedback in the basal ganglia,and a reinforcement learning model is established to solve the brain-like intelligent decision-making problems in the process of interacting with the environment.In this thesis,first,a detailed bionic mechanism architecture based on basal ganglia was proposed by the consideration and analysis of its feedback regulation mechanism;second,the above mechanism was transformed into a reinforcement Q-learning model,so as to implement the learning and adaptation abilities of an intelligent vehicle for brain-like intelligent decision-making during car-following;finally,the feasibility and effectiveness of the proposed method were verified by the simulations and real vehicle tests.

关 键 词：Brain-like intelligent decision-making Dopamine in basal ganglia Reinforcement learning Longitudinal autonomous driving 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]