Artificial potential fields (APF) and reinforcement learning (RL) are two common methods for the intelligent decision of autonomous vehicles. The process of vehicle driving includes the constraints of vehicle dynamics, traffic rules, road conditions, and other traffic vehicles, which are quite complex. The existing APF methods perform inadequately since they consider only limited factors and their effects. As such, it is difficult to adapt to increasingly complex traffic environments. In this paper, we propose a new concept, compound traffic field (CTF). The concept makes use of field theory to model various traffic environments based on the physical properties and traffic rules, besides, introduces the concept of the force correction field to reveal the interaction between the vehicle and the surrounding environment during driving. Moreover, an intelligent decision method and a co-simulation platform are established based on combining RL and CTF. The method has passed the tests in various scenarios built by PreScan and compared with the Conventional APF and modeless algorithm. For solving intelligent decision problems in the complex environment provides an applicable field model and its application method.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Research on Intelligent Decision Based on Compound Traffic Field


    Additional title:

    Int.J Automot. Technol.


    Contributors:
    Luo, Yutao (author) / Dai, Jinkun (author) / Li, Hongluo (author)

    Published in:

    Publication date :

    2021-08-01


    Size :

    12 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




    Intelligent Decision Support System for Traffic Incident Management

    Li, H. / Lu, H. / Qureshi, I. A. et al. | British Library Conference Proceedings | 2005


    Intelligent Decision Support System for Traffic Incident Management

    Li, Hongqiang / Lu, Huapu / Qureshi, Intikhab Ahmed | ASCE | 2006


    Research of Intelligent Traffic Management System

    Fang, Dan Yu | Trans Tech Publications | 2013