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Research on Integrated Decision Control Algorithm for Autonomous Vehicles Under Multi-Task Hybrid Constraints in Intelligent Transportation Scenarios

School of Automation, Chongqing University, Shapingba District, Chongqing 400044, P. R. China

Dongfeng Xiaokang Automobile Co., Ltd, Jiujiang Avenue, Shuangfu New District, Jiangjin District Chongqing 402247, P. R. China

E-mail Address: zonghuan208@163.com

Corresponding author.

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Dihua Sun

School of Automation, Chongqing University, Shapingba District, Chongqing 400044, P. R. China

E-mail Address: d3sun@163.com

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, and

Lin Zhou

Dongfeng Xiaokang Automobile Co., Ltd, Jiujiang Avenue, Shuangfu New District, Jiangjin District Chongqing 402247, P. R. China

E-mail Address: lin.zhou03783@dfsk.com.cn

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https://doi.org/10.1142/S0218126622501225Cited by:2 (Source: Crossref)

Abstract

In order to improve the decision-making and control effect of autonomous vehicles, in this paper, combined with literature research and process analysis, the control algorithm of autopilot vehicle is analyzed, and the driving process is analyzed combined with the flow method. In order to improve the effect of autonomous driving, with the support of improved algorithms, an integrated decision-making control system for autonomous vehicles under multi-task constraints in intelligent traffic scenarios is constructed, and system performance is improved by simulating autonomous driving decisions in a variety of complex situations. Moreover, this paper designs the road driving model according to actual needs, sets the functional modules of the entire system, and build the overall framework of the system. Finally, in order to study the integrated decision-making effect of this system, this paper conducts test research by designing a simulation test method. From the simulation test results, it can be seen that the intelligent decision-making system for autonomous vehicles constructed in this paper has certain effects.

This paper was recommended by Regional Editor Takuro Sato.

Keywords:

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