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Research Article | Open Access

Intelligent decision-making method for vehicles in emergency conditions based on artificial potential fields and finite state machines

Xunjia Zheng1,2, Huilan Li3, Qiang Zhang1, Yonggang Liu4, Xing Chen2, Hui Liu2, Tianhong Luo2, Jianjie Gao5( ), Lihong Xia1
China Automotive Engineering Research Institute Co., Ltd., Chongqing 401122, China
School of Intelligent Manufacturing Engineering, Chongqing University of Arts and Sciences, Chongqing 402160, China
Department of Information and Intelligence Engineering, Chongqing City Vocational College, Chongqing 402160, China
College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China
Intelligent Policing Key Laboratory of Sichuan Province, Luzhou 646000, China
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Abstract

This study aims to propose a decision-making method based on artificial potential fields (APFs) and finite state machines (FSMs) in emergency conditions. This study presents a decision-making method based on APFs and FSMs for emergency conditions. By modeling the longitudinal and lateral potential energy fields of the vehicle, the driving state is identified, and the trigger conditions are provided for path planning during lane changing. In addition, this study also designed the state transition rules based on the longitudinal and lateral virtual forces. It established the vehicle decision-making model based on the finite state machine to ensure driving safety in emergency situations. To illustrate the performance of the decision-making model by considering APFs and finite state machines. The version of the model in the co-simulation platform of MATLAB and CarSim shows that the developed decision model in this study accurately generates driving behaviors of the vehicle at different time intervals. The contributions of this study are two-fold. A hierarchical vehicle state machine decision model is proposed to enhance driving safety in emergency scenarios. Mathematical models for determining the transition thresholds of lateral and longitudinal vehicle states are established based on the vehicle potential field model, leading to the formulation of transition rules between different states of autonomous vehicles (AVs).

Keywords

autonomous drivingdecision-makingartificial potential fieldfinite state machinesemergency conditions

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Journal of Intelligent and Connected Vehicles
Volume 7 Issue 1,
March 2024
Pages 19-29
DOI: 10.26599/JICV.2023.9210025
Cite this article:
Zheng X, Li H, Zhang Q, et al. Intelligent decision-making method for vehicles in emergency conditions based on artificial potential fields and finite state machines. Journal of Intelligent and Connected Vehicles, 2024, 7(1): 19-29. https://doi.org/10.26599/JICV.2023.9210025

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Received: 24 September 2023
Revised: 18 October 2023
Accepted: 06 November 2023
Published: 31 March 2024
© The author(s) 2024.

This is an open access article under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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