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Article

A Data-Driven Path-Tracking Model Based on Visual Perception Behavior Analysis and ANFIS Method

by
Ziniu Hu
1,†,
Yue Yu
2,†,
Zeyu Yang
1,3,*,
Haotian Zhu
1,
Lvfan Liu
1 and
Yunshui Zhou
1
1
College of Mechanical and Vehicle Engineering, Hunan University, Changsha 410012, China
2
Bosch HUAYU Steering Systems Company, Shanghai 201821, China
3
Wuxi Intelligent Control Research Institute (WICRI) of Hunan University, Wuxi 214121, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Electronics 2024, 13(1), 61; https://doi.org/10.3390/electronics13010061
Submission received: 2 November 2023 / Revised: 6 December 2023 / Accepted: 8 December 2023 / Published: 21 December 2023
(This article belongs to the Special Issue Recent Advances in Motion Planning and Control of Autonomous Vehicles, 2nd Edition)
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Abstract

This paper proposes a data-driven human-like driver model (HDM) based on the analysis and understanding of human drivers’ behavior in path-tracking tasks. The proposed model contains a visual perception module and a decision-making module. The visual perception module was established to extract the visual inputs, including road information and vehicle motion states, which can be perceived by human drivers. The extracted inputs utilized for lateral steering decisions can reflect specific driving skills exhibited by human drivers like compensation control, preview behavior, and anticipation ability. On this basis, an adaptive neuro-fuzzy inference system (ANFIS) was adopted to design the decision-making module. The inputs of the ANFIS include the vehicle speed, lateral deviation in the near zone, and heading angle error in the far zone. The output is the steering wheel angle. ANFIS can mimic the fuzzy reasoning characteristics of human driving behavior. Next, a large amount of human driving data was collected through driving simulator experiments. Based on the data, the HDM was established. Finally, the results of the joint simulation under PreScan/MATLAB verified the superior performances of the proposed HDM.
Keywords: human-like driver model; path tracking; visual perception of drivers; steering behavior; ANFIS human-like driver model; path tracking; visual perception of drivers; steering behavior; ANFIS

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MDPI and ACS Style

Hu, Z.; Yu, Y.; Yang, Z.; Zhu, H.; Liu, L.; Zhou, Y. A Data-Driven Path-Tracking Model Based on Visual Perception Behavior Analysis and ANFIS Method. Electronics 2024, 13, 61. https://doi.org/10.3390/electronics13010061

AMA Style

Hu Z, Yu Y, Yang Z, Zhu H, Liu L, Zhou Y. A Data-Driven Path-Tracking Model Based on Visual Perception Behavior Analysis and ANFIS Method. Electronics. 2024; 13(1):61. https://doi.org/10.3390/electronics13010061

Chicago/Turabian Style

Hu, Ziniu, Yue Yu, Zeyu Yang, Haotian Zhu, Lvfan Liu, and Yunshui Zhou. 2024. "A Data-Driven Path-Tracking Model Based on Visual Perception Behavior Analysis and ANFIS Method" Electronics 13, no. 1: 61. https://doi.org/10.3390/electronics13010061

APA Style

Hu, Z., Yu, Y., Yang, Z., Zhu, H., Liu, L., & Zhou, Y. (2024). A Data-Driven Path-Tracking Model Based on Visual Perception Behavior Analysis and ANFIS Method. Electronics, 13(1), 61. https://doi.org/10.3390/electronics13010061

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