A Review of Progresses and Prospects of Human-machine Shared Control Technology for L2 Intelligent Driving Based on Haptic Guidance

DENG Xiujin; WANG Yanyang; HUANG Qiushi; WANG Ke; LIAO Kaikai

doi:10.3963/j.jssn.1674-4861.2022.05.003

Volume 40 Issue 5

Nov. 2022

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Article Navigation > Journal of Transport Information and Safety > 2022 > 40(5): 23-33

DENG Xiujin, WANG Yanyang, HUANG Qiushi, WANG Ke, LIAO Kaikai. A Review of Progresses and Prospects of Human-machine Shared Control Technology for L2 Intelligent Driving Based on Haptic Guidance[J]. Journal of Transport Information and Safety, 2022, 40(5): 23-33. doi: 10.3963/j.jssn.1674-4861.2022.05.003

Citation:

DENG Xiujin, WANG Yanyang, HUANG Qiushi, WANG Ke, LIAO Kaikai. A Review of Progresses and Prospects of Human-machine Shared Control Technology for L2 Intelligent Driving Based on Haptic Guidance[J]. Journal of Transport Information and Safety, 2022, 40(5): 23-33. doi: 10.3963/j.jssn.1674-4861.2022.05.003

Citation:

DENG Xiujin, WANG Yanyang, HUANG Qiushi, WANG Ke, LIAO Kaikai. A Review of Progresses and Prospects of Human-machine Shared Control Technology for L2 Intelligent Driving Based on Haptic Guidance[J]. Journal of Transport Information and Safety, 2022, 40(5): 23-33. doi: 10.3963/j.jssn.1674-4861.2022.05.003

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A Review of Progresses and Prospects of Human-machine Shared Control Technology for L2 Intelligent Driving Based on Haptic Guidance

doi: 10.3963/j.jssn.1674-4861.2022.05.003

DENG Xiujin^{1, 2, 3
,},
WANG Yanyang^{1, 2, 3
,
,},
HUANG Qiushi^{1, 2, 3},
WANG Ke^{1, 2, 3},
LIAO Kaikai^{1, 2, 3}

1.
Key Laboratory of Automobile Measurement and Control & Safety, Xihua University, Chengdu 610039, China
2.
Key Laboratory of Fluid and Power Machinery of Ministry of Education, Xihua University, Chengdu 610039, China
3.
Provincial Engineering Research Center for New Energy Vehicle Intelligent Control and Simulation Test Technology of Sichuan, Chengdu 610039, China

Received Date: 2021-12-31
Available Online: 2022-12-05

Abstract

Abstract

It is nearly impossible for intelligent automobiles to achieve a fast upgradation from L1 to L5 in a short time due to the limitations of technologies, regulations, and other factors. Thus, human-machine shared driving will be the case for a long run. The human-machine shared control (HMSC) technology based on haptic guidance provides an effective way for intelligent automobiles operating at the L2 level. Through reviewing the literature regarding the current progress of HMSC technology, this study focuses on studying conflicts created over the human-machine collaboration in the process of route planning, intention commitment, and control assignment related to the maneuvers like lane keeping, lane changing, collision avoidance and backing-up, which may result in reduced vehicle stability, poor driving safety, and deteriorated operating comfort and freedom. Meanwhile, the driving styles and cognition differences of drivers are studied to identify the design methods of human-machine shared controller and the mechanism of human-machine conflict. Therefore, it is proposed that the intelligent driving system should be iteratively optimized base on massive simulated or measured driving data in the future and the accuracy of the intelligent driving system in recognizing driving environment and driver's status should be improved. In this way, the control weights of human and machine can be assigned and the problems of control conflict, vehicle stability, driving safety, deteriorated operating comfort and degree of freedom can be solved. Based on the existing issues identified within the research to date, it is pointed out that shared controllers based on the adaptive haptic-guidance, assignment of control weight, neuromuscular response, and advanced assistance systems are major research directions of the HMSC.
- human-machine shared driving,
- haptic guidance,
- human-machine shared control,
- vehicle stability,
- conflicts in human-machine collaboration

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References(49)

References

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A Review of Progresses and Prospects of Human-machine Shared Control Technology for L2 Intelligent Driving Based on Haptic Guidance

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