Optimal fuzzy control system design for car-following behaviour based on the driver–vehicle unit online delays in a real traffic flow

Author:

Ghaffari Ali1,Khodayari Alireza2,Faraji Maysam3

Affiliation:

1. Mechanical Engineering Department, Islamic Azad University, South Tehran Branch, Tehran, Iran

2. Mechanical Engineering Department, Islamic Azad University, Pardis Branch, Pardis, Iran

3. Mechatronic Engineering Department, Islamic Azad University, South Tehran Branch, Tehran, Iran

Abstract

Promoting safety and comfort in driving and reducing the traffic, the pollution and the energy consumption are the main purposes of using many control systems in different driving processes. Car following is the dominant and effective behaviour in traffic flow, the automatization of which is crucial to achieving the aforementioned goals. In this paper, a novel optimal fuzzy control system is designed so that the follower vehicle maintains a safe distance from the vehicle in front of it in a traffic queue with a reduction in the energy consumption. This controller is superior in that it considers the online delays in the reaction of the driver–vehicle unit in the design. The instantaneous delay is estimated using the stimulus–reaction idea based on a real car-following data set. Tuning the controller is achieved by using the linear quadratic regulator gains in the fuzzy scaling gains. Considering the reaction delay enables the controller to be used in an advanced driver assistance system to obtain simultaneously a higher degree of safety, greater energy saving and more freedom for the driver. Fewer errors and more optimality in the results demonstrated the better performance of the proposed control system in comparison with those of a real driver and other controllers.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Aerospace Engineering

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research on vehicle carrying efficiency of three-lane expressway based on DEA method;Transportation Letters;2021-07-11

2. Path planning and robust fuzzy output-feedback control for unmanned ground vehicles with obstacle avoidance;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2020-12-10

3. Development of a Driving Behavior-Based Collision Warning System Using a Neural Network;International Journal of Automotive Technology;2018-09-12

4. A novel multi-parameter coordinated shift control strategy for an automated manual transmission based on fuzzy inference;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2016-08-29

5. An adaptive framework to enhance microscopic traffic modelling: an online neuro-fuzzy approach;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2016-08-05

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