Citation

Mattas K, Botzoris G, Papadopoulos B. J. Traffic Transp. Eng. Engl. Ed. 2021; 8(4): 568-581.

Copyright

(Copyright © 2021, Periodical Offices of Chang'an University, Publisher Elsevier Publishing)

DOI

10.1016/j.jtte.2020.12.006

PMID

unavailable

Abstract

Vehicle automation holds significant opportunities in the efforts for safer road traffic. Even lower levels of automation like adaptive cruise control (ACC) systems have great potential. Apart from safety benefits, ACC systems could improve the efficiency of traffic networks. However, contemporary ACC systems are designed to be comfortable, but not guaranteed to be safe. Moreover, according to recent literature studies, they have been found to be conservative and string unstable, with traffic oscillations being amplified when traveling downstream. Due to those issues, severe problems can arise in the traffic flow and the efficiency of road traffic networks may deteriorate. Automating the vehicles' longitudinal movement through ADAS systems offers new opportunities in improving the safety conditions on the roads by designing more consistent controllers. In the present paper, a fuzzy controller is developed for automated longitudinal vehicle control. The controller is validated through simulation and real-world data of ACC systems that are currently available in the market. Using fuzzy surrogate safety metrics, the controller becomes aware of the safety level of any situation and can react properly. Moreover, the driving behavior is efficient for the traffic flow, comfortable and string stable, dampening traffic shockwaves that travel upstream.

RESULTS prove the robustness of the proposed solution.

Language: en

Keywords

Adaptive cruise control; Fuzzy inference system; Road safety; Traffic simulation; Vehicle automation