Title: Vehicle-assisted driving system based on FNN-PID controller

Authors: Yunpeng Li

Addresses: School of Intelligent Manufacturing, Jilin Railway Technology College, Jilin, Jilin, China

Abstract: The rapid development of urban transportation has increased the number of motor vehicles, causing serious traffic congestion and frequent accidents, which challenge the efficiency of transportation systems. To improve autonomous driving performance and relieve traffic pressure, this study proposes a vehicle-assisted driving system combining a fuzzy neural network with a proportional integral derivative controller. The longitudinal control structure is analysed, and controllers at different levels are designed. Experimental results indicate that the maximum overshoot is reduced by 11.4% compared with the traditional proportional integral derivative controller. The rise time and adjustment time decrease by 0.3 s and 0.9 s, and the response stabilises at about 0.5 s with almost no overshoot. In practical road tests, the controller reaches the desired speed within 10 s and maintains a stable following distance, demonstrating strong robustness and effective control performance.

Keywords: fuzzy neural network; assisted driving; fuzzy control; vertical control system; intelligent vehicles.

DOI: 10.1504/IJVICS.2026.152935

International Journal of Vehicle Information and Communication Systems, 2026 Vol.11 No.2, pp.163 - 179

Received: 04 Jul 2024
Accepted: 05 Mar 2025
Published online: 15 Apr 2026 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article