Title: An intelligent fuzzy-based cascade system for determining safe driving level in vehicle edge computing and its performance evaluation

Authors: Yi Liu; Leonard Barolli

Addresses: Department of Information and Communication Engineering, Fukuoka Institute of Technology (FIT), 3-30-1, Wajiro-Higashi, Higashi-Ku, 811-0295, Fukuoka, Japan ' Department of Information and Communication Engineering, Fukuoka Institute of Technology (FIT), 3-30-1, Wajiro-Higashi, Higashi-Ku, 811-0295, Fukuoka, Japan

Abstract: In vehicular ad hoc networks and internet of vehicles, stress and frustration while driving can negatively impact safe driving. Thus, managing drivers' stress levels is crucial for improving safety. In this work, we introduce an intelligent system based on fuzzy logic (FL) to evaluate safe driving level in a vehicle edge computing (VEC) environment. We implement the proposed system in cascade considering three modules: driver anxiety level (DAL) module, driver mental status (DMS) module and safe driving evaluation level (SDEL) module. We carried out many simulations to evaluate the performance of each module for different parameters. Simulations results show that DAL is good for drivers aged between 30 and 50 years, but it tends to decrease for young drivers less than 30 or older drivers more than 50. While DMS is good when the driving time is shorter.

Keywords: edge computing; vehicular ad hoc networks; VANETs; fuzzy logic; safe driving; IoV.

DOI: 10.1504/IJWGS.2026.154455

International Journal of Web and Grid Services, 2026 Vol.22 No.2, pp.129 - 151

Received: 12 Dec 2025
Accepted: 20 Jan 2026
Published online: 29 Jun 2026 *

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