ITSC 2025 Paper Abstract

Paper FR-EA-T44.2

Kimura, Masaki (Chiba University), Shigeo, Shioda (Chiba University)

Analysis of Road Traffic Congestion Considering Individual Differences in Forward Movement Time

Scheduled for presentation during the Regular Session "S44b-Human Factors and Human Machine Interaction in Automated Driving" (FR-EA-T44), Friday, November 21, 2025, 13:50−14:10, Currumbin

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Keywords Trust, Acceptance, and Public Perception of Autonomous Transportation Technologies, Data Analytics and Real-time Decision Making for Autonomous Traffic Management

Abstract

The time it takes for a driver to start moving their vehicle after the preceding vehicle has begun to move (forward movement time) depends on various factors including the driver's driving skills. It is known that differences in the forward movement time among drivers have a significant impact on the occurrence of congestion. This study aims to quantitatively evaluate the effect of variability in forward movement time on traffic congestion using a mathematical model, with the goal of developing congestion mitigation methods utilizing autonomous driving technology. Theoretical analysis and simulation results indicate that the conditions under which congestion occurs are strongly influenced by individual differences in forward movement time. Furthermore, the results obtained in this study show good agreement with congestion data from expressways in Japan.