ITSC 2025 Paper Abstract

Paper TH-LM-T29.6

KANG, MINJI (University of Seoul), Do, Woo Seok (Keimyung University), Kwon, Oh Hoon (Keimyung University), Park, Shin Hyoung (University of Seoul)

An Empirical Analysis of Driver Behavioral Changes Following Urban Speed Limit Adjustments

Scheduled for presentation during the Regular Session "S29a-Human Factors and Human Machine Interaction in Automated Driving" (TH-LM-T29), Thursday, November 20, 2025, 12:10−12:30, 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 Human-Machine Interaction Systems for Enhanced Driver Assistance and Safety, AI, Machine Learning for Real-time Traffic Flow Prediction and Management, Data Analytics and Real-time Decision Making for Autonomous Traffic Management

Abstract

Roads have speed limits to ensure safety by restricting the maximum speed at which vehicles can travel. These speed limits are established based on road environmental conditions to reduce speed disparities between vehicles and decrease the risk of accidents caused by speeding. This study aims to comprehensively analyze how changes in speed limits on urban roads affect driver behavior. In particular, we evaluated the effects of speed limit policies from multiple perspectives by integrating compliance rate analysis from a macroscopic viewpoint with driver behavior analysis from a microscopic perspective. For analysis, we utilized individual operational data from Digital Tachograph (DTG) commercial vehicles across 20,881 road sections in Seoul's standard node-link network. We examined overall policy impacts by analyzing compliance rates by speed limit change type (6,954 sections with decreased limits, 1,620 sections with increased limits, and 8,288 sections with maintained limits).The results revealed that the larger the downward adjustment of the speed limit, the lower the driver compliance rate, and confirmed a significant relationship between overall compliance rate changes and individual driver behavior changes. These findings suggest that future speed limit policies should adopt a gradual approach that considers the magnitude of change and road characteristics. a limitation of this research is that the DTG data used for analysis is limited to commercial vehicles, which may exhibit driving behavior differences compared to general drivers.