Abstract
Individual driving behavior is a pivotal element that shapes the overall traffic dynamics in a city. In this work, we study and analyze the complex web of relationships between individual driving behaviors and their impact on the overall traffic dynamics of a smart city with two primary objectives: first, understanding the spatial interaction between individual vehicles and their impact on each other, and second, finding anomalous driving behaviors, which lead to congestion and traffic incidents. Specifically, we introduce an overarching modular framework investigating human factors of driver characteristics, vehicle attributes, geographical terrain surrounding the road infrastructure, and environmental conditions. Analyzing driving maneuvers considering such diverse factors emphasizes the removal of the bias in driving behavior prediction. Our study serves as an essential foundation to delve into the problem of traffic dynamics in a city and further motivates the need for a deeper understanding of the correlation between driving behavior and traffic management.
Recommended Citation
D. Das et al., "Pervasive Sensing to Correlate Vehicle Driving Behavior with City-Scale Traffic Dynamics," IEEE Pervasive Computing, Institute of Electrical and Electronics Engineers; Computer Society, Jan 2025.
The definitive version is available at https://doi.org/10.1109/MPRV.2025.3555872
Department(s)
Computer Science
Publication Status
Early Access
International Standard Serial Number (ISSN)
1558-2590; 1536-1268
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2025 Institute of Electrical and Electronics Engineers; Computer Society, All rights reserved.
Publication Date
01 Jan 2025
