Abstract
Road Traffic Congestion Affects Not Only the Commute Delay but Also a city's overall Social, Economic, and Environmental Growth. Existing Approaches for Road Congestion Mitigation Primarily Adopt a Reactive Approach by Detecting Congestion after It Occurs and Recommending Alternate Routes to the Vehicles, Which Fails to Prevent Congestion Cascading. in Contrast, We Propose a Pervasive Platform Called ProCon that Proactively Infers the Driving Micro-Behaviors that Can Contribute to Congestion Formation and Assist the Drivers in Avoiding Such Maneuvers in Real-Time during the Navigation. Thorough Evaluations over Multiple Real-Life and Simulated Datasets Indicate that ProCon Can Reduce Congestion for More Than 60% of the Scenarios on Average While Significantly Reducing the Travel Time of the Vehicles.
Recommended Citation
D. Das et al., "Early Detection of Driving Maneuvers for Proactive Congestion Prevention," 2024 IEEE International Conference on Pervasive Computing and Communications, PerCom 2024, pp. 135 - 142, Institute of Electrical and Electronics Engineers, Jan 2024.
The definitive version is available at https://doi.org/10.1109/PerCom59722.2024.10494436
Department(s)
Computer Science
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Jan 2024
Comments
Science and Engineering Research Board, Grant ITS/2024/000077