Paper Info
Title
Telematics-Based Traffic Law Enforcement and Network Management System for Connected Vehicles
Abstract
This article introduces a telematics-based traffic law enforcement and management system (SLEM), which leverages connected vehicle and telematics technologies. The system assigns each driver a real-time score that measures her/his driving performance. Using these driver scores, SLEM then adopts a personalized route guidance strategy that favors high-performing drivers by guiding them to less congested routes at the expense of low-performing drivers who are directed to alternative, slower routes. This routing strategy shifts the network traffic distribution pattern from the undesirable user equilibrium pattern to the system optimal pattern. Hence, SLEM not only incentivizes drivers to improve their driving performance but it also provides a mechanism to manage network congestion. A bilevel mathematical program and an efficient solution methodology were developed to derive SLEM's optimal routing strategy. A set of experiments that was conducted to evaluate the performance of SLEM under different operation scenarios showed that the adoption of SLEM's routing strategy reduced travel time during recurrent congestion situations by about 5%.
Year
DOI
Venue
2021
10.1109/JIOT.2021.3063621
IEEE Internet of Things Journal
Keywords
DocType
Volume
Connected vehicles (CVs),driver performance,system optimal (SO) traffic assignment,traffic network management
Journal
8
Issue
ISSN
Citations 
15
2327-4662
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Moahd Alghuson100.34
Khaled Abdelghany2887.99
Ahmed E. Hassan35959287.68