Traffic congestion in urban areas has become a critical problem that municipal governments cannot overlook. Meanwhile, mixed traffic systems containing both autonomous and human-driven electric vehicles ramp up the challenge for traffic management in urban areas. Although numerous researchers have proposed traffic control heuristics to alleviate traffic congestion problems in the recent literature, scant research has addressed the joint problems of route and charging strategies for electric vehicles along with urban traffic congestion prevention. Accordingly, this work tackles the complex task of traffic management in urban areas during peak periods by using practical congestion prevention strategies that consider the characteristics of mixed traffic flows and the charging demands of electric vehicle users. Notably, we apply support vector regressions to compute the charging time at each charging point and the traverse time of an electric vehicle at each road segment/intersection, based on historical traffic data. The simulation results reveal that the proposed algorithms are feasible because they can avoid possible occurrences of traffic congestion during rush hours and provide the routes and charging options that are chosen by electric vehicle users.
Traffic congestion in metropolitan areas all over the world has become a critical issue that governments mustdeal with effectively. Traffic congestion during rush hours causes vehicle drivers to arrive late at their destinations,resulting in significant economic losses. Although researchers have proposed solutions to the traffic congestionproblem, little research work has presented a joint route and charging planning strategy for electric vehicles(EVs) that alleviates traffic congestion problems simultaneously. Accordingly, a congestion-preventing route and charging planning mechanism for EVs is proposed in this work to tackle the complicated route and charging optimizationproblems of EVs. The route and charging planning proposed in this work analyzes the information providedby EVs, the charging points, and road traffic information simultaneously, and mediates the traffic jammingby means of a route and charging reservation mechanism. Possible occurrence of traffic congestion is detectedin advance and traffic regulation is carried out by allocating an elastic range to the traveling period for late-bookingEVs, to avoid moving during rush hours. EV owners are also encouraged to provide rideshare services forlate-booking EV users during rush hours. The simulation results reveal that the proposed work can satisfy thepreferred route and charging demands of EV users and alleviate traffic congestion effectively.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
334 Leonard St
Brooklyn, NY 11211
Copyright © 2023 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.