TY - GEN
T1 - Drive-Charge Dilemma in Electric Mobility
T2 - 5th International Conference on Advanced Communication Technologies and Networking, CommNet 2022
AU - Mahrez, Zineb
AU - Sabir, Fssaid
AU - Saad, Walid
AU - Badidi, Elarbi
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The advent of electric mobility has created new costs that are closely linked to and influenced by the actions and behaviors of electric vehicle (EV) drivers. These include time-, energy-, and risk-related costs that each driver seeks to reduce by adjusting his or her strategy. In this paper, an electric vehicle charging dilemma using a non-cooperative routing game with selfish players is formulated. We assume that an electric vehicle plans a trip from one place to another and, in the process, must choose a specific route, stop at a roadside station, decide on the charging station, and charge its battery by a certain amount. The strategy of EVs to drive or stop depends on factors related to battery level, waiting status at charging stations, availability of charging types, and traffic load both on roads and at stations. The research problem aims to solve the EV driver's dilemma and determine the route that the EV driver must take to optimize his travel cost.' To solve the dilemma, we propose to build a simulation model based on input data obtained from historical records of U.S. government sources, as described in the paper.
AB - The advent of electric mobility has created new costs that are closely linked to and influenced by the actions and behaviors of electric vehicle (EV) drivers. These include time-, energy-, and risk-related costs that each driver seeks to reduce by adjusting his or her strategy. In this paper, an electric vehicle charging dilemma using a non-cooperative routing game with selfish players is formulated. We assume that an electric vehicle plans a trip from one place to another and, in the process, must choose a specific route, stop at a roadside station, decide on the charging station, and charge its battery by a certain amount. The strategy of EVs to drive or stop depends on factors related to battery level, waiting status at charging stations, availability of charging types, and traffic load both on roads and at stations. The research problem aims to solve the EV driver's dilemma and determine the route that the EV driver must take to optimize his travel cost.' To solve the dilemma, we propose to build a simulation model based on input data obtained from historical records of U.S. government sources, as described in the paper.
KW - data analytics
KW - electric vehicles
KW - price of anarchy
KW - routing games
KW - Wardrop equilibrium
UR - http://www.scopus.com/inward/record.url?scp=85146487584&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85146487584&partnerID=8YFLogxK
U2 - 10.1109/CommNet56067.2022.9993902
DO - 10.1109/CommNet56067.2022.9993902
M3 - Conference contribution
AN - SCOPUS:85146487584
T3 - Proceedings - 2022 5th International Conference on Advanced Communication Technologies and Networking, CommNet 2022
BT - Proceedings - 2022 5th International Conference on Advanced Communication Technologies and Networking, CommNet 2022
A2 - El Bouanani, Faissal
A2 - Ayoub, Fouad
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 December 2022 through 14 December 2022
ER -