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Zhang, Xu 
ORCID: https://orcid.org/0000-0001-6557-6607, Xia, Xu, Liu, Shuohan, Cao, Yue, Li, June and Guo, Weisi
(2022)
An integrated framework on autonomous-EV charging and autonomous valet parking (AVP) management system.
IEEE Transactions on Transportation Electrification, 8 (2).
pp. 2836-2852.
ISSN 2332-7782
Abstract
Autonomous vehicles (AVs) transform traditional commuting by decreasing congestion, improving road safety, and naturally integrate better with electric controls for flexible implementation of autonomous driving technologies. Indeed, electric-powered AVs or autonomous electric vehicles (AEVs) are benefiting each other in many aspects. While autonomy brings great efficiency in driving as well as battery use, electric vehicles (EVs) require less maintenance and drastically cut fuel costs. With AVs, a pivotal concern is within the realm of long-range autonomous valet parking (LAVP), such as diverse customer demands on parking (or drop-off/pick-up) for various journey planning. On the other hand, electric-powered AVs are typically with limited cruising range, and locating convenient charging services are also among the major impediments. As of yet, recent studies have started to investigate EV charging and LAVP in isolation as they rarely consider a joint optimization on user trip and energy refueling. Rather, we target in this work the integration of vehicle charging with autonomy in the sense of a systemic approach. Specifically, we propose an integrated AEV charging and LAVP management scheme, to resolve critical decision-making on convenient charging and parking management upon customer requirements during their journeys. The proposed scheme jointly considers charging reservations as well as parking duration at car parks (CPs), aiming to enable accurate predictions on future charging (and parking) states at CPs. Results show the advantage of our proposal over benchmarks, in terms of enhanced customer experiences in traveling period, as well as charging performances at both AEV and CP sides. Particularly, effective load balancing can be achieved across the network regarding the amount of charged as well as parked vehicles.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | autonomous vehicle (av),charging management,long-range autonomous valet parking (lavp),trip planning,automotive engineering,transportation,energy engineering and power technology,electrical and electronic engineering ,/dk/atira/pure/subjectarea/asjc/2200/2203 |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Data Science and AI |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 01 Feb 2024 03:08 |
| Last Modified: | 10 Dec 2024 01:43 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/94331 |
| DOI: | 10.1109/TTE.2022.3145198 |
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