Quality-of-Service Aware Battery Swapping Navigation and Pricing for Autonomous Mobility-on-Demand System

被引:23
|
作者
Ding, Zhaohao [1 ]
Tan, Wenrui [1 ]
Lu, Wenbing [1 ]
Lee, Wei-Jen [2 ]
机构
[1] North China Elect Power Univ, Sch Elect & Elect Engn, Beijing 102206, Peoples R China
[2] Univ Texas Arlington, Energy Syst Res Ctr, Arlington, TX 76019 USA
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Batteries; Pricing; Quality of service; Navigation; Optimization; Costs; Routing; Autonomous mobility-on-demand (AMoD); battery swapping pricing; electric vehicles (EVs); queue; ELECTRIC VEHICLES; CHARGING STATIONS; OPERATION; TRANSPORTATION; NETWORK; MODEL;
D O I
10.1109/TII.2022.3172985
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The autonomous mobility-on-demand (AMoD) system is regarded as a promising shared mobility method for the sustainable transportation system. In addition, battery swapping could become an efficient energy-refueling means for electric vehicles (EVs). The quality-of-service aware battery swapping price determined by the battery swapping stations (BSSs) considers the interaction between AMoD fleet and BSSs, which is formulated as a bilevel optimization problem in this article. The interdependence between two systems is bridged by the swapping price that is both time-varying and location-varying. In the upper level, the swapping pricing is optimized to reflect the battery inventory so that the EV fleet could be navigated for the BSS strategically, the queue time would be reduced consequently. BSS operator optimizes swapping pricing scheme and battery charging management with the objective of minimizing the cost induced by the queue process and battery charging. In the lower level, a unified network flow model incorporating queue procedure in BSSs is proposed in order to characterize the operational decision of AMoD fleet. The AMoD operator develops fleet scheduling strategies with the objective of maximizing the AMoD system profit. An iteration-based algorithm is applied to attain the results and the effectiveness of the algorithm is validated by the real-world data from New York.
引用
收藏
页码:8247 / 8257
页数:11
相关论文
共 31 条
  • [1] Integrated Operation Model for Autonomous Mobility-on-Demand Fleet and Battery Swapping Station
    Ding, Zhaohao
    Tan, Wenrui
    Lee, Wei-Jen
    Pan, Xuyang
    Gao, Shiqiao
    IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2021, 57 (06) : 5593 - 5602
  • [2] Joint Pricing and Rebalancing of Autonomous Mobility-on-Demand Systems
    Wollenstein-Betech, Salomon
    Paschalidis, Ioannis Ch
    Cassandras, Christos G.
    2020 59TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2020, : 2573 - 2578
  • [3] Deep Reinforcement Learning-Based Charging Pricing for Autonomous Mobility-on-Demand System
    Lu, Ying
    Liang, Yanchang
    Ding, Zhaohao
    Wu, Qiuwei
    Ding, Tao
    Lee, Wei-Jen
    IEEE TRANSACTIONS ON SMART GRID, 2022, 13 (02) : 1412 - 1426
  • [4] Charging Pricing for Autonomous Mobility-on-demand Fleets Based on Game Theory
    Jiawei Wang
    Yujie Sheng
    Huaichang Ge
    Xiang Bai
    Jia Su
    Qinglai Guo
    Hongbin Sun
    Journal of Modern Power Systems and Clean Energy, 2024, 12 (06) : 2006 - 2018
  • [5] Charging Pricing for Autonomous Mobility-on-Demand Fleets Based on Game Theory
    Wang, Jiawei
    Sheng, Yujie
    Ge, Huaichang
    Bai, Xiang
    Su, Jia
    Guo, Qinglai
    Sun, Hongbin
    JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2024, 12 (06) : 2006 - 2018
  • [6] Multi-Class Autonomous Vehicles for Mobility-on-Demand Service
    Pendleton, Scott Drew
    Andersen, Hans
    Shen, Xiaotong
    Eng, You Hong
    Zhang, Chen
    Kong, Hai Xun
    Leong, Wei Kang
    Ang, Marcelo H., Jr.
    Rus, Daniela
    2016 IEEE/SICE INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION (SII), 2016, : 204 - 211
  • [7] Revenue Uncertainty Analysis for Autonomous Mobility-on-Demand System
    Sun, Yimeng
    Huang, Yuan
    Ding, Zhaohao
    2022 IEEE/IAS INDUSTRIAL AND COMMERCIAL POWER SYSTEM ASIA (I&CPS ASIA 2022), 2022, : 631 - 636
  • [8] A Congestion-aware Routing Scheme for Autonomous Mobility-on-Demand Systems
    Salazar, Mauro
    Tsao, Matthew
    Aguiar, Izabel
    Schiffer, Maximilian
    Pavone, Marco
    2019 18TH EUROPEAN CONTROL CONFERENCE (ECC), 2019, : 3040 - 3046
  • [9] Autonomous Golf Cars for Public Trial of Mobility-on-Demand Service
    Pendleton, Scott
    Uthaicharoenpong, Tawit
    Chong, Zhuang Jie
    Fu, Guo Ming James
    Qin, Baoxing
    Liu, Wei
    Shen, Xiaotong
    Weng, Zhiyong
    Kamin, Cody
    Ang, Mark Adam
    Kuwae, Lucas Tetsuya
    Marczuk, Katarzyna Anna
    Andersen, Hans
    Feng, Mengdan
    Butron, Gregory
    Chong, Zhuang Zhi
    Ang, Marcelo H., Jr.
    Frazzoli, Emilio
    Rus, Daniela
    2015 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2015, : 1164 - 1171
  • [10] Autonomous Personal Mobility Scooter for Multi-Class Mobility-on-Demand Service
    Andersen, Hans
    Eng, You Hong
    Leong, Wei Kang
    Zhang, Chen
    Kong, Hai Xun
    Pendleton, Scott
    Ang, Marcelo H., Jr.
    Rus, Daniela
    2016 IEEE 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2016, : 1753 - 1760