Society-Centered and DAO-Powered Sustainability in Transportation 5.0: An Intelligent Vehicles Perspective

被引:39
作者
Chen, Yuanyuan [1 ,2 ]
Zhang, Hui [3 ,4 ]
Wang, Fei-Yue [5 ,6 ]
机构
[1] Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
[2] Chinese Acad Sci, Inst Automat, State Key Lab Multimodal Artificial Intelligence S, Beijing 100190, Peoples R China
[3] Beihang Univ, Sch Transportat Sci & Engn, Beijing 100091, Peoples R China
[4] Beihang Univ, Ningbo Inst Technol NIT, Ningbo 315323, Peoples R China
[5] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
[6] Macau Univ Sci & Technol, Inst Engn, Macau 999078, Peoples R China
来源
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES | 2023年 / 8卷 / 04期
基金
中国国家自然科学基金;
关键词
Carbon neutral; Intelligent vehicles; Sustainable development; Logistics; Air pollution; Behavioral sciences; Climate change; Sustainability; intelligent vehicles; parallel transportation system; carbon emission; air pollution; carbon neutrality; green transportation; EMISSIONS; SHANGHAI;
D O I
10.1109/TIV.2023.3264585
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As economic and social activities continue to increase, transportation is increasingly contributing to climate change, air pollution and other environmental damage. The growing concerns about the sustainability of transportation are forcing everyone in this field to think about solutions to keep our mobility environmentally, economically and socially sustainable. To provide a forum for the exchange of ideas and experiences from industry, academia and the public sector, we have recently held a series of seminars and the first Distributed/Decentralized Hybrid Workshop on Sustainability for Transportation and Logistics (DHW-STL), part of Distributed/Decentralized Hybrid Symposia on Sustainability for Transportation and Logistics (DHS-STL), and Distributed/Decentralized Hybrid Conferences on Sustainability for Transportation and Logistics (DHC-STL). This letter provides a brief report of the First DHW-STL and discusses the potentials, possibilities and perspectives driven by Intelligent Vehicles (IV) technologies to achieve sustainable intelligent systems for transportation and logistics.
引用
收藏
页码:2635 / 2638
页数:4
相关论文
共 43 条
[1]   MaLTESE: Large-Scale Simulation-Driven Machine Learning for Transient Driving Cycles [J].
Aithal, Shashi M. ;
Balaprakash, Prasanna .
HIGH PERFORMANCE COMPUTING, ISC HIGH PERFORMANCE 2019, 2019, 11501 :186-205
[2]   Complex economic activities concentrate in large cities [J].
Balland, Pierre-Alexandre ;
Jara-Figueroa, Cristian ;
Petralia, Sergio G. ;
Steijn, Mathieu P. A. ;
Rigby, David L. ;
Hidalgo, Cesar A. .
NATURE HUMAN BEHAVIOUR, 2020, 4 (03) :248-254
[3]   Analysis of Sustainable Transport for Smart Cities [J].
Bamwesigye, Dastan ;
Hlavackova, Petra .
SUSTAINABILITY, 2019, 11 (07)
[4]   Eco-driving: An overlooked climate change initiative [J].
Barkenbus, Jack N. .
ENERGY POLICY, 2010, 38 (02) :762-769
[5]   Public acceptability of personal carbon trading and carbon tax [J].
Bristow, Abigail L. ;
Wardman, Mark ;
Zanni, Alberto M. ;
Chintakayala, Phani K. .
ECOLOGICAL ECONOMICS, 2010, 69 (09) :1824-1837
[6]   Future Directions of Intelligent Vehicles: Potentials, Possibilities, and Perspectives [J].
Cao, Dongpu ;
Wang, Xiao ;
Li, Lingxi ;
Lv, Chen ;
Na, Xiaoxiang ;
Xing, Yang ;
Li, Xuan ;
Li, Ying ;
Chen, Yuanyuan ;
Wang, Fei-Yue .
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2022, 7 (01) :7-10
[7]   Acting as a Decision Maker: Traffic-Condition-Aware Ensemble Learning for Traffic Flow Prediction [J].
Chen, Yuanyuan ;
Chen, Hongyu ;
Ye, Peijun ;
Lv, Yisheng ;
Wang, Fei-Yue .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (04) :3190-3200
[8]   Detecting Traffic Information From Social Media Texts With Deep Learning Approaches [J].
Chen, Yuanyuan ;
Lv, Yisheng ;
Wang, Xiao ;
Li, Lingxi ;
Wang, Fei-Yue .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2019, 20 (08) :3049-3058
[9]   Synergistic effects of the built environment and commuting programs on commute mode choice [J].
Ding, Chuan ;
Cao, Xinyu ;
Wang, Yunpeng .
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2018, 118 :104-118
[10]   Personal carbon trading: A policy ahead of its time? [J].
Fawcett, Tina .
ENERGY POLICY, 2010, 38 (11) :6868-6876