华南理工大学学报(自然科学版) ›› 2025, Vol. 53 ›› Issue (6): 104-118.doi: 10.12141/j.issn.1000-565X.240119

• 智慧交通系统 • 上一篇    下一篇

共享自动驾驶汽车的多阶城市影响综述

钟绍鹏1,2,3(), 刘骜2, 翟君诺2, 范美含4, 李茜瑶5(), 林原6, 李振华7   

  1. 1.大连理工大学 经济管理学院,辽宁 大连 116024
    2.大连理工大学 交通运输系,辽宁 大连 116024
    3.杭州国际城市学研究中心 浙江省城市治理研究中心,浙江 杭州 311121
    4.大连东软信息学院 信息与商务管理学院,辽宁 大连 116023
    5.交通运输部公路科学研究院 国家智能交通系统工程技术研究中心,北京 100088
    6.大连理工大学 公共管理学院,辽宁 大连 116024
    7.交通运输部公路科学研究院 车路一体智能交通全国重点实验室,北京 100088
  • 收稿日期:2024-03-13 出版日期:2025-06-10 发布日期:2024-12-06
  • 通信作者: 李茜瑶 E-mail:szhong@dlut.edu.cn;lixy@itsc.cn
  • 作者简介:钟绍鹏(1982—),男,博士,教授,主要从事共享自动驾驶车辆与城市可持续发展研究。E-mail: szhong@dlut.edu.cn
  • 基金资助:
    车路一体智能交通全国重点实验室开放基金课题(2024-B002);国家自然科学基金项目(71971038);山东省重点研发计划项目(2023CXPT005);中国工程院重大咨询研究项目子课题(2023-JB-10-04)

Review of Multi-Level Urban Impacts of Shared Autonomous Vehicles

ZHONG Shaopeng1,2,3(), LIU Ao2, ZHAI Junnuo2, FAN Meihan4, LI Xiyao5(), LIN Yuan6, LI Zhenhua7   

  1. 1.School of Economics and Management,Dalian University of Technology,Dalian 116024,Liaoning,China
    2.Department of Transportation and Logisctics,Dalian University of Technology,Dalian 116024,Liaoning,China
    3.International Urbanology Research Center,Center for Urban Governance of Zhejiang,Hangzhou 311121,Zhejiang,China
    4.School of Information and Business Management,Dalian Neusoft University of Information,Dalian 116023,Liaoning,China
    5.Engineering and Technology,Research Institute of Highway Ministry of Transport,Beijing 100088,China
    6.School of Public Administration and Policy,Dalian University of Technology,Dalian 116024,Liaoning,China
    7.State Key Lab of Intelligent Transportation System,Research Institute of Highway Ministry of Transport,Beijing 100088,China
  • Received:2024-03-13 Online:2025-06-10 Published:2024-12-06
  • Contact: LI Xiyao E-mail:szhong@dlut.edu.cn;lixy@itsc.cn
  • Supported by:
    the National Natural Science Foundation of China(71971038);the Key R & D Program of Shandong Province(2023CXPT005);the Sub-Project of the Major Consulting Research Project of the Chinese Academy of Engineering(2023-JB-10-04)

摘要:

为深入理解共享自动驾驶汽车(SAVs)的引入对城市可能产生的影响,并推动城市交通系统的可持续发展,围绕SAVs的多阶影响进行了全面回顾和系统分析,旨在总结以往研究的主要贡献和存在的缺陷,并提出未来研究的可能方向。综述结果表明,现有研究主要集中于SAVs对交通系统的短期影响,包括对居民出行行为与道路交通流等方面的探讨;然而,对于SAVs的长期影响,特别是对城市可达性、环境与能源的研究相对较少。与此同时,尽管已有研究揭示了SAVs可能带来的负面效应,例如对环境或可达性的潜在不利影响,但鲜有研究提出具有针对性和实效性的发展策略。此外,在研究方法方面,现有研究主要依赖定性分析或独立的交通需求模型进行推演和模拟,研究结果的可靠性存在一定局限性。未来研究应开发土地利用与交通整合模型,并将其与数据驱动的方法相结合,以更精确、全面和系统地刻画SAVs引入对城市土地利用、环境与能源的长期(负面)影响,并提出针对性的发展策略和应对措施,以优化SAVs的应用效果,减少其潜在负面影响,推动城市交通系统向高效、智能和可持续的方向发展。

关键词: 智能交通, 共享自动驾驶汽车, 土地利用与交通, 城市影响, 可达性

Abstract:

To gain a deeper understanding of the potential impacts of Shared Autonomous Vehicles (SAVs) on urban and promote the sustainable development of urban transportation systems, this paper conducted a comprehensive review and systematic analysis of the multi-level impacts of SAVs. The aim is to summarize the main contributions and shortcomings of previous studies and propose possible directions for future research. The review findings indicate that existing studies primarily focus on the short-term impacts of SAVs on the transportation system, including residents’ travel behavior and road traffic flow. However, there is relatively little research on the long-term impacts of SAVs, particularly concerning urban accessibility, environment, and energy. While some studies have revealed potential negative effects of SAVs, such as adverse impacts on the environment or accessibility, few have proposed targeted and effective development strategies. Additionally, in terms of methods, existing studies mainly rely on qualitative analysis or independent transportation demand models for projections and simulations, which have certain limitations regarding the reliability of the results. Future research should focus on developing integrated land use and transportation models combined with data-driven approaches to more precisely, comprehensively, and systematically characterize the long-term (negative) impacts of introducing SAVs on urban land use, the environment, and energy consumption. Additionally, targeted development strategies and responsive measures should be proposed to optimize the effectiveness of SAV deployment, mitigate potential adverse effects, and promote the evolution of urban transportation systems toward greater efficiency, intelligence, and sustainability.

Key words: intelligent transportation, shared autonomous vehicle, land use and transportation, urban impact, accessibility

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