Data-Driven Intelligent Transportation Systems: A Survey

被引:1152
作者
Zhang, Junping [1 ]
Wang, Fei-Yue [3 ]
Wang, Kunfeng
Lin, Wei-Hua [4 ]
Xu, Xin [5 ]
Chen, Cheng [2 ]
机构
[1] Fudan Univ, Shanghai Key Lab Intelligent Informat Proc, Sch Comp Sci, Shanghai 200433, Peoples R China
[2] Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100190, Peoples R China
[3] Univ Arizona, Tucson, AZ 85719 USA
[4] Univ Arizona, Dept Syst & Ind Engn, Tucson, AZ 85721 USA
[5] Natl Univ Def Technol, Inst Automat, Coll Mechatron & Automat, Changsha 410073, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Data mining; data-driven intelligent transportation systems ((DITS)-I-2); machine learning; microblog; mobility; visual analytics; visualization; PEDESTRIAN-DETECTION; NIGHT-VISION; COLLISION-AVOIDANCE; VEHICLE DETECTION; TIME-ESTIMATION; CELL PHONES; ASSISTANCE; TRACKING; VIDEO; PERFORMANCE;
D O I
10.1109/TITS.2011.2158001
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
For the last two decades, intelligent transportation systems (ITS) have emerged as an efficient way of improving the performance of transportation systems, enhancing travel security, and providing more choices to travelers. A significant change in ITS in recent years is that much more data are collected from a variety of sources and can be processed into various forms for different stakeholders. The availability of a large amount of data can potentially lead to a revolution in ITS development, changing an ITS from a conventional technology-driven system into a more powerful multifunctional data-driven intelligent transportation system ((DITS)-I-2): a system that is vision, multisource, and learning algorithm driven to optimize its performance. Furthermore, (DITS)-I-2 is trending to become a privacy-aware people-centric more intelligent system. In this paper, we provide a survey on the development of (DITS)-I-2, discussing the functionality of its key components and some deployment issues associated with (DITS)-I-2. Future research directions for the development of (DITS)-I-2 is also presented.
引用
收藏
页码:1624 / 1639
页数:16
相关论文
共 50 条
  • [1] A Survey on Data-Driven Learning for Intelligent Network Intrusion Detection Systems
    Abdelmoumin, Ghada
    Whitaker, Jessica
    Rawat, Danda B.
    Rahman, Abdul
    ELECTRONICS, 2022, 11 (02)
  • [2] Data poisoning attacks in intelligent transportation systems: A survey
    Wang, Feilong
    Wang, Xin
    Ban, Xuegang
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2024, 165
  • [3] Big Data Analytics in Intelligent Transportation Systems: A Survey
    Zhu, Li
    Yu, Fei Richard
    Wang, Yige
    Ning, Bin
    Tang, Tao
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2019, 20 (01) : 383 - 398
  • [4] Empowering Learning through Intelligent Data-Driven Systems
    Aldriwish, Khalid Abdullah
    ENGINEERING TECHNOLOGY & APPLIED SCIENCE RESEARCH, 2024, 14 (01) : 12844 - 12849
  • [5] Data-driven occupant actions prediction to achieve an intelligent building
    Pereira, Pedro F.
    Ramos, Nuno M. M.
    Simoes, M. Lurdes
    BUILDING RESEARCH AND INFORMATION, 2020, 48 (05) : 485 - 500
  • [6] Data-driven approaches in FinTech: a survey
    Tian, Xin
    He, Jing Selena
    Han, Meng
    INFORMATION DISCOVERY AND DELIVERY, 2021, 49 (02) : 123 - 135
  • [7] Code analysis for intelligent cyber systems: A data-driven approach
    Coulter, Rory
    Han, Qing-Long
    Pan, Lei
    Zhang, Jun
    Xiang, Yang
    INFORMATION SCIENCES, 2020, 524 (46-58) : 46 - 58
  • [8] Data-driven intelligent method for detection of electricity theft
    Chen, Junde
    Nanehkaran, Y. A.
    Chen, Weirong
    Liu, Yajun
    Zhang, Defu
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2023, 148
  • [9] Computer Vision Applications in Intelligent Transportation Systems: A Survey
    Dilek, Esma
    Dener, Murat
    SENSORS, 2023, 23 (06)
  • [10] A Survey on Data-driven Network Intrusion Detection
    Chou, Dylan
    Jiang, Meng
    ACM COMPUTING SURVEYS, 2022, 54 (09)