Leveraging Intelligent Transportation Systems and Smart Vehicles Using Crowdsourcing: An Overview

被引:26
|
作者
Lucic, Michael C. [1 ]
Wan, Xiangpeng [1 ]
Ghazzai, Hakim [1 ]
Massoud, Yehia [1 ]
机构
[1] Stevens Inst Technol, Sch Syst & Enterprises, Hoboken, NJ 07030 USA
来源
SMART CITIES | 2020年 / 3卷 / 02期
关键词
automatic sensing; mobile crowdsourcing; ITS; smart cities; smart vehicles; spatial crowdsourcing; INTERNET; PRIVACY; NAVIGATION; FRAMEWORK;
D O I
10.3390/smartcities3020018
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The current and expected future proliferation of mobile and embedded technology provides unique opportunities for crowdsourcing platforms to gather more user data for making data-driven decisions at the system level. Intelligent Transportation Systems (ITS) and Vehicular Social Networks (VSN) can be leveraged by mobile, spatial, and passive sensing crowdsourcing techniques due to improved connectivity, higher throughput, smart vehicles containing many embedded systems and sensors, and novel distributed processing techniques. These crowdsourcing systems have the capability of profoundly transforming transportation systems for the better by providing more data regarding (but not limited to) infrastructure health, navigation pathways, and congestion management. In this paper, we review and discuss the architecture and types of ITS crowdsourcing. Then, we delve into the techniques and technologies that serve as the foundation for these systems to function while providing some simulation results to show benefits from the implementation of these techniques and technologies on specific crowdsourcing-based ITS systems. Afterward, we provide an overview of cutting edge work associated with ITS crowdsourcing challenges. Finally, we propose various use-cases and applications for ITS crowdsourcing, and suggest some open research directions.
引用
收藏
页码:341 / 360
页数:20
相关论文
共 50 条
  • [41] Digital Twin Consensus for Blockchain-Enabled Intelligent Transportation Systems in Smart Cities
    Liao, Siyi
    Wu, Jun
    Bashir, Ali Kashif
    Yang, Wu
    Li, Jianhua
    Tariq, Usman
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (11) : 22619 - 22629
  • [42] Leveraging Advanced Technologies for (Smart) Transportation Planning: A Systematic Review
    Son, Heejoo
    Jang, Jinhyeok
    Park, Jihan
    Balog, Akos
    Ballantyne, Patrick
    Kwon, Heeseo Rain
    Singleton, Alex
    Hwang, Jinuk
    SUSTAINABILITY, 2025, 17 (05)
  • [43] Framework to process vehicles uncertain locations for intelligent transportation
    Abdalla, Mohammed
    Islam, Abdullah
    Ali, Mohamed
    Hendawi, Abdeltawab
    INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS, 2024, 18 (03): : 2097 - 2113
  • [44] Privacy and Security of Connected Vehicles in Intelligent Transportation System
    Jolfaei, Alireza
    Kant, Krishna
    2019 49TH ANNUAL IEEE/IFIP INTERNATIONAL CONFERENCE ON DEPENDABLE SYSTEMS AND NETWORKS - SUPPLEMENTAL VOL (DSN-S), 2019, : 9 - 10
  • [45] Distributed perception and model inference with intelligent connected vehicles in smart cities
    Li, Chunhai
    Wang, Siming
    Li, Xiaohuan
    Zhao, Feng
    Yu, Rong
    AD HOC NETWORKS, 2020, 103
  • [46] Artificial Co-Drivers as a Universal Enabling Technology for Future Intelligent Vehicles and Transportation Systems
    Da Lio, Mauro
    Biral, Francesco
    Bertolazzi, Enrico
    Galvani, Marco
    Bosetti, Paolo
    Windridge, David
    Saroldi, Andrea
    Tango, Fabio
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2015, 16 (01) : 244 - 263
  • [47] A security framework for QaaS model in intelligent transportation systems
    Rawashdeh, Majdi
    Alshboul, Yazan
    Al Zamil, Mohammed G. H.
    Samarah, Samer
    Alnusair, Awny
    Hossain, M. Shamim
    MICROPROCESSORS AND MICROSYSTEMS, 2022, 90
  • [48] Blockchain-based Reputation for Intelligent Transportation Systems
    Hirtan, Liviu-Adrian
    Dobre, Ciprian
    Gonzalez-Velez, Horacio
    SENSORS, 2020, 20 (03)
  • [49] Emergency Messages Dissemination Challenges Through Connected Vehicles for Efficient Intelligent Transportation Systems: A Review
    Mujahid, Muhammad Akram
    Bakar, Kamalrulnizam Abu
    Darwish, Tasneem S. J.
    Zuhra, Fatima Tul
    Ejaz, Muhammad Aamer
    Sahar, Gul
    BAGHDAD SCIENCE JOURNAL, 2020, 17 (04) : 1304 - 1319
  • [50] A framework for evaluating deployment strategies for intelligent transportation systems
    Tsao, HSJ
    ITS JOURNAL, 2000, 6 (02): : 141 - 173