Towards Next Generation of Pedestrian and Connected Vehicle In-the-Loop Research: A Digital Twin Co-Simulation Framework

被引:22
作者
Wang, Zijin [1 ]
Zheng, Ou [1 ]
Li, Liangding [2 ]
Abdel-Aty, Mohamed [1 ]
Cruz-Neira, Carolina [2 ]
Islam, Zubayer [1 ]
机构
[1] Univ Cent Florida, Dept Civil Environm & Construct Engn, Orlando, FL 32816 USA
[2] Univ Cent Florida, Dept Comp Sci, Orlando, FL 32816 USA
来源
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES | 2023年 / 8卷 / 04期
关键词
Digital twins; Legged locomotion; Safety; Connected vehicles; Virtual environments; Solid modeling; Hidden Markov models; Digital twin; connected vehicles; pedestrian; co-simulation; cave automatic virtual environment; AUTONOMOUS VEHICLES; SAFETY BENEFITS; INTELLIGENT; TECHNOLOGY; REALITY; SYSTEM; SPEED;
D O I
10.1109/TIV.2023.3250353
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Digital Twin is an emerging technology that replicates real-world entities into a digital space. It has attracted increasing attention in the transportation field and many researchers are exploring its future applications in the development of Intelligent Transportation System (ITS) technologies. Connected vehicles (CVs) and pedestrians are among the major traffic participants in ITS. However, the usage of Digital Twin in research involving both CV and pedestrian remains largely unexplored. In this study, a Digital Twin framework for CV and pedestrian in-the-loop simulation is proposed. The proposed framework consists of the physical world, the digital world, and data transmission in between. The features for the entities (CV and pedestrian) that need digital twining are divided into external state and internal state, and the attributes in each state are described. We also demonstrate a sample architecture under the proposed Digital Twin framework, which is based on Carla-Sumo Co-simulation and Cave automatic virtual environment (CAVE). A case study that investigates Vehicle-Pedestrian (V2P) warning system is conducted to validate the effectiveness of the presented architecture. The proposed framework is expected to provide guidance to the future Digital Twin research, and the architecture we build can serve as the testbed for further research and development of ITS applications on CV and pedestrians.
引用
收藏
页码:2674 / 2683
页数:10
相关论文
共 52 条
  • [41] Cooperative Method of Traffic Signal Optimization and Speed Control of Connected Vehicles at Isolated Intersections
    Xu, Biao
    Ban, Xuegang Jeff
    Bian, Yougang
    Li, Wan
    Wang, Jianqiang
    Li, Shengbo Eben
    Li, Keqiang
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2019, 20 (04) : 1390 - 1403
  • [42] OpenCDA: An Open Cooperative Driving Automation Framework Integrated with Co-Simulation
    Xu, Runsheng
    Guo, Yi
    Han, Xu
    Xia, Xin
    Xiang, Hao
    Ma, Jiaqi
    [J]. 2021 IEEE INTELLIGENT TRANSPORTATION SYSTEMS CONFERENCE (ITSC), 2021, : 1155 - 1162
  • [43] Intelligent and connected vehicles: Current status and future perspectives
    Yang DianGe
    Jiang Kun
    Zhao Ding
    Yu ChunLei
    Cao Zhong
    Xie ShiChao
    Xiao ZhongYang
    Jiao XinYu
    Wang SiJia
    Zhang Kai
    [J]. SCIENCE CHINA-TECHNOLOGICAL SCIENCES, 2018, 61 (10) : 1446 - 1471
  • [44] Predicting Pedestrian Crossing Intention With Feature Fusion and Spatio-Temporal Attention
    Yang, Dongfang
    Zhang, Haolin
    Yurtsever, Ekim
    Redmill, Keith A.
    Ozguner, Umit
    [J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2022, 7 (02): : 221 - 230
  • [45] Connected vehicle real-time traveler information messages for freeway speed harmonization under adverse weather conditions: Trajectory level analysis using driving simulator
    Yang, Guangchuan
    Ahmed, Mohamed
    Gaweesh, Sherif
    Adomah, Eric
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2020, 146
  • [46] Effects of connected and autonomous vehicle merging behavior on mainline human-driven vehicle
    Yue L.
    Abdel-Aty M.
    Wang Z.
    [J]. Journal of Intelligent and Connected Vehicles, 2022, 5 (01): : 36 - 45
  • [47] Influence of pedestrian-to-vehicle technology on drivers' response and safety benefits considering pre-crash conditions
    Yue, Lishengsa
    Abdel-Aty, Mohamed
    Wu, Yina
    Yuan, Jinghui
    Morris, Morgan
    [J]. TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2020, 73 (73) : 50 - 65
  • [48] Assessment of the safety benefits of vehicles' advanced driver assistance, connectivity and low level automation systems
    Yue, Lishengsa
    Abdel-Aty, Mohamed
    Wu, Yina
    Wang, Ling
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2018, 117 : 55 - 64
  • [49] Evaluating the Safety Impact of Connected and Autonomous Vehicles with Lane Management on Freeway Crash Hotspots Using the Surrogate Safety Assessment Model
    Zhang, Hui
    Hou, Ninghao
    Zhang, Jianhua
    Li, Xuyi
    Huang, Yan
    [J]. JOURNAL OF ADVANCED TRANSPORTATION, 2021, 2021
  • [50] A Novel Prediction Algorithm of Pedestrian Activity Region for Intelligent Vehicle Collision Avoidance System
    Zhao, Baixuan
    Zhang, Xi
    Chen, Hao
    Zhu, Wangwang
    [J]. IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2023, 8 (03): : 2173 - 2183