A Survey on Testbench-Based Vehicle-in-the-Loop Simulation Testing for Autonomous Vehicles: Architecture, Principle, and Equipment

被引:2
作者
Cheng, Jingjun [1 ,2 ]
Wang, Zhen [1 ]
Zhao, Xiangmo [1 ]
Xu, Zhigang [1 ]
Ding, Ming [2 ]
Takeda, Kazuya [2 ,3 ]
机构
[1] Changan Univ, Sch Informat Engn, Xian 710064, Peoples R China
[2] Nagoya Univ, Inst Innovat Future Soc, Nagoya 4648601, Japan
[3] Nagoya Univ, Open Innovat Ctr, TierIV Inc, Nagoya 4506610, Japan
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
autonomous vehicles; physical signal stimulations simulation testings; testbenches; vehicle-in-the-loops; SAFETY; VERIFICATION; ENERGY; ENVIRONMENT; VALIDATION; EFFICIENT; PLATFORM; SYSTEMS; DESIGN; MODEL;
D O I
10.1002/aisy.202300778
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Autonomous vehicles (AVs) must be thoroughly tested to ensure safety and reliability before marketing. Simulation-based testing has gained widespread recognition as the essential approach for AV testing by providing sufficient testing scenarios in the virtual environment. Vehicle-in-the-loop (VIL) simulation has the ability to perform comprehensive tests and validations for the AVs' overall behaviors while keeping significant testing accuracy and efficiency through the combination of the virtual scenarios and the physical AV. This article provides an overview of representative studies on testbench-based VIL simulation testing for AVs, mainly focusing on utilizing testbenches to simulate realistic road conditions, and using physical signal stimulation methods and related equipment to generate sensors' physical signals. This article first summarizes current AV testing studies, identifying existing issues and flaws of the state-of-the-art methods and tools. Afterward, the testbench-based VIL is addressed around architecture, principles, advantages, and characteristics. Then, the road condition simulation and the sensor physical signal generation in VIL are discussed in depth from structure, principle, and corresponding advanced equipment. Finally, research gaps between cutting-edge technologies and AV testing applications in industrialization are identified to facilitate future research in this direction. This article comprehensively reviews recent studies of testbench-based vehicle-in-the-loop (VIL) simulation testing for autonomous vehicles from architecture, procedures, characteristics, and advantages. Two essential technologies: road condition simulation and sensor physical signal generation are investigated in detail on structure, principles, equipment, and applications, for assisting researchers in choosing appropriate methods and equipment during VIL testing.image (c) 2024 WILEY-VCH GmbH
引用
收藏
页数:20
相关论文
共 139 条
  • [21] Effect of components on the emulsification characteristic of glucose solution emulsified heavy fuel oil
    Chen, Zhenbin
    Wang, Li
    Wei, Zhilong
    Wang, Yu
    Deng, Jiaojun
    [J]. ENERGY, 2022, 244
  • [22] Optimal design of glucose solution emulsified diesel and its effects on the performance and emissions of a diesel engine
    Chen, Zhenbin
    Li, Kaimian
    Liu, Jun
    Wang, Xiaochen
    Jiang, Shengjun
    Zhang, Chengliang
    [J]. FUEL, 2015, 157 : 9 - 15
  • [23] VeRA: A Simplified Security Risk Analysis Method for Autonomous Vehicles
    Cui, Jin
    Zhang, Biao
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2020, 69 (10) : 10494 - 10505
  • [24] Collaborative Analysis Framework of Safety and Security for Autonomous Vehicles
    Cui, Jin
    Sabaliauskaite, Giedre
    Liew, Lin Shen
    Zhou, Fengjun
    Zhang, Biao
    [J]. IEEE ACCESS, 2019, 7 : 148672 - 148683
  • [25] A review on safety failures, security attacks, and available countermeasures for autonomous vehicles
    Cui, Jin
    Liew, Lin Shen
    Sabaliauskaite, Giedre
    Zhou, Fengjun
    [J]. AD HOC NETWORKS, 2019, 90
  • [26] D?ser T., 2010, P ASME INT MECH ENG, P807, DOI DOI 10.1115/IMECE2010-39959
  • [27] Prediction Performance of Lane Changing Behaviors: A Study of Combining Environmental and Eye-Tracking Data in a Driving Simulator
    Deng, Qi
    Wang, Jiao
    Hillebrand, Kevin
    Benjamin, Christoper Ragenold
    Soeffker, Dirk
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2020, 21 (08) : 3561 - 3570
  • [28] Arbitrary Angle of Arrival in Radar Target Simulation
    Diewald, Axel
    Nuss, Benjamin
    Pauli, Mario
    Zwick, Thomas
    [J]. IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2022, 70 (01) : 513 - 520
  • [29] Radar Target Simulation for Vehicle-in-the-Loop Testing
    Diewald, Axel
    Kurz, Clemens
    Kannan, Prasanna Venkatesan
    Giessler, Martin
    Pauli, Mario
    Gottel, Benjamin
    Kayser, Thorsten
    Gauterin, Frank
    Zwick, Thomas
    [J]. VEHICLES, 2021, 3 (02): : 257 - 271
  • [30] A Survey on Safety-Critical Driving Scenario Generation-A Methodological Perspective
    Ding, Wenhao
    Xu, Chejian
    Arief, Mansur
    Lin, Haohong
    Li, Bo
    Zhao, Ding
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (07) : 6971 - 6988