Risk Assessment in the Context of Dynamic Reconfiguration of Level of Driving Automation in Highly Automated Vehicles

被引:0
作者
Panagiotopoulos, Ilias E. [1 ]
Karathanasopoulou, Konstantina N. [1 ]
Dimitrakopoulos, George J. [1 ]
机构
[1] Harokopio Univ Athens, Dept Informat & Telemat, Kallithea, Greece
来源
2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI 2021) | 2021年
关键词
automated vehicles; level of automation; risk assessment; failure mode and effect analysis; AUTONOMOUS VEHICLES;
D O I
10.1109/CSCI54926.2021.00352
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Advanced Driver Assistance Systems (ADAS) constitute a field that continues to attract immense research BY promising significant advantages and novelties to the manner in which we drive vehicles, facilitating several of the driver's operations and the passengers' journey, as well as protecting the vehicle from undesired situations. With the advent of Automated Vehicles (AVs), the research and development in ADAS will be intensified, so as to holistically undertake the responsibility of getting a vehicle safely from one point to another point. Risk assessment and reliability analysis are a cornerstone of the evaluation of ADAS and their probability of success in completing a prescribed mission of an AV. In this paper, the classical Failure Mode and Effect Analysis (FMEA) technique is applied to investigate the risk assessment regarding real time adaptation of the Level of Driving Automation (LoDA) in AVs. This analysis is crucial as high risky events are evolved in the transition mode of LoDA related to hardware, sensors, software failures, front obstacles or crashes, dense traffic congestion, adverse weather or road conditions, etc. Through this analysis, an efficient approach is developed by exploring the reliability of the LoDA transition in an AV operation and its impact on the behaviour of both the AV and the driver.
引用
收藏
页码:1868 / 1873
页数:6
相关论文
共 39 条
  • [21] Driving Decisions for Autonomous Vehicles in Intersection Environments: Deep Reinforcement Learning Approaches with Risk Assessment
    Yu, Wangpengfei
    Qian, Yubin
    Xu, Jiejie
    Sun, Hongtao
    Wang, Junxiang
    WORLD ELECTRIC VEHICLE JOURNAL, 2023, 14 (04):
  • [22] ISO/SAE 21434-Based Risk Assessment of Security Incidents in Automated Road Vehicles
    Puellen, Dominik
    Liske, Jonas
    Katzenbeisser, Stefan
    COMPUTER SAFETY, RELIABILITY, AND SECURITY (SAFECOMP 2021), 2021, 12852 : 82 - 97
  • [23] Occlusion-Aware Risk Assessment and Driving Strategy for Autonomous Vehicles Using Simplified Reachability Quantification
    Park, Hyunwoo
    Choi, Jongseo
    Chin, Hyuntai
    Lee, Sang-Hyun
    Baek, Doosan
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2023, 8 (12) : 8486 - 8493
  • [24] Vehicle Assisted Driving Behavior Decision-Making Based on Dynamic Risk Assessment
    Liu, Zhongjie
    Zhao, Zhiguo
    Yu, Qin
    Qiche Gongcheng/Automotive Engineering, 2024, 46 (11): : 2005 - 2016
  • [25] A methodology for architectural-level risk assessment using dynamic metrics
    Yacoub, SM
    Ammar, HH
    Robinson, T
    11TH INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING, PROCEEDINGS, 2000, : 210 - 221
  • [26] Risk assessment criteria for utilizing dynamic line rating in presence of electric vehicles uncertainty
    Hajeforosh, SeyedeFatemeh
    Bakhtiari, Hamed
    Bollen, Math
    ELECTRIC POWER SYSTEMS RESEARCH, 2022, 212
  • [27] Quantitative risk assessment for connected automated Vehicles: Integrating improved STPA-SafeSec and Bayesian network
    Liu, Qi
    Sun, Ke
    Liu, Wenqi
    Li, Yufeng
    Zheng, Xiangyu
    Cao, Chenhong
    Li, Jiangtao
    Qin, Wutao
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2025, 253
  • [28] Remote driving as the Failsafe: Qualitative investigation of Users' perceptions and requirements towards the 5G-enabled Level 4 automated vehicles
    Li, Shuo
    Zhang, Yanghanzi
    Blythe, Phil
    Edwards, Simon
    Ji, Yanjie
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2024, 100 : 211 - 230
  • [29] Dynamic Risk Assessment Enabling Automated Interventions for Medical Cyber-Physical Systems
    Leite, Fabio L., Jr.
    Schneider, Daniel
    Adler, Rasmus
    COMPUTER SAFETY, RELIABILITY, AND SECURITY, SAFECOMP 2019, 2019, 11698 : 216 - 231
  • [30] ESTIMATED ASSESSMENT OF THE POTENTIAL IMPACT OF DRIVER-ASSISTANCE SYSTEMS USED IN AUTOMATED VEHICLES ON THE LEVEL OF ROAD SAFETY IN POLAND
    Pedzierska, Malgorzata
    Pawlak, Piotr
    Kruszewski, Mikolaj
    Jamson, Samantha
    TRANSPORT PROBLEMS, 2020, 15 (04) : 325 - 338