Safety Oriented State Transitions in Level 3 Automated Driving Systems: A General Framework

被引:0
|
作者
Huang, Chao [1 ]
Liu, Yahui [1 ]
Li, Liang [1 ]
Chen, Zheng [2 ]
机构
[1] Tsinghua Univ, Dept Automot Engn, State Key Lab Automot Safety & Energy, Beijing, Peoples R China
[2] Ningbo Univ Technol, Sch Sci, Ningbo, Peoples R China
基金
中国国家自然科学基金;
关键词
COLLISION-AVOIDANCE;
D O I
10.1109/icarm.2019.8833761
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
On the road to fully autonomous driving, the level 3 (L3) automated driving systems (ADS) appears to be a more realistic choice. However, this is also a difficult problem in that the ADS and the driver are convoluted together, making control of the system difficult. Another is the safety and responsibility partition concerns, hindering commercialization of the system. Under this circtunstance, the research conducted in this paper aims to establish a safety oriented state transition framework for the L3 ADS, utilizing an event based dynamic hazard and risk assessment (DHAKA) framework. In doing so, the system would be able to maintain a state of acceptable risk or loss even facing unexpectable changes. More importantly, the reason would be traceable when certain accident happens, and the responsibility partition would be unambiguous under this architecture.
引用
收藏
页码:918 / 923
页数:6
相关论文
共 50 条
  • [1] Human factors of transitions in automated driving: A general framework and literature survey
    Lu, Zhenji
    Happee, Riender
    Cabrall, Christopher D. D.
    Kyriakidis, Miltos
    de Winter, Joost C. F.
    TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR, 2016, 43 : 183 - 198
  • [2] A review and framework of control authority transitions in automated driving
    Lu, Zhenji
    de Winter, Joost C. F.
    6TH INTERNATIONAL CONFERENCE ON APPLIED HUMAN FACTORS AND ERGONOMICS (AHFE 2015) AND THE AFFILIATED CONFERENCES, AHFE 2015, 2015, 3 : 2510 - 2517
  • [3] Safety assessment of highly automated driving systems in test tracks: A new framework
    Feng, Shuo
    Feng, Yiheng
    Yan, Xintao
    Shen, Shengyin
    Xu, Shaobing
    Liu, Henry X.
    ACCIDENT ANALYSIS AND PREVENTION, 2020, 144
  • [4] Safety Verification of Automated Driving Systems
    Kianfar, Roozbeh
    Falcone, Paolo
    Fredriksson, Jonas
    IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2013, 5 (04) : 73 - 86
  • [5] Automated Functional Safety Analysis of Automated Driving Systems
    Koelbl, Martin
    Leue, Stefan
    FORMAL METHODS FOR INDUSTRIAL CRITICAL SYSTEMS, FMICS 2018, 2018, 11119 : 35 - 51
  • [6] Taming Functional Deficiencies of Automated Driving Systems: a Methodology Framework toward Safety Validation
    Chen, Meng
    Knapp, Andreas
    Pohl, Martin
    Dietmayer, Klaus
    2018 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2018, : 1918 - 1924
  • [7] AUTOMATED DRIVING SYSTEMS: Collaborative Research Framework
    Harding, John
    Public Roads, 2024, 88 (02) : 30 - 33
  • [8] Safety Assurance Concepts for Automated Driving Systems
    Ballingall, Stuart
    Sarvi, Majid
    Sweatman, Peter
    Ballingall, Stuart (sballingall@student.unimelb.edu.au), 1600, SAE International (02): : 1528 - 1537
  • [9] Forecast Horizon for Automated Safety Actions in Automated Driving Systems
    Mehmed, Ayhan
    Antlanger, Moritz
    Steiner, Wilfried
    Punnekkat, Sasikumar
    COMPUTER SAFETY, RELIABILITY, AND SECURITY, SAFECOMP 2019, 2019, 11698 : 111 - 125
  • [10] Safety in higher level automated vehicles: Investigating edge cases in crashes of vehicles equipped with automated driving systems
    Moradloo, Nastaran
    Mahdinia, Iman
    Khattak, Asad J.
    ACCIDENT ANALYSIS AND PREVENTION, 2024, 203