Automotive Engineering ›› 2022, Vol. 44 ›› Issue (11): 1636-1646.doi: 10.19562/j.chinasae.qcgc.2022.11.002
Special Issue: 智能网联汽车技术专题-感知&HMI&测评2022年
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Hao Chen1,2,Hong Wang3,Weihan Li1,2,Xianxu Bai1,2(),Jiong Chen4,Chuzhao Li3,5,Qin Shi1,2,Jun Sun1,2
Received:
2022-05-06
Revised:
2022-06-16
Online:
2022-11-25
Published:
2022-11-19
Contact:
Xianxu Bai
E-mail:bai@hfut.edu.cn
Hao Chen,Hong Wang,Weihan Li,Xianxu Bai,Jiong Chen,Chuzhao Li,Qin Shi,Jun Sun. Risk Assessment of Safety of the Intended Functionality Scenes Based on Driving Safety Field Theory[J].Automotive Engineering, 2022, 44(11): 1636-1646.
1 | Forbes. Tesla in Taiwan crashes directly into overturned truck, ignores pedestrian, with autopilot on [EB/OL]. Forbes, (2020-1-2)[2022-2-18].https://www.forbes.com/sites/bradtempleton/2020/06/02/tesla-in-taiwan-crashes-directly-into-overturned-truck-ignores-pedestrian-with-autopilot-on/. |
2 | MENZEL T, BAGSCHIK G, MAURER M. Scenarios for development, test and validation of automated vehicles[C]. 2018 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2018: 1821-1827. |
3 | WEBER H, BOCK J, KLIMKE J, et al. A framework for definition of logical scenarios for safety assurance of automated driving[J]. Traffic Injury Prevention, 2019, 20: S65-S70. |
4 | ZHAO D, GUO Y, JIA Y J. Trafficnet: an open naturalistic driving scenario library[C]. IEEE 20th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2017: 1-8. |
5 | ZHAO D, LAM H, PENG H, et al. Accelerated evaluation of automated vehicles safety in lane-change scenarios based on importance sampling techniques[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 18(3): 595-607. |
6 | ZHAO D, HUANG X, PENG H, et al. Accelerated evaluation of automated vehicles in car-following maneuvers[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 19(3): 733-744. |
7 | XU Y, ZOU Y, SUN J. Accelerated testing for automated vehicles safety evaluation in cut-in scenarios based on importance sampling, genetic algorithm and simulation applications[J]. Journal of Intelligent and Connected Vehicles, 2018. |
8 | FENG S, FENG Y, YU C, et al. Testing scenario library generation for connected and automated vehicles, part I: methodology[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 22(3): 1573-1582. |
9 | FENG S, FENG Y, YU C, et al. Testing scenario library generation for connected and automated vehicles, part II: case studies[J]. IEEE Transactions on Intelligent Transportation Systems, 2020, 22(9): 5635-5647. |
10 | FENG S, FENG Y, YAN X, et al. Safety assessment of highly automated driving systems in test tracks: a new framework[J]. Accident Analysis & Prevention, 2020, 144: 105664. |
11 | FENG S, FENG Y, SUN H, et al. Testing scenario library generation for connected and automated vehicles: an adaptive framework[J]. IEEE Transactions on Intelligent Transportation Systems, 2020. |
12 | FENG S, YAN X, SUN H, et al. Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment[J]. Nature Communications, 2021, 12(1): 1-14. |
13 | ISO. Road vehicles safety of the intended functionality: ISO/PAS 21448: 2019[S]. Switzerland: ISO, 2018. |
14 | LI Y, LI K Q, ZHENG Y, et al. Threat assessment techniques in intelligent vehicles: a comparative survey[J]. IEEE Intelligent Transportation Systems Magazine, 2020, 13(4): 71-91. |
15 | BOGENRIEDER R, FEHRING M, BACHMANN R. PRE-SAFE in rear-end collision situations[C]. Proceedings 21st International Technical Conferrence on the Enhanced Safety of Vehicles, Stuttgart, 2009. |
16 | LI Y, ZHENG Y, WANG J Q, et al. Crash probability estimation via quantifying driver hazard perception[J]. Accident Analysis & Prevention, 2018, 116: 116-125. |
17 | WINSUM W V, HEINO A. Choice of time-headway in car-following and the role of time-to-collision information in braking[J]. Ergonomics, 1996, 39(4): 579-592. |
18 | WANG J Q, WU J, LI Y. The driving safety field based on driver-vehicle-road interactions[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 16(4): 2203-2214. |
19 | WANG J Q, WU J, ZHENG X, et al. Driving safety field theory modeling and its application in pre-collision warning system [J]. Transportation Research Part C: Emerging Technologies, 2016, 72: 306-324. |
20 | LI Y, WANG J Q, WU J. Model calibration concerning risk coefficients of driving safety field model[J]. Journal of Central South University, 2017, 24(6): 1494-1502. |
21 | LI M J, SONG X L, CAO H T, et al. Shared control with a novel dynamic authority allocation strategy based on game theory and driving safety field[J]. Mechanical Systems and Signal Processing, 2019, 124: 199-216. |
22 | WU R F, ZHENG X J, XU Y N, et al. Modified driving safety field based on trajectory prediction model for pedestrian–vehicle collision[J]. Sustainability, 2019, 11(22): 6254. |
23 | GONZÁLEZ D, PÉREZ J, MILANÉS V, et al. A review of motion planning techniques for automated vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 17(4): 1135-1145. |
24 | RAKSINCHAROENSAK P, HASEGAWA T, NAGAI M. Motion planning and control of autonomous driving intelligence system based on risk potential optimization framework[J]. International Journal of Automotive Engineering, 2016, 7(AVEC14): 53-60. |
25 | RASEKHIPOUR Y, KHAJEPOUR A, CHEN S K, et al. A potential field-based model predictive path-planning controller for autonomous road vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2016, 18(5): 1255-1267. |
26 | BOUNINI F, GINGRAS D, POLLART H, et al. Modified artificial potential field method for online path planning applications[C]. 2017 IEEE Intelligent Vehicles Symposium (IV). IEEE, 2017: 180-185. |
27 | ULBRICH S, MENZEL T, RESCHKA A, et al. Defining and substantiating the terms scene, situation, and scenario for automated driving[C]. IEEE 18th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2015: 982-988. |
28 | WU S Y, WANG H, YU W H, et al. A new SOTIF scenario hierarchy and its critical test case generation based on potential risk assessment[C]. 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI). IEEE, 2021: 399-409. |
29 | 李林恒, 甘婧, 曲栩, 等. 智能网联环境下基于安全势场理论的车辆换道模型[J]. 中国公路学报, 2021, 34(6): 184-195. |
LI L H, GAN J, QU X, et al. Lane-changing model based on safety potential field theory under the connected and automated vehicles environment[J]. China Journal of Highway and Transport, 2021, 34(6): 184-195. | |
30 | 中国公安部交通运输局. 2010-2016年中华人民共和国道路交通事故统计年报[G]. 北京, 2017. |
Transportation Bureau of the Ministry of Public Security of the PRC. 2010-2016 annals of road traffic accidents statistics of the People’s Republic of China[G]. Beijing, 2017. |
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