Volume 39 Issue 4
Aug.  2021
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Article Navigation >  Journal of Transport Information and Safety  > 2021  >  39(4): 9-15, 34
WU Zixiang, HUANG Helai, CHEN Jiguang, ZHENG Dehong, ZHA Wuping. A Study on Collision Avoidance Strategy for Vulnerable Road Users Under Visual Obstruction[J]. Journal of Transport Information and Safety, 2021, 39(4): 9-15, 34. doi: 10.3963/j.jssn.1674-4861.2021.04.002
Citation: WU Zixiang, HUANG Helai, CHEN Jiguang, ZHENG Dehong, ZHA Wuping. A Study on Collision Avoidance Strategy for Vulnerable Road Users Under Visual Obstruction[J]. Journal of Transport Information and Safety, 2021, 39(4): 9-15, 34. doi: 10.3963/j.jssn.1674-4861.2021.04.002
shu

A Study on Collision Avoidance Strategy for Vulnerable Road Users Under Visual Obstruction

doi: 10.3963/j.jssn.1674-4861.2021.04.002
  • 1.

    School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China

  • 2.

    Smart Transport Key Laboratory of Hunan Province, Central South University, Changsha 410075, China

  • 3.

    Traffic Police Corps of Public Security Department of Hunan Province, Changsha 410100, China

  • Received Date: 2021-03-04
    Abstract
  • The traffic accident caused by visual obstruction is one of the main types of current urban-road traffic accidents. The work proposes an autonomous emergency-brake avoidance control strategy based on the collision time ratio and the safe braking distance, aiming at the crossroad traffic accident caused by a visual obstruction between vehicle and vulnerable road users(VRU). Firstly, the traffic state model of the vehicle and VRU is established to analyze the critical distance of braking to avoid a collision. Then the collision avoidance scenarios are divided into three types with different braking deceleration speeds adopted. The autonomous emergency collision-avoidance control strategy is proposed based on the critical distance and the collision time ratio between the vehicle and VRU in this scenario. Finally, the strategy and the traditional TTC braking algorithm are analyzed by the Euro NCAP test scenario. The results show that the vehicle can avoid collisions at a higher speed under ideal circumstances using this strategy in the Euro NCAP CPNC test scenario. Compared with the traditional TTC algorithm, it can reduce the collision speed more effectively in the high-speed driving condition where collisions cannot be avoided and reduce the risk of serious injury and death to improve the safety of vehicles.

     

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    • References(23)
  • [1]
    WHO. Global status report on road safety: Time for action[R]. Geneva: World Health Organization, 2015.
    [2]
    CHEN Q, CHEN Y, BOSTROM O, et al. A comparison study of car-to-pedestrian and car-to-E-bike accidents: Data source: the China in-depth accident study(CIDAS)[C]. SAE 2014World Congress & amp; Exhibition, Detroit, Michigan, USA: SAE, 2014.
    [3]
    TREAT J R, TUMBAS N S, MCDONALD S T, et al. Tri-level study of the causes of traffic accidents: Final report. Executive summary[R]. Bloomington: Indiana University, Institute for Research in Public Safety, 1979.
    [4]
    EURO NCAP. Test protocol-AEB systems Version 1.1[EB/OL]. (2015-7-6)[2021-03-04]. https://www.euroncap.com/en/forengineers/protocols/safety-assist/.
    [5]
    何仁, 冯海鹏. 自动紧急制动(AEB)技术的研究与进展[J]. 汽车安全与节能学报, 2019, 10(1): 1-15. doi: 10.3969/j.issn.1674-8484.2019.01.001

    HE Ren, FENG Haipeng. Research and development of autonomous emergency brake(AEB)technology[J]. Journal of Automotive Safety and Energy, 2019, 10(1): 1-15. (in Chinese). doi: 10.3969/j.issn.1674-8484.2019.01.001
    [6]
    LEE K, PENG H. Evaluation of automotive forward collision warning and collision avoidance algorithms[J]. Vehicle System Dynamics, 2005, 43(10): 735-751. doi: 10.1080/00423110412331282850
    [7]
    FANCHER P S, BAREKET Z, ERVIN R D, et al. Human-centered design of an Acc-with-braking and forward-crash-warning system[J]. Vehicle System Dynamics, 2001, 36(2/3): 203-223. http://www.onacademic.com/detail/journal_1000037062648010_f234.html
    [8]
    李霖, 贺锦鹏, 刘卫国, 等. 基于驾驶员紧急制动行为特征的危险估计算法[J]. 同济大学学报(自然科学版), 2014, 42(1): 109-114. https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ201401019.htm

    LI Lin, HE Jinpeng, LIU Weiguo, et al. Threat assessment algorithm based on characteristic of driver emergency braking behavior[J]. Journal of Tongji University(Natural Science), 2014, 42(1): 109-114. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-TJDZ201401019.htm
    [9]
    SAVINO G, BROWN J, RIZZI M, et al. Triggering algorithm based on inevitable collision states for autonomous emergency braking(AEB)in motorcycle-to-car crashes[C]. 26thIEEE Intelligent Vehicles Symposium(Ⅳ), Seoul, South Korea: IEEE, 2015.
    [10]
    张立存, 苗强, 耿冬冬. 乘用车与两轮车事故特征分析和目标识别因素研究[J]. 汽车技术, 2020(3): 41-44. https://www.cnki.com.cn/Article/CJFDTOTAL-QCJS202003011.htm

    ZHANG Licun, MIAO Qiang, GENG Dongdong. Research on car and two-wheeler accident characteristic analysis and object detection factor[J]. Automobile Technology, 2020(3): 41-44. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-QCJS202003011.htm
    [11]
    SUI B, ZHOU S, ZHAO X, et al. An overview of car-to-twowheeler accidents in China: Guidance for AEB assessment[C]. 25thInternational Technical Conference on the Enhanced Safety of Vehicles(ESV), Eindhoven, Netherlands: NHTSA, 2017.
    [12]
    CAO Y, XIAO L, DONG H, et al. Typical pre-crash scenarios reconstruction for two-wheelers and passenger vehicles and its application in parameter optimization of aeb system based on nais database[C]. 26thInternational Technical Conference on the Enhanced Safety of Vehicles(ESV), Detroit, Michigan USA: NHTSA, 2019.
    [13]
    刘颖, 贺锦鹏, 刘卫国, 等. 自动紧急制动系统行人测试场景的研究[J]. 汽车技术, 2014(3): 35-39. doi: 10.3969/j.issn.1000-3703.2014.03.009

    LIU Ying, HE Jinpeng, LIU Weiguo, et al. Research on test scenarios for AEB pedestrian system[J]. Automobile Technology, 2014(3): 35-39. (in Chinese). doi: 10.3969/j.issn.1000-3703.2014.03.009
    [14]
    SUI B, LUBBE N, BÄRGMAN J. A clustering approach to developing car-to-two-wheeler test scenarios for the assessment of automated emergency braking in China using in-depth Chinese crash data[J]. Accident Analysis & amp; Prevention, 2019(132): 105242. http://www.sciencedirect.com/science/article/pii/S0001457519303264
    [15]
    EURO NCAP. Test Protocol-AEB VRU systems Version 3.0. 3[EB/OL]. (2020-06)[2021-03-04]. https://cdn.euroncap.com/media/58226/euro-ncap-aeb-vru-test-protocol-v303.pdf.
    [16]
    SUN Ling, LI Yameng, GAO Jian. Architecture and application research of cooperative intelligent transport systems[J]. Procedia Engineering, 2016(137): 747-753. http://www.sciencedirect.com/science/article/pii/S1877705816003398/pdf?md5=3e174bd7813037962a9b293b6c7004b5&pid=1-s2.0-S1877705816003398-main.pdf
    [17]
    SERGEI KORJAGIN, PAVEL KLACHEK. Innovative development of intelligent transport systems based on biocybernetical vehicle control systems[J]. Transportation Research Procedia, 2017(20): 326-333. http://www.onacademic.com/detail/journal_1000039829808410_ee06.html
    [18]
    YAN Gongjun, DANDA B R. Vehicle-to-vehicle connectivity analysis for vehicular ad-hoc networks[J]. Ad Hoc Networks, 2017(58): 25-35. http://www.sciencedirect.com/science?_ob=ShoppingCartURL&_method=add&_eid=1-s2.0-S1570870516303274&originContentFamily=serial&_origin=article&_ts=1482496148&md5=6a81ac0854da3cd4e551a9e52581ec21
    [19]
    SHANE T, MARTIN G, EDWARD J, et al. Hybrid testbed for simulating in-vehicle automotive networks[J]. Simulation Modelling Practice and Theory, 2016(66): 193-211. http://www.onacademic.com/detail/journal_1000038935847810_86c3.html
    [20]
    李霖, 朱西产, 陈海林. 驾驶员制动和转向避撞极限[J]. 同济大学学报(自然科学版), 2016, 44(11): 1743-1748. doi: 10.11908/j.issn.0253-374x.2016.11.015

    LI Lin, ZHU Xichan, CHEN Hailin. Drivers'collision avoidance limit by braking and steering[J]. Journal of Tongji University(Natural Science), 2016, 44(11): 1743-1748. (in Chinese). doi: 10.11908/j.issn.0253-374x.2016.11.015
    [21]
    MCLAUGHLIN SB. Analytic assessment of collision avoidance systems and driver dynamic performance in rear-end crashes and near-crashes[D]. Virginia: Virginia Polytechnic Institute and State University, 2008.
    [22]
    李霖, 朱西产, 董小飞, 等. 自主紧急制动系统避撞策略的研究[J]. 汽车工程, 2015, 37(2): 168-174. https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC201502008.htm

    LI Lin, ZHU Xichan, DONG Xiaofei, et al. A research on the collision avoidance strategy for autonomous emergency braking system[J]. Automotive Engineering, 2015, 37(2): 168-174. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-QCGC201502008.htm
    [23]
    ROSÉN E, KAÄLLHAMMER J E, ERIKSSON D, et al. Pedestrian injury mitigation by autonomous braking[J]. Accident Analysis & amp; Prevention, 2010, 42(6): 1949-1957. http://www.sciencedirect.com/science?_ob=ShoppingCartURL&_method=add&_eid=1-s2.0-S0001457510001636&originContentFamily=serial&_origin=article&_ts=1477547159&md5=bf83c0465122e4d3a822857914b93ad9
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