考虑过街行人运动不确定性的人-车碰撞伤害评估
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摘要
过街行人运动不确定性是影响人-车碰撞和行人伤害预测准确性与可靠性的重要因素。本文中采用1阶马尔科夫模型描述行人过街运动,利用无味变换,高效地估计人-车碰撞概率和碰撞时间与速度的概率密度,从而预测人-车冲突中行人的伤害概率。在运动仿真的基础上,构建了无味变换点集。以蒙特卡罗模拟为参考,验证所提出方法预测行人伤害概率的准确性。采用仿真,预测在人-车冲突场景下,采取不同避撞操作的行人伤害概率。结果表明,相比于确定性方法,本文中所提出的方法能更加真实地反映在不同避撞操作下对行人的伤害,为避撞决策与控制提供有效的目标量化手段。
The uncertainty of pedestrian movement during road crossing is an important factor affecting the correctness and robustness of the prediction of vehicle-pedestrian collision and pedestrian injuries. In this paper,the first order Markov model is employed to describe the road crossing movement of pedestrian and unscented transformation( UT) is used to efficiently estimate the probability of vehicle-pedestrian collision and the probability density of collision time and speed,and hence to predict the injury probability of pedestrian in collision. Based on kinematical simulation,the-set of UT is constructed. With Monte Carlo simulation as reference,the correctness of pedestrian injury probability predicted by the method proposed is verified. The pedestrian injury probability in vehicle-pedestrian collision with different vehicle maneuvers adopted to avoid collision is predicted buy simulation. The results show that compared with the determinate method,the method proposed in this paper can more truly reflect the pedestrian injury with different vehicle maneuvers,providing an effective objective quantization means for the decision making and control of collision avoidance.
The uncertainty of pedestrian movement during road crossing is an important factor affecting the correctness and robustness of the prediction of vehicle-pedestrian collision and pedestrian injuries. In this paper,the first order Markov model is employed to describe the road crossing movement of pedestrian and unscented transformation( UT) is used to efficiently estimate the probability of vehicle-pedestrian collision and the probability density of collision time and speed,and hence to predict the injury probability of pedestrian in collision. Based on kinematical simulation,the-set of UT is constructed. With Monte Carlo simulation as reference,the correctness of pedestrian injury probability predicted by the method proposed is verified. The pedestrian injury probability in vehicle-pedestrian collision with different vehicle maneuvers adopted to avoid collision is predicted buy simulation. The results show that compared with the determinate method,the method proposed in this paper can more truly reflect the pedestrian injury with different vehicle maneuvers,providing an effective objective quantization means for the decision making and control of collision avoidance.
引文
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[2]GANDHI T,TRIVEDI M M.Pedestrian protection systems:Issues,survey,and challenges[J].IEEE Transactions on Intelligent Transportation Systems,2007,8(3):413-430.
[3]COELINGH E,EIDEHALL A,BENGTSSON M.Collision warning with full auto brake and pedestrian detection-a practical example of automatic emergency braking[C].Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems,Sept 19-22,2010,Madeira Island,Portugal.2010:155-160.
[4]朱西产,刘智超,李霖.基于车辆与行人危险工况的转向避撞控制策略[J].汽车安全与节能学报,2015,6(3):217-223.
[5]KELLER C G,DANG T,FRITZ H,et al.Active pedestrian safety by automatic braking and evasive steering[J].IEEE Transactions on Intelligent Transportation Systems,2011,12(4):1292-1304.
[6]景超.行人过街交通特性研究[D].长春:吉林大学,2007.
[7]冯树民,吴阅辛.信号交叉口行人过街速度分析[J].哈尔滨工业大学学报,2004,36(1):76-78.
[8]BRAEUCHLE C,FLEHMIG F,ROSENSTIEL W,et al.Maneuver decision for active pedestrian protection under uncertainty[C].Proceedings of the 16th International IEEE Conference on Intelligent Transportation Systems,Oct 6-9,2013,Netherlands,2013:646-651.
[9]MAKRIS D,ELLIS T.Spatial and probabilistic modelling of pedestrian behaviour[C].Proceedings of the BMVC,Sept 2-5,Cardiff,UK,2002:557-566.
[10]KHLER S,GOLDHAMMER M,BAUER S,et al.Early detection of the pedestrian's intention to cross the street[C].Proceedings of the 2012 15th International IEEE Conference on Intelligent Transportation Systems,Sept16-19,IEEE Intelligent Vehicles Symposium,2012:1759-1764.
[11]GOLDHAMMER M,GERHARD M,ZERNETSCH S,et al.Early prediction of a pedestrian's trajectory at intersections[C].Proceedings of the 16th International IEEE Conference on Intelligent Transportation Systems,Oct 6-9,Netherlands,2013:237-242.
[12]KELLER C G,HERMES C,GAVRILA D M.Will the pedestrian cross?probabilistic path prediction based on learned motion features[M].MESTER R,FELSBERG M.Pattern Recognition:33rd DAGM Symposium,Frankfurt/Main,Germany,August 31-September 2,2011 Proceedings.Berlin,Heidelberg;Springer Berlin Heidelberg,2011:386-395.
[13]NICOLAO G D,FERRARA A,GIACOMINI L.Onboard sensorbased collision risk assessment to improve pedestrians'safety[J].IEEE Transactions on Vehicular Technology,2007,56(5):2405-2413.
[14]SCHUBERT R,RICHTER E,WANIELIK G.Comparison and evaluation of advanced motion models for vehicle tracking[C].Proceedings of the 11th International Conference on Information Fusion,June 30-July 3,2008,IEEE Intelligent Vehicles Symposium,2008:1-6.
[15]JAYANT N.A first-order markov model for understanding delta modulation noise spectra[J].IEEE Transactions on Communications,1978,26(8):1316-1318.
[16]HILLENBRAND J,SPIEKER A,KROSCHEL K.Efficient decision making for a multi-level collision mitigation system[C].Proceedings of the 2006 IEEE Intelligent Vehicles Symposium,June13-15,Tokyo,Japan,2006:460-465.
[17]TAMKE A,DANG T,BREUEL G.A flexible method for criticality assessment in driver assistance systems[C].Proceedings of the Intelligent Vehicles Symposium(IV),June5-9,Baden-Baden,Germany,2011:697-702.
[18]BERTHELOT A,TAMKE A,DANG T,et al.A novel approach for the probabilistic computation of Time-To-Collision[C].Proceedings of the Intelligent Vehicles Symposium(IV),June3-7,IEEE Intelligent Vehicles Symposium,2012:1173-1178.
[19]BERTHELOT A,TAMKE A,DANG T,et al.Handling uncertainties in criticality assessment[C].Proceedings of the Intelligent Vehicles Symposium(IV),June5-9,Baden-Baden,Germany,2011:571-576.
[20]JULIER S J,UHLMANN J K.A general method for approximating nonlinear transformations of probability distributions[R].Technical Report,Robotics Research Group,Department of Engineering Science,University of Oxford,1996.
[21]HANNAWALD L,KAUER F.Equal effectiveness study on pedestrian protection[M].Isaacson:Dresden University of Technology,2004.
[22]KONG C,YANG J.Logistic regression analysis of pedestrian casualty risk in passenger vehicle collisions in China[J].Accident Analysis&Prevention,2010,42(4):987-993.
[23]黄智,吴乙万,刘剑,等.高速车辆车道偏离辅助控制研究[J].机械工程学报,2013,49(22):157-163.