Purpose–To support the standardized evaluation of bicyclist automatic emergency braking(AEB)systems,test scenarios,test procedures and test system hardware and software tools have been investigated and developed by t...Purpose–To support the standardized evaluation of bicyclist automatic emergency braking(AEB)systems,test scenarios,test procedures and test system hardware and software tools have been investigated and developed by the Transportation Active Safety Institute(TASI)at Indiana University-Purdue University Indianapolis.This paper aims to focus on the development of test scenarios and bicyclist surrogate for evaluating vehicle–bicyclist AEB systems.Design/methodology/approach–The harmonized general estimates system(GES)/FARS 2010-2011 crash data and TASI 110-car naturalistic driving data(NDD)are used to determine the crash geometries and environmental factors of crash scenarios including lighting conditions,vehicle speeds,bicyclist speeds,etc.A surrogate bicyclist including a bicycle rider and a bicycle surrogate is designed to match the visual and radar characteristics of bicyclists in the USA.A bicycle target is designed with both leg pedaling and wheel rotation to produce proper micro-Doppler features and generate realistic motion for camera-based AEB systems.Findings–Based on the analysis of the harmonized GES/FARS crash data,five crash scenarios are recommended for performance testing of bicyclist AEB systems.Combined with TASI 110-car naturalistic driving data,the crash environmental factors including lighting conditions,obscuring objects,vehicle speed and bicyclist speed are determined.The surrogate bicyclist was designed to represent the visual and radar characteristics of the real bicyclists in the USA.The height of the bicycle rider mannequin is 173 cm,representing the weighted height of 50th percentile US male and female adults.The size and shape of the surrogate bicycle were determined as 26-inch wheel and mountain/road bicycle frame,respectively.Both leg pedaling motion and wheel rotation are suggested to produce proper micro-Doppler features and support the camera-based AEB systems.Originality/value–The results have demonstrated that the developed scenarios,test procedures and bicyclist surrogate will provide effective objective methods and necessary hardware and software tools for the evaluation and validation of bicyclist AEB systems.This is crucial for the development of advanced driver assistance systems.展开更多
文摘针对现有的自动紧急制动(autonomous emergency braking,AEB)系统在弯道工况下存在误识别的情况,提出一种基于曲线坐标转换法的目标识别方法。通过传感器反映道路模型几何信息,利用曲线坐标转换法定位主车与目标车辆的位置,计算车辆之间的相对距离,采用逻辑门限制法确定危险目标车辆。针对基于安全距离模型或者碰撞时间(time to collision,TTC)算法的传统避撞算法无法兼顾制动过程中的安全性和舒适性问题,提出一种融合优化的Honda算法和TTC算法的纵向避撞控制策略。利用TTC算法作为前向碰撞预警策略,根据优化的Honda算法设计自动紧急制动策略。仿真结果表明,基于曲线坐标变换的方法能够精确计算主车与目标车辆之间的距离,准确且高效地识别危险目标车辆,基于安全距离算法和TTC算法协同控制的融合算法有效避免车辆纵向跟驰碰撞,兼顾了紧急制动过程的安全性和舒适性。
文摘Purpose–To support the standardized evaluation of bicyclist automatic emergency braking(AEB)systems,test scenarios,test procedures and test system hardware and software tools have been investigated and developed by the Transportation Active Safety Institute(TASI)at Indiana University-Purdue University Indianapolis.This paper aims to focus on the development of test scenarios and bicyclist surrogate for evaluating vehicle–bicyclist AEB systems.Design/methodology/approach–The harmonized general estimates system(GES)/FARS 2010-2011 crash data and TASI 110-car naturalistic driving data(NDD)are used to determine the crash geometries and environmental factors of crash scenarios including lighting conditions,vehicle speeds,bicyclist speeds,etc.A surrogate bicyclist including a bicycle rider and a bicycle surrogate is designed to match the visual and radar characteristics of bicyclists in the USA.A bicycle target is designed with both leg pedaling and wheel rotation to produce proper micro-Doppler features and generate realistic motion for camera-based AEB systems.Findings–Based on the analysis of the harmonized GES/FARS crash data,five crash scenarios are recommended for performance testing of bicyclist AEB systems.Combined with TASI 110-car naturalistic driving data,the crash environmental factors including lighting conditions,obscuring objects,vehicle speed and bicyclist speed are determined.The surrogate bicyclist was designed to represent the visual and radar characteristics of the real bicyclists in the USA.The height of the bicycle rider mannequin is 173 cm,representing the weighted height of 50th percentile US male and female adults.The size and shape of the surrogate bicycle were determined as 26-inch wheel and mountain/road bicycle frame,respectively.Both leg pedaling motion and wheel rotation are suggested to produce proper micro-Doppler features and support the camera-based AEB systems.Originality/value–The results have demonstrated that the developed scenarios,test procedures and bicyclist surrogate will provide effective objective methods and necessary hardware and software tools for the evaluation and validation of bicyclist AEB systems.This is crucial for the development of advanced driver assistance systems.
