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动态多特征融合的道路遗洒物威胁度分析方法 被引量:1

Novel Threat Degree Analysis Method for Scattered ObJects in Road Traffic Based on Dynamic Multi-feature Fusion
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摘要 道路上的遗洒物可能对交通运输构成潜在的安全威胁。在自动驾驶环境感知的行业应用背景下,提出一种基于动态多特征融合的道路遗洒物威胁度分析方法,一方面可以实现对道路多车辆目标的跟踪,另一方面可以实现行驶区域内遗洒物对车辆行驶的威胁度自动分析。为提取道路前景车辆目标的交通特性参数,首先开展多车辆跟踪方法研究,提出一种基于Camshift和身份数据关联的多目标跟踪算法,通过建立跟踪链表,对跟踪车辆身份数据进行记录,实时跟踪道路前景车辆目标,提取并记录感兴趣车辆交通特性参数;然后结合交通特性参数提取道路车辆动态特征,在该类目标跟踪基础上建立道路遗洒物安全分析模型,通过分析被跟踪车辆的特征变化,提出一种多特征融合的道路遗洒物威胁度分析方法,突破单一动态特征分析在自动驾驶环境感知应用中的局限性,利用动态多特征的融合决策方法,准确量化判断道路遗洒物对交通运输造成的威胁程度;最后,为了验证算法的鲁棒性和实用性,设计了仿真视频结合实际传感器获取的道路视频对所提威胁度分析方法进行验证,仿真视频用3dmax仿真得到,实采视频由CCD摄像机拍摄得到。相关算法验证采用VS2008和OpenCV搭建软件平台,仿真图由MATLAB2014得到,视频图像的分辨率为320*240。实验结果表明,该方法能准确、真实地确定遗洒物的威胁程度,利用第三方实验视角拓宽了特定车辆安全威胁区域分析的应用范围,通过对自动驾驶主车体行驶范围内的安全威胁环境建模,为自动驾驶车辆安全行驶决策的车载应用提供理论依据和技术支持。 Scattered obJects in road traffic may cause potential safety threat to transportation.In the context of industry application of auto-driving environment sensing,a novel threat-degree analysis method for abandoned obJect in road traffic based on dynamic multi-feature fusion was proposed in this paper.It realizes multiple vehicles tracking and the automatic analysis of the threat degree of the scattered obJects to vehicles in the driving area.In the proposed method,in order to extract the traffic characteristic parameters of the vehicles in foreground,firstly,the multi-vehicle tracking method was studied,and a novel tracking algorithm based on Camshift and identity data association was proposed.This algorithm records the identity data of the tracked vehicles by establishing the track list,real-time tracking of multi-vehicle targets in foreground can be realized.Then,the dynamic features of the vehicles are extracted based on the traffic characteristic parameters,the scattered obJects safety analysis modeling is established based on target tracking.A threat-degree analysis method of scattered obJects in road traffic was put forward by analyzing the dynamic multi-feature of the tracked vehicles.The proposed method not only overcomes the limitation of the environment sensing using only one dynamic feature,but also can accurately estimate the threat-degree of scattered obJects in road traffic to transportation by the multiple features fusion decision method.Finally,in order to verify the robustness and practicability of the proposed threat-degree analysis method,this paper designed an experiment that using the simulation and the real road video.The simulation video was simulated by 3dmax,and the real video was captured by CCD camera.The proposed algorithm was tes-ted on the software platform constructed by VS2008 and OpenCV,and the simulation figures were obtained by MATLAB2014.The resolution of video image was 320*240.The results show that the proposed method can accurately analyze the threat-degree of scattered obJects in road traffic,and utilizing the third party’s test perspective can broaden the application range of the particular vehicle’s safety area threat-degree analysis.By designing a safety threat-degree analysis model of the auto-vehicle’s surrounding environment,the proposed method can provide theoretical basis and technical support for on-board application of safe driving decision-making of auto-driving vehicles.
作者 吴宏涛 刘力源 孟颖 荣亚鹏 李路凯 WU Hong-tao;LIU Li-yuan;MENG Ying;RONG Ya-peng;LI Lu-kai(Shanxi Traffic Science Research Institute,Taiyuan 030032,China;Taiyuan Normal University,Taiyuan 030619,China)
出处 《计算机科学》 CSCD 北大核心 2020年第S01期196-205,共10页 Computer Science
基金 面向自动驾驶车辆的公路安全要求和现场评价研究(2018-1-21) 自动驾驶汽车-高速公路运行环境融合性技术研究与应用(18-JKKJ-01) 山西省交控集团应用研究项目(19-JKKJ-51,19-JKKJ-30)。
关键词 自动驾驶环境感知 目标威胁度分析 多特征融合 遗洒物 道路安全决策 Auto-driving environment sensing Target threat-degree analysis Multiple features fusion Scattered obJect Road safety decision-making
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