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An Approach to Evaluation of Potential Danger of Vehicles Using Video Image Data on Traffic Flow

利用交通流视频图像数据评估车辆潜在危险的方法

基本信息

批准号：
16560463
负责人：
UNO Nobuhiro
金额：
$ 2.18万
依托单位：
Kyoto University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2004
资助国家：
日本
起止时间：
2004 至 2005
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-16560463/
关键词：
video image data vehicle trajectory traffic conflict evaluation of traffic flow safety conflict simulation soft computing 走行支援道路システム

项目摘要

Based on an overall review about researches to improve traffic safety, it can be said that our attentions should be paid to the following research topics : 1) understanding the major factors to cause traffic conflicts or accidents based on the analyses of actual traffic phenomena, 2) developing the suitable indices to evaluate the traffic safety, and 3) developing the engineering tools to predict the effect of traffic safety measures. Considering the above, this study develops an approach to evaluate the traffic flow safety using the vehicular trajectory data extracted from the video image including the continuous observation of vehicular movements along a road section. The followings are what we have done in this study.1. This study develops the approaches to quantitatively evaluate the traffic conflicts considering the types of accidents frequently observed on the analyzed road section. In order to confirm the applicability of these approaches for evaluating traffic flow safety, this study analyzes the relation between the frequency of accidents and the severity of conflicts measured by the conflict indices proposed.2. Focusing on the movements of potentially dangerous vehicles extracted from the vehicular trajectory data using the conflict indices, together with the information on vehicle type and size, lane changing behavior and so on, this study investigates the major causes and process of occurrence of dangerous event in the traffic flow.3. This study analyzes the vehicular behavior in a microscopic way and develops car-following, lane-changing and speed adjustment models that are applicable for the dense traffic condition with very short spacing between vehicles. It is expected that these models might be incorporated into the microscopic traffic simulation model to evaluate traffic safety and road design.

总体回顾交通安全研究的进展，可以说我们应该关注以下研究课题：1）基于对实际交通现象的分析，了解导致交通冲突或事故的主要因素；2）开发合适的交通安全评价指标；3）开发预测交通安全措施效果的工程工具。考虑到上述情况，本研究开发了一种使用从视频图像中提取的车辆轨迹数据来评估交通流安全的方法，包括对沿路段的车辆运动的连续观察。以下是我们在本研究中所做的工作： 1．本研究开发了定量评估交通冲突的方法，考虑到分析路段上经常观察到的事故类型。为了证实这些方法在交通流安全评估中的适用性，本研究分析了事故发生频率与所提出的冲突指数衡量的冲突严重程度之间的关系。 2．本研究主要针对利用冲突指数从车辆轨迹数据中提取的潜在危险车辆的运动情况，结合车辆类型、尺寸、换道行为等信息，探讨交通流中危险事件发生的主要原因和过程。 3．本研究从微观角度分析车辆行为，开发适用于车辆间距很短的密集交通状况的跟车、变道和速度调整模型。预计这些模型可能会被纳入微观交通仿真模型中，以评估交通安全和道路设计。