Analysis of lane-changing conflict between cars and trucks at freeway merging sections using UAV video data

IF 2.4 3区 工程技术 Q3 TRANSPORTATION
yicheng Lu, Kai Cheng, Yue Zhang, Xinqiang Chen, Y. Zou
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引用次数: 2

Abstract

Abstract The freeway on-ramp merging section is often identified as a crash-prone spot due to the high frequency of traffic conflicts. Cars and trucks have different sizes and operation characteristics, but very few traffic conflict analysis studies considered different vehicle types at freeway merging sections. Thus, the main objective of this study is to analyze lane-changing conflicts between different vehicle types at freeway merging sections. Vehicle trajectories are extracted from the Unmanned Aerial Vehicle (UAV) video data which are collected in Shanghai, China. Time-to-collision (TTC) is utilized as the surrogate safety measure (SSM) to analyze lane-changing conflicts. Results show that TTC values of car-car conflicts are the smallest, while truck-truck conflicts have the largest TTC values. Although traffic conflicts frequently occur at the on-ramp and additional rightmost lane, the spatial distribution of lane-changing conflicts is significantly different between different vehicle types. The findings of this study are useful for transportation management agencies to design proper strategies to improve traffic safety at freeway merging sections.
基于无人机视频数据的高速公路合流路段车卡变道冲突分析
高速公路入口匝道合流路段由于交通冲突频发,常被认定为交通事故多发路段。轿车和货车具有不同的尺寸和运行特性,但考虑高速公路合流路段不同车辆类型的交通冲突分析研究很少。因此,本研究的主要目的是分析高速公路合流路段不同车辆类型之间的变道冲突。从中国上海地区采集的无人机视频数据中提取飞行器轨迹。采用碰撞时间(TTC)作为替代安全措施(SSM)分析变道冲突。结果表明,车-车冲突的TTC值最小,车-车冲突的TTC值最大。虽然在入口匝道和最右侧附加车道上经常发生交通冲突,但不同车辆类型之间变道冲突的空间分布存在显著差异。研究结果可为交通管理部门设计合理的策略以提高高速公路合流路段的交通安全提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.00
自引率
15.40%
发文量
38
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