The verbiage in variable message signs and traffic diversion during crash incidents

Sailesh Acharya;Michelle Mekker
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Abstract

Purpose - WIth limited research on the effects of variable message sign (VMS) message content and verbiage on revealed driver behavior, this study aims to investigate how different verbiage of crash-related messages are related to the diversion rate. Design/methodology/approach - Using ordered logit models, the associations of message verbiage with diversion rates during crash incidents were assessed using five years of VMS message history within a section of I-15 in the state of Utah. Findings - A significant impact of message verbiage on the diversion rate was observed. Based on the analysis results, the crash message verbiage with the highest diversion was found to be miles to crash 1 "prepare to stop," followed by crash location 1 delay information, miles to crash 1 "use caution" 1 lane of the crash, etc. In addition, the diversion rate was found to be correlated to some roadway characteristics (e.g. occupancy in mainline, weather condition and light condition) along with the temporal variations. Research limitations/implications - These findings could be used by transportation agencies (e.g. state department of transportation [DOTs]) to make informed decisions about choosing the message verbiage during future crash incidents. This study also revealed that higher diversion rates are associated with a shorter distance between the crash location and VMS device location, recommending increasing the number of VMS devices, particularly in crash-prone areas.
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车祸期间可变信息标志和交通改道中的措辞
目的-通过对可变信息标志(VMS)信息内容和措辞对驾驶员行为的影响进行有限的研究,本研究旨在调查碰撞相关信息的不同措辞与分流率之间的关系。设计/方法/方法-使用有序logit模型,使用犹他州I-15路段内五年的VMS信息历史,评估了碰撞事件期间信息措辞与分流率的关联。调查结果-观察到信息措辞对转移率的显著影响。根据分析结果,转向最高的碰撞信息措辞是距离碰撞1英里“准备停车”,其次是碰撞位置1延迟信息,距离碰撞1公里“小心使用”1车道,等等。此外,研究发现,改道率与一些道路特征(如主线占用率、天气条件和光照条件)以及时间变化有关。研究局限性/影响-交通机构(如州交通部[DOTs])可以利用这些发现,在未来的撞车事故中就选择信息措辞做出明智的决定。这项研究还表明,较高的分流率与坠机地点和VMS设备位置之间的距离较短有关,建议增加VMS设备的数量,特别是在坠机易发地区。
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Front Cover Contents Advancements and Prospects in Multisensor Fusion for Autonomous Driving Extracting Networkwide Road Segment Location, Direction, and Turning Movement Rules From Global Positioning System Vehicle Trajectory Data for Macrosimulation Decision Making and Control of Autonomous Vehicles Under the Condition of Front Vehicle Sideslip
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