详情

Evaluate Alternative Methods to Examine Visibility of Pavement Markings

项目名称：	Evaluate Alternative Methods to Examine Visibility of Pavement Markings
摘要：	Pavement markings are the primary means for an agency to provide longitudinal guidance to drivers. Effective pavement markings can improve safety, improve driver comfort, and increase functionality/reliability of automated driving systems and Advanced Driver Assistance Systems (ADAS). To be effective, markings must be visible during all driving conditions, day and night. Markings are typically characterized by their retroreflectivity which is a surrogate measure for how visible the marking is at night. Retroreflectivity does not consider other factors that will impact the actual visibility of the marking such as the color or retroreflectivity of the pavement that the marking is applied to, the color or width of the marking, or the viewing conditions (i.e., observation vehicle, observer characteristics, weather conditions). Retroreflectivity is also a metric for nighttime visibility that may not relate to the marking visibility during the day. This project aims to improve current pavement marking installation and maintenance practices such that effective markings are continuously maintained. The project also aims to develop a tool to effectively assess the visibility of pavement markings and to make suggestions for marking maintenance. The Performing Agency shall evaluate marking visibility for both human and automated drivers across a range of conditions. These evaluations shall be used to make recommendations to improve new marking installation specifications and techniques, improve marking maintenance practices, and evaluate other technologies that should be considered to improve pavement marking delineation.
状态：	Active
资金：	467,604
资助组织：	Texas Department of Transportation
项目负责人：	Adediwura, Jade
执行机构：	Texas A&M Transportation Institute<==>The University of Texas at San Antonio
开始时间：	20210901
预计完成日期：	20240831
主题领域：	Operations and Traffic Management；Safety and Human Factors