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Translation of driver-pedestrian behavioral models at semi-controlled crosswalks into a quantitative framework for practical self-driving vehicle applications

项目名称：	Translation of driver-pedestrian behavioral models at semi-controlled crosswalks into a quantitative framework for practical self-driving vehicle applications
摘要：	A large number of crosswalks are indicated by pavement markings and signs but are not signal-controlled. Such a location is called “semi-controlled”. However, there is a sufficient amount of interaction between pedestrians and vehicles at “semi-controlled” crosswalks to be concerned about the time when “negotiations” between pedestrians and human drivers are replaced by interactions between pedestrians and self-driving vehicles. Although the behavior between pedestrians and drivers at a semi-controlled crosswalk is becoming better understood, but much efforts are still needed to translate behavioral models into a quantitative framework for practical self-driving vehicles applications. Moreover, if the appropriate sensor and control technology can lead to an optimal traffic control strategy from the perspectives of safety and efficiency, we will have achieved a form of “smart interaction” at crosswalks, which can be a useful element of smart mobility.
状态：	Active
资金：	150,000 ($75,000 CCAT, $75,000 InDOT)
资助组织：	Office of the Assistant Secretary for Research and Technology<==>Center for Connected and Automated Transportation
项目负责人：	Tucker-Thomas, Dawn；Bezzina, Debra
执行机构：	Purdue University, Lyles School of Civil Engineering
开始时间：	20210101
预计完成日期：	20211221
主题领域：	Pedestrians and Bicyclists；Policy；Safety and Human Factors；Transportation (General)；Vehicles and Equipment