Translation of Driver-Pedestrian Behavioral Models at Semi-Controlled Crosswalks into a Quantitative Framework for Practical Self-Driving Vehicle Applications

Translation of Driver-Pedestrian Behavioral Models at Semi-Controlled Crosswalks into a Quantitative Framework for Practical Self-Driving Vehicle Applications

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Jon D. Fricker
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Principal Investigator(s):

Jon D. Fricker, Professor of Civil Engineering – Purdue University

Project Abstract:
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.

Research Thrust(s): Human FactorsPolicy & Planning

Project Form(s):
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