Undergrad Research Project - Safe Cyclist Project

Spring 2016

John Bird
Anthony Rowe
Project description

Last year there were more than 52,000 people seriously injured in the United States due to bicycle accidents. Bicycle transportation represents a healthy and clean mechanism to improve both transportation efficiency and parking in urban areas. Traditional bicycles are now even being augmented with electric drive systems to decrease the barrier of adoption for commuters. Unfortunately, as bicycles become more capable and hybrid and electric vehicle usage increases the ability for cyclists to perceive traffic danger is decreasing. In this project, we explore how DSRC communication, differential positioning technologies and sensor-based trajectory estimation techniques can be used to warn drivers about potential collisions with cyclists. This requires developing rider models that can help anticipate the complex motion patterns of a cyclist or pedestrian as compared to that of a vehicle. For my research, I will be working on data acquisition from vehicle CANbus networks via on-board diagnostic (OBD) ports. Using Ford's OpenXC platform, I will log car steering, braking, and acceleration data for use in collision prediction. Easy access to vehicle data will aid in augmenting future DSRC warning systems that will be deployed in both cars as well as smartphones carried by cyclists.

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