Developing and testing machine learning technology to make getting around L.A. safer.
Building on the use of smart systems by the Los Angeles Department of Transportation (LADOT) to monitor vehicular traffic, this project developed machine learning technologies to monitor the movement of pedestrians and bicycles through critical intersections.
MFLA partnered with the City’s Data Science Federation and the California State University Los Angeles Data Science Research Group on this effort, with key support from the Toyota Mobility Foundation.
The goal was to develop a mature algorithm to increase safety and traffic flow through better traffic management and planning, incorporating key data on pedestrian and bicycle movement. After undergoing tests in the Arts District, the technology can be further developed to serve as a model for other cities and municipalities.