Mobility

UCLA uses AI to improve curb safety

Posted on November 16, 2017

UCLA's campus has a daily population of 76,000 people and experiences 68,000 ride-hailing stops per week. Photo: UCLA
UCLA's campus has a daily population of 76,000 people and experiences 68,000 ride-hailing stops per week. Photo: UCLA

Correction: The original story incorrectly stated that the artificial intelligence system was installed on campus shuttles. It should have said the AI system was implemented at pick-up and ride-sharing drop-off sites.

UCLA has partnered with VIMOC Technologies to implement an artificial intelligence-enabled system at pick-up and ride-sharing drop-off sites that visually detects and classifies various forms of transportation such as buses, cars, bicycles, and pedestrians.

The Smart Multi-modal transportation system will combine public, private, and ride-sharing transportation.

“Working with UCLA has given us the opportunity to demonstrate and validate a new and effective approach for Multi-modal traffic management,” said Tarik Hammadou, CEO of VIMOC.

The system, which utilizes VIMOC's Rosella Platform, allows UCLA's soft enforcement to optimize curb space for safety and efficiency at the campus' Gateway Plaza loop.

“Gateway Plaza is a vital hub for the university’s functional transfer of our students, employees and visitors,” said David Karwaski, senior associate director of UCLA Transportation. “With the addition of over 60,000 weekly ride-hailing drop-offs and pick-ups, ensuring safe and efficient traffic flow has given us the opportunity to pursue traffic and curb space management with an entirely new perspective.”

UCLA's campus has a daily population of 76,000 people and experiences 68,000 ride-hailing stops per week.

VIMOC will continue to work with UCLA by providing AI-based solutions in pursuit of a Smart Campus environment.

“Intelligent Transportation System solutions can be effective when the gathered intelligence is highly accurate and can be presented in real-time,” said Hammadou. “Operators can then act upon this data to make significant improvements to existing structures and guide transportation behavior."

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