Accuracy is Key to the Multi-Modal Future

Every day brings a new advancement in the Intelligent Transportation industry, and with the growing use of shared mobility and an increase in different modes of transportation, consumers are beginning to take full advantage of their options.

Tarik Hammadou, CEO of VIMOC Technologies, says that there is a paradigm shift quickly coming to transportation that will move us from an auto-driven world to a multi-modal focused structure which will put a great deal of stress on the existing system. Because of this, we will need to be thinking ahead and begin moving away from one-dimensional data that is imprecise to multiple streams of highly accurate data that will need to be calculated in real-time at the edge of the cloud. Hammadou said that as we move toward autonomous vehicles, this accuracy will be key to getting to the next step.

VIMOC Technologies is a leader in creating Artificial Intelligence (AI) solutions at the edge of the network. In partnership with UCLA, they recently deployed their AI-enabled deep learning Rosella™ Platform that is providing real-time, accurate information on the university’s heavily trafficked Gateway Plaza loop.

UCLA is currently in the full-throws of experiencing this multi-modal revolution and sees 68,000 ride-hailing stops a week, creating massive traffic-flow challenges on campus. Embracing this reality, the new system visually detects and classifies different transportation modes including cars, buses, bicycles and pedestrians allowing them to quickly identify problems that can quickly be resolved with soft enforcement. It’s an innovative approach that makes sure the curb space in the loop area will be managed effectively and improves the overall user experience.

This exciting partnership has allowed VIMOC to validate it’s new and effective approach to managing multi-modal traffic on arguably one of the busiest college campuses in California. Hammadou says that giving these operators real-time and highly accurate information allows them to make improvements to existing structures and also change transportation behavior.