This video is part of the Machine Intelligence in Autonomous Vehicles Summit, Amsterdam, 2017 Event. If you would like to access all of the videos please click here.

High-capacity Ride-sharing and Planning in Intelligent Autonomous Transportation Systems

Ride-sharing services are transforming urban mobility by providing timely and convenient transportation to anybody, anywhere, and anytime. I will present a general mathematical model for real-time high-capacity ride-sharing and quantify experimentally the tradeoff between different vehicle types and fleet sizes, using more than three million rides extracted from a NYC taxicab public dataset. The algorithm applies to fleets of autonomous vehicles and also incorporates rebalancing of idling vehicles to areas of high demand.

Javier Alonso-Mora, Assistant Professor at Delft University of Technology

Javier Alonso-Mora is an Assistant Professor at the Delft University of Technology. Previously he was a Postdoctoral Associate at the Massachusetts Institute of Technology and received his Ph.D. degree in robotics from ETH Zurich. He was also a member of Disney Research. His main research interest is in autonomous mobile robots, with a special emphasis in multi-robot systems and robots that interact with other robots and humans. We contribute novel methods and solutions in the areas of motion planning and multi-robot control. Towards the smart cities of the future, we apply these techniques to self-driving cars, automated factories, aerial vehicles and intelligent transportation systems.