Advised by Mar Hershenson of Pear. Pear.vc is a leading early stage venture capital firm.
Imagine an intersection that warns you if you’re on a collision path just seconds before you can see the other vehicle.
Whether a car is human operated or autonomous, sensing the environment from a car’s vantage point faces limitations because of occlusion by structures and other vehicles. With self-driving cars looming on the horizon, is it possible to use a network of sensors and cameras to augment the navigation of cars? Could we expedite the adoption of autonomous vehicles?
Cities have the opportunity to include sensors and cameras in areas with limited visibility to provide additional information to the vehicles in the vicinity and reduce the chances of a collision. This network can help current human drivers, and possibly solve an important barrier for commercial application of self-driving cars: reliable sensing of the environment.
The goal of this Collider Project is to develop a proof-of-concept prototype and a business model, in order to explore the viability of a network of city cameras/sensors. Such a network would augment autonomous car navigation from reducing accidents in blind intersections to optimizing traffic flow and parking. An important innovation in this project is the creation a self-sustaining business model that could monetize the sensors early on and not rely on massive initial capital or city budgets to deploy. This could also help speed up the adoption of autonomous vehicles in cities.
This project is a great opportunity to learn about autonomous vehicles and the latest innovations in transportation. This will position you to get involved in a rapidly growing industry, or create your own startup.
Action:
If you would like to take an active leadership role in this project (student CTO, business lead) now it’s time to send a resume/cv with an statement of interest to scet.collider@berkeley.edu. Write – Designing Cities for Autonomous Cars – in the Subject line. We will follow up with more information.