Derq Teaches Driverless Cars to Safely Navigate Busy Intersections

There are many technical challenges to overcome in the development of self-driving cars, but one of the toughest is predicting and preventing collisions with pedestrians and other objects that end up in the roadway.

As urban cyclists know, there is a fair amount of intense eye contact that goes on between bikers and drivers as bikers seek to ensure drivers are paying attention—especially in the current era of constant smartphone distractions. That biker-driver interaction is something that can’t be easily replicated or taught to machines.

Derq, a Techstars Mobility alum based in Detroit and Dubai, is conducting a yearlong pilot project on Jefferson Avenue and Randolph Street in the Motor City to focus on vehicle- and pedestrian-related risks around intersections.

“We’re concentrating on road safety for regular cars as well as autonomous vehicles,” says Georges Aoude, Derq’s co-founder and CEO. “Our two main applications are intersection safety—predicting red light violations and sending warnings to a vehicle—and pedestrian safety, which involves leveraging cameras from smart cities to predict pedestrian intent.”


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