Voyage Develops A Supercharged AEB System

The following is excerpted from a post written by Oliver Cameron, co-founder and CEO of Voyage which has developed SafeStop braking system for autonomous vehicles. The entire piece can be read by clicking on this sentence.

PALO ALTO, Calif. – Voyage SafeStop is a supercharged automatic emergency braking (AEB) system, designed from the ground up for driverless cars. SafeStop utilizes high-resolution depth sensors, state-of-the-art algorithms, and automotive-grade compute to make intelligent decisions about emergency braking events. We are excited to begin sharing more information about this safety-critical system.

Why did we build SafeStop? While engineering any safety-critical system, whether hardware or software, it is vital you construct it with multiple layers of redundancy to avoid any single point of failure. A correctly composed safety-critical system assumes any layer can fail at any time, and ensures that each failure mode is handled (i.e. no silent failures). SafeStop is one of those mission-critical layers within our self-driving technology, and ensures our vehicle comes to a stop for critical objects (e.g. pedestrians, bicyclists, vehicles) in the path of our self-driving car.

You may be asking “Isn’t the whole purpose of a self-driving car to stop for critical objects?” You’d be correct, but delivering on this promise is a complex undertaking. If you inspect the results of many of the Automatic Emergency Braking (AEB) systems installed on consumer vehicles today, you’ll note that although some systems do prevent collisions proactively, many systems instead optimize for reducing the impact of collisions (i.e. hitting the brakes when a collision is unavoidable). This design decision is due in large part to the complexity of reliably detecting objects with low-resolution sensors, and the safety issues involved with high-speed braking events caused by false positives. An AEB system designed from the ground up for self-driving cars, complete with advanced sensors, algorithms, and compute, can and should do better.

While a Voyage car drives itself, it processes information from its many vision sensors 10 times per second. This information is processed on its primary compute cluster powered by its primary power source. Within those 100 milliseconds, our self-driving technology executes its primary set of vision algorithms on the sensor data, outputting rich information about objects around us. We engineer each primary vision algorithm to be unique in their approach, to minimize common failures.

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