Self-driving cars typically use radar or LiDAR technology to avoid collisions with other vehicles. Scientists have created a much simpler insect-inspired system that can serve the same purpose more efficiently. That is, at night.
Radar, LiDAR, and computer vision systems are all pretty effective at preventing self-driving cars from colliding with things, but the actual modules themselves can only be small to a point. It also requires significant power and generally only adds complexity to the vehicle.
Professor Assoc. Saptarshi Das of Pennsylvania State University and his colleagues turned to the world of insects. More specifically, I studied the neural circuits that prevent insects such as grasshoppers from colliding with objects or being caught by predators during flight.
The resulting optoelectronic sensor is made from a layer of molybdenum disulfide and incorporates eight photosensitive “memtransistors” arranged in a circuit. Measuring just 40 square microns, it consumes hundreds of picojoules of energy. According to the university, this is tens of thousands of times less than a conventional collision avoidance sensor would require.
Used at night, the device measures the relative distance of cars simply by measuring changes in headlight intensity. The brighter the light, the closer the car is. When tested in a real-world driving scenario, the sensors were able to predict him two to three seconds before a two-vehicle accident occurred. It may not seem like a big deal, but it will give the automated driving system (or the driver himself) plenty of time to take corrective action.
The technology probably won’t replace existing systems, but scientists say conduct “We strongly believe that the proposed collision detector can enhance the existing sensors needed to ensure the safety of autonomous vehicles.”
The study is described in a paper recently published in the journal. ACS Nano.
Source: American Chemical Society
