Self-driving cars are trained to be overly cautious, but there may be situations where they need to make high-speed maneuvers to avoid a collision. Can these vehicles, festooned with tens of thousands of dollars worth of high-tech sensors and programmed to drive at grandma-speeds, handle these split-second decisions like a human?
Engineers at Stanford University may have the answer. They created a neural network that can enable driverless cars to perform high-speed, low-friction maneuvers just as well as race car drivers. When they eventually arrive, driverless cars will need capabilities beyond those of humans, as 94 percent of crashes are attributable to human error. Researchers say this is an important step in improving autonomous vehicles’ ability to avoid accidents.
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Python for Microcontrollers – Adafruit Daily — Python on Microcontrollers Newsletter: CircuitPython 2025 Wraps, Focus on Using Python, Open Source and More! #CircuitPython #Python #micropython @ThePSF @Raspberry_Pi
EYE on NPI – Adafruit Daily — EYE on NPI Maxim’s Himalaya uSLIC Step-Down Power Module #EyeOnNPI @maximintegrated @digikey
