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Self-Driving Cars Won’t Save Us
Better solutions are right in front of our eyes
When you read Elon Musk’s blustering declarations about LIDAR, the laser scanning technology most self-driving cars rely on, it’s easy to imagine the words coming out of Donald Trump’s mouth.
“Anyone relying on LIDAR is doomed. Doomed,” the Tesla CEO said at an event for investors in April. “Expensive sensors that are unnecessary. It’s like having a whole bunch of expensive appendices… you’ll see.”
LIDAR, short for light detection and ranging, is a light beam sensor that, combined with cameras and radar, helps autonomous vehicles “see” their surroundings and avoid collisions. Nearly all of Tesla’s competitors think of LIDAR as an essential pillar to driverless capabilities. Yet Musk claims that advances in artificial intelligence-powered cameras will make LIDAR unnecessary. As the Verge’s Andrew J. Hawkins noted from the event this past spring, Musk has a long history of trash-talking the technology. He thinks it’s “lame.” But oftentimes, the most practical solutions are just that — kind of boring.
Driverless cars have been the height of technological aspiration for decades. But flooding roads with fully autonomous vehicles — if that’s even possible — will do little to solve our most pressing transportation problems. The dream of a safer, greener driverless car that reduces traffic and allows you to take a nap is still just that: a dream. When it comes to transportation, the best solutions prioritize accessibility and efficiency, not personalized luxury.
Self-driving technology continues to receive billions of dollars in funding and free publicity for one simple and obvious reason: The idea is cool. Still, even the trendiest CEOs and investors know they need more than social cache to sell a product.
Proponents of driverless technologies say that, in theory, cars would use sensors and algorithms to cut out much of the human error that leads to crashes. The vehicles would communicate with one another and incorporate traffic patterns to choose routes that cause less gridlock. Reducing traffic should reduce driving time and emissions. And allowing an algorithm (rather than lead-footed humans) to control acceleration and braking can also decrease fuel usage.
