In a line reminiscent of Steve Jobs’s famous defence of the iPhone 4’s flawed antennae—“Don't hold it like that” — these technologists say the problem isn’t that self-driving cars don’t work, it’s that people act unpredictably.
“What we tell people is, ‘Please be lawful and please be considerate,’” says Andrew Ng, a well-known machine learning researcher who runs a venture fund that invests in AI-enabled companies, including self-driving startup Drive.AI. In other words: no jaywalking.
Whether self-driving cars can correctly identify and avoid pedestrians crossing streets has become a burning issue since March after an Uber self-driving car killed a woman in Arizona who was walking a bicycle across the street at night outside a designated crosswalk.
The incident is still under investigation, but a preliminary report from federal safety regulators said the car’s sensors had detected the woman but its decision-making software discounted the sensor data, concluding it was likely a false positive.
Google’s Waymo has promised to launch a self-driving taxi service, starting in Phoenix, Arizona, later this year, and General Motors has pledged a rival service — using a car without a steering wheel or pedals — sometime in 2019. But it’s unclear if either will be capable of operating outside of designated areas or without a safe driver who can take over in an emergency. Meanwhile, other initiatives are losing steam.
Elon Musk has shelved plans for an autonomous Tesla to drive across the US. Uber has axed a self-driving truck program to focus on autonomous cars. Daimler Trucks, part of Daimler AG, now says commercial driverless trucks will take at least five years. Others, including Musk, had previously predicted such vehicles would be road-ready by 2020.
With these timelines slipping, driverless proponents like Ng say there’s one surefire shortcut to getting self-driving cars on the streets sooner: persuade pedestrians to behave less erratically. If they use crosswalks, where there are contextual clues — pavement markings and stop lights — the software is more likely to identify them.