Brad Templeton

Baidu Apollo Robotaxis froze in the middle of lanes, stranding passengers and causing crashes. What didn't Baidu learn from Waymo and what might we suspect about the cause?

Pony.AI is doing their first European deployment in Zagreb in concert with Croation robotaxi company Verne because it's a quick way to demonstrate

It's counter-intuitive, but smaller, van-sized vehicles can make more energy-efficient transit than buses and trains, because better service means less empty seats, thanks to self-driving

Flying cars, self-driving vans and full traffic metering probably can't be fully ready in 2028, but some modern technology can help to reduce the traffic nightmare.

Waymo has been scaling fast, now reporting that they do 500,000 rides/week. As this grows, we should expect to see more and more stories about mistakes.

A recent update to the California regulations around self-driving cars “fixes” a flaw in the earlier rules--it wasn't clear how to cite a self-driving

The Waymo robotaxi service has been having a bad week, particularly in dealing with flooded roads. Waymos have driven into flooded streets and gotten stuck.

Through a mix of luck and skill, I happen to have made the most accurate prediction of the timelines for robotaxis back in 2013.

As a robocar team progresses towards its eventual goal of making a fully unsupervised vehicle that can drive without the full-time involvement of a human, they will go through many steps.

Waymo's new study refines autonomous vehicle safety comparisons by factoring in incident rates specific to location, road, and time, aiming for a true "apples-to-apples" evaluation against human driving. This approach provides crucial data for regulators to assess if robocars genuinely improve overall road safety, contrasting with past misleading claims like Tesla's exaggerated 10x safety improvement. The article stresses that robocars will always make mistakes, and public focus on individual incidents often overshadows the larger goal of reducing serious injuries. Regulators should prioritize data showing improving mistake rates and potential for significant risk reduction, even tolerating minor inconveniences. The focus should be on public interest goals, not prescriptive technical standards.