[bo1024]

My opinion as a researcher in AI/ML but without any expertise in self-driving tech:

We are a long way from where I would be willing to trust my life to self-driving cars - as a passenger, as another driver on the streets, as a cyclist, or as a pedestrian. Much farther away than these companies press releases make it seem.

Here's why. These driving algorithms are successful in large part because of data. They train their systems, such as visual recognition (what are the objects in the world around me), on millions of miles of visual data collected on the roads, most of it in California in the sunny daytime.

This means they are very likely to perform well in the average case when everything goes according to plan. And if deployed there they might live up to the hype and save thousands of lives compared to human drivers.

But now say you're in a major city in the midwest or northeast, for instance. It may be night time. It might be raining. There might be two feet of snow on the ground, narrow lanes, road signs covered up and unreadable. There may be a pedestrian crossing in dark colors. The street lines may be faded or nonexistent. There may be a street that is marked one way on the GPS map but is currently detoured the opposite direction due to construction.

There may be a policeman directing traffic. The police might pull the car over and direct it to a parking lot. There might be a fire truck or ambulance coming at an unusual time.

A computerized system trained on data can only perform well in situations very similar to its training set. But its vision will have a hard time recognizing objects it hasn't seen before. Its language processing will not understand unusual or novel road signs. Even if it recognizes the objects around it correclty, it lacks the "true" intelligence to deal with unforeseen situations falling significantly outside its training set.

I believe that cars are quite likely to run into novel situations they haven't experienced before, and I don't trust their reactions or decisionmaking in these scenarios. So I think what we have are self-driving cars that perform very well in the common, easy case, as we have already seen in numerous press releases, but are in my opinion very unpredictable in the long, fat tail of situations.

[vladimirralev]

I think you are missing the most important part here. These cars are always online and share data between them. They have a detailed map of every street and every road bump and every road pole/sign that can be used for navigation. Even if everything is in snow and the camera/lidar is frozen and can't see anything, these cars know exactly where they are and where the road is from predictive navigation based on speed, direction, road shape/bumps from previous data that was collected from 1000s of passes before that on that very same road. At first AI cars will probably avoid certain areas that have not been mapped. Each car will signal any unexpected road blocks, data will be sent realtime to a human operator who will script a walkthrough in seconds. Such as "ok, you are legitimately stuck in traffic right now, just wait" or "ok, there is a crashed car ahead of you so the right-turning lane is closed, move into the left lane and you can turn right from here as an exception". There will be humans like ATC in all cases.

Police and emergency services will just coordinate with the "ATC" to pre-script routes differently depending on the situation.

[greenleafjacob]

Dead reckoning is pretty bad by itself but with GPS it probably wouldn't be too bad.

[walrus1066]

Also, communicating and negotiating with human drivers. You have to do this all the time in a city like London, mostly on two way roads where there's only room for one car, due to obstacles (roadworks) or parked cars.

In complex situations, flashing lights and honks are not enough, you need to verbally communicate with other drivers.

I would eat my hat if an AI could handle these kinds of situations.

So in short, I'll believe the hype when I see a video of a full auto drive through London at rush hour.