Traffic Planning in the Age of Self-Driving Cars

A company called Sidewalk Labs, which is reported to have “spun off from Google”, has announced a platform to help city managers and traffic planners deal with the driverless car revolution.

It’s all pretty abstract right now, because their platform isn’t actually in use yet, but the federal DoT will be announcing grants to cities and the Sidewalk Labs platform will come along with the grant.

So far this sounds like a “not a big deal yet, but keep it in the back of my mind” kind of program. I wish them success.

But what really got me thinking is whether the driverless car revolution will require traffic planning, or whether planners will really even be able to control it.

Backlash is already growing against apps like Waze, which route human drivers through residential neighborhoods to avoid highway traffic. In spite of the backlash, I assume that only a small percentage of drivers are actually even capable of pulling this off.

But once the computer is driving the car, the road network will be utilized to maximum efficiency, even if that’s unpleasant for people living on now-quiet residential streets.

In the future, will planners be able to funnel self-driving cars onto the desired thoroughfares, or will the computers always be ten steps ahead?

Alaska Would Like Google’s Cars

Alaska is pitching Google on testing its self-driving cars in The Last Frontier.

And Google is at least taking the idea seriously enough to send a representative up to talk with state officials.

Inclement weather is one of the biggest challenges facing autonomous vehicles, and Alaska is a good place to find and test against inclement weather.

This story is of particular interest to me because I was born in Alaska and have strong family ties to the state. It would be super-cool if this came to fruition.

Baidu Cars

Baidu has announced a plan to test autonomous cars in the United States, and to build commercially viable cars by 2016, according to The Verge.

The Verge notes that Baidu previously announced a partnership with BMW to launch a car by 2016, and that plan did not bear fruit. So, caveat emptor.

The current plan is interesting however, because Baidu’s chief scientist, Andrew Ng, is on-record as stating that self-driving cars are not yet technically feasible. Ng, by contrast, has favored self-driving buses on well-defined and limited routes.

Google Applies a Little Pressure to Uber

Google Applies a Little Pressure to Uber

One of the elements of the self-driving car industry that fascinates me is the interplay of cooperation and competition between companies.

Google is the most interesting company in this regard, because Google is so large that it touches many different elements of other businesses.

For example, Google Ventures has invested money in Uber, Google Maps supplies Uber, [Google] Android is Uber’s largest platform, and yet [Google] X is building self-driving cars that might compete with Uber.

And recently, Google Maps began directing users to services that compete with Uber.

In some countries, searching for a route from one destination to another now prompts Google Maps to provide information about Uber and about competitive ride-sharing services.

Interestingly, the US is not in that list of “some countries”. Google Maps does not promote Lyft in the US, only Uber. So far.

The Opposite Point of View

I am a big fan of self-driving cars and hope they come to a street near me as soon as possible. Tomorrow, even.

So it’s helpful to remember that there are well-intentioned people, smarter than me, who are decidedly more skeptical.

Missy Cummings, a robotics professor at Duke, is one of those people. And yesterday, Cummings testified to Congress to that effect.

I am decidedly less optimistic about what I perceive to be a rush to field systems that are absolutely not ready for widespread deployment, and certainly not ready for humans to be completely taken out of the driver’s seat.

According to reports, Cummings’ objections focused primarily on driving in bad weather, and on cyber-security.

Both of those seem to me like known and solvable problems. And, in that vein, representatives from Google and GM testified that they were much more optimistic about self-driving cars.

But it’s helpful to remember that all the smart people aren’t 100% in agreement about this.

Honda’s ADAS System

Honda has flown below the radar in the self-driving car world, compared to manufacturers like Tesla and Ford.

This week, though, Honda announced its own ADAS suite that allows drivers to ride along with their hands off the wheel and their feet off the pedals, “as lane markings are visible and another vehicle is in front of the car”.

The requirement for another vehicle to be out front is particularly interesting. It may map to the US Army’s project of building self-driving truck convoys that can follow the truck ahead of them, with a human driver at the front of the line.

As manufacturers each launch their own ADAS systems, with different names and features, it’s increasingly difficult to keep track of who supports what. I’ll be curious to see whether this represents a big step into the self-driving car world for Honda, or just a natural addition of features that more or less match what competitors offer.

A big selling point for Honda is price, so maybe this represents the ability to mass product ADAS systems for $20,000 cars.

Mixed Messages from the NHTSA

The National Highway Transportation Safety Administration has recently been an important booster for self-driving cars.

Although it’s not clear how much sway the agency has (most US transportation laws are implemented at the state level), the NHTSA has been trying to clear a legal path for self-driving cars.

Friday, however, the NHTSA qualified their support somewhat, and made clear what development direction they favor.

The National Highway Traffic Safety Administration (NHTSA) said on Friday that self-driving cars — which do not have steering wheels or brake/gas pedals — can be made available for purchase by in the US only after they clear some potentially ‘significant’ legal hurdles.

However, NHTSA spokesman Gordon Trowbridge said pointed out that a new report released by the agency on Friday shows there were fewer legal hurdles in deploying self-driving cars with human controls, compared to fully autonomous cars.

The NHTSA appears to taking sides in the split over whether to develop “Level 3” vehicles, or skip right to “Level 4”. Level 3 vehicles require mechanisms for the driver to take over from the computer, whereas Level 4 vehicles entrust the computer to drive in all situations.

Tesla is working on, and indeed has released, Level 3 technology. Google and many auto manufacturers, however, are hoping to skip Level 3, citing the complexity of transferring control between the human and computer drivers.

The California Blog has a little more depth on the NHTSA’s statements.

Image Annotation

Image annotation is an interesting and surprising problem that many autonomous vehicle researchers are struggling with.

The issue is that its easy to send a car and a camera out into the world to collect data, but its time-consuming and expensive to label that data.

And the labeling is necessary in order to train the machine to read the data.

Think about lane lines, for example. Lots of companies can now capture millions of images of roads, in all sorts of conditions. But in order to find the lane lines, the computer models have to be trained. And training the models involves telling them where the lane lines are in the sample images.

Lots of academic researchers use Amazon’s Mechanical Turk, a job system where cheap workers overseas can pick up manual tasks from companies in the US and elsewhere. But that is both expensive – even the world’s cheapest workers become expensive when asked to perform billions of tasks – and slow.

There doesn’t seem to be a solution yet to this problem.