Iâve been in Bangalore, India, for the last two days and it has been a delightful trip. The traffic here is fiercesome, though. Even within India, Bangalore has a reputation for congestion on the roads.
Many of the Indians Iâve spoken with look at the traffic here and express skepticism that self-driving cars will ever come to India, or at least any time soon.
I suspect self-driving cars will arrive in India sooner than people expect, though. The key will be that the first experiments will start just as they did in the United States: in locations chosen specifically for their ease of driving.
For years, self-driving cars in the US only operated in Silicon Valley and Las Vegas. And there was a reason for that. Those locations are flat and sunny, and the streets are rectilinear. Even now, Waymoâs first public rollout is in Phoenix, which is flatter, sunnier, and more rectilinear still.
Something similar will happen in India. Self-driving cars wonât come to Bangalore firstâââthat would be crazy. Theyâll come first to private campuses and controlled-access public roads with good pavement and markings, where the challenge of getting self-driving cars to work will be more manageable.
Over time, self-driving cars will expand their footprint, in India and elsewhere, but there will be learning curve. Just as self-driving cars in the US have now reached Detroit and Pittsburgh and even Boston, eventually self-driving cars will get to Bangalore.
Lyft is serious about self-driving cars. Last fall, they announced they were funding 400 scholarships for Udacityâs Intro to Self-Driving Cars Nanodegree Program, with a focus on increasing diversity in the autonomous vehicle industry.
Today, Lyft and Udacity announced the Lyft Perception Challenge to identify top Udacity students to interview for positions on Lyftâs Level 5 self-driving car team.
The project requires students to use computer vision techniques to identify and locate vehicles on the road. These are the same skills taught in the Udacity Self-Driving Car Engineer Nanodegree Program. We are excited to see what students develop even above and beyond what we teach in class!
Udacity Self-Driving Car students and alumni are invited to participate. The top 25 students with US work authorization will earn interviews with Lyftâs team. The top 150 candidates from around the world will be invited to special interview preparation workshops with Udacityâs Career Services team.
Our goal on the Udacity Self-Driving Car Team is to help connect as many students to jobs as possible. We are excited to be working with Lyft to achieve that goal and make self-driving cars a reality for everyone.
No surprise there. After all, it was the DARPA Grand Challenge that kicked off the autonomous vehicle revolution.
But this line struck me:
âAccording to [Undersecretary of Defense Michael] Griffin, 52 percent of casualities in combat zones are attributed to military personnel delivering food, fuel and other logistics.â
The post doesnât break out what portion of those causalties come from logistics personal who are attacked, versus just plain old vehicle collisions. But itâs plausible that a lot are due to collisions that donât involve troops being directly under attack.
The framework is currently modest, as expected for a first release, but helpful. And the point of the exercise is to engage the self-driving car community in building out a robust, open-source solution to autonomous vehicle testing.
What gets me really excited about this is the potential to create a path toward test-driven development for autonomous vehicles.
The Ruby on Rails world, which was my world for years, is fanatical about testing. Theylovetestingsomuch. One of Railsâ engineers most beloved development principles is Test-Driven Development.
TDD is the process of designing and developing your code using tests first. The mantra âred-green-refactorâ is familiar to any Rails engineer, as TDD requires:
Writing a test case
Verifying that the application fails the test case (red)
Writing the application code to pass the test case
Watching it pass (green)
Fixing and improving the application code (refactor)
Verifying that the application code still passes the test case
Rinse and repeat.
I loved this cycle as a Rails engineer and I love the idea that a public testing framework for autonomous vehicles could provide a red-green-refactor cycle for autonomous vehicle developers.
Take a self-driving car scenario. Watch the virtual driver software fail. Write the code to pass the scenario. Watch the virtual driver pass. Refactor. Verify that the virtual driver keeps on passing that test case forever.
Of course, we donât need a public, open-source testing framework to do this. Any self-driving car engineer anywhere can use TDD by themselves. But a public test suite would take a lot of the work out of TDD, by pre-specifying the hurdles that developers need to clear.
Hopefully that would lead to safer self-driving cars, sooner.
Didi Chuxing (a Udacity partner, ahem) has been in the news on a few fronts this week, and will probably show up a few more times with the upcoming Beijing Motor Show this week.
On the more traditional, human-driven, ride-hailing front, Didi is moving into Mexico, with a new office in Toluca. This seems ever-so-close to the lucrative US market, currently dominated by Uber and Lyft.
Building a self-driving car from scratch seems like a pretty big deal to me. Tesla is famously struggling with the challenges of manufacturing a car, and even automotive manufacturers like GM/Cruise are basically re-purposing existing vehicles into self-driving cars.
By contrast, Didi believes:
ââŚcurrent mainstream cars are heavily âoverspeccedââââpacked with equipment most drivers do not need such as engines and other technologies that allow them to go as fast a 150 mph (250 kmph).
Performance levels for ride-hailing and car-sharing service vehicles could be dialled down significantly, meaning they would not have to be so aerodynamic. Cars designed to carry just one or two people at a time to work or the shops could therefore be âboxierâ, with fewer seats and more space for luggage.â
Iâm excited to see what Didi comes up with for its âpurpose-builtâ self-driving cars. Big risk, big reward.
To try and answer this question, Iâll begin with a story. In October of 2016, Udacity welcomed the first class of students into our Self-Driving Car Engineer Nanodegree program. Since that historic debut, we have been delighted to enroll over 11,000 students around the world in this program!
Along the way, we learned that while people across the globe were thrilled at the prospect of being able to work on autonomous vehicles, not all of them were equipped to do soâmany of them needed additional training to get ready for the rigors and challenges of our curriculum.
In order to provide a viable point-of-entry for these eager learners, we built the Intro to Self-Driving Cars Nanodegree Program, and welcomed the first class of students at the end of 2017. This âIntroâ program prepares students with the fundamentals in Python, C++, calculus, linear algebra, statistics, and physics that are necessary to become a Self-Driving Car Engineer.
Both Nanodegree programs are paths to a career in the self-driving car field, but the goals of each program are distinct, as are the skills one learns.
The Self-Driving Car Engineer (SDC) Nanodegree program is an advanced program in which students write programs in Python and C++, and learn new frameworks like ROS and TensorFlow. Students entering SDC should be able to write programs from scratch, and should be comfortable with both calculus and linear algebra. SDC does not require solving differential equations by hand, but does require that students be comfortable interpreting mathematical notation and translating it into code.
The Intro to Self-Driving Cars (iSDC) Nanodegree program is an intermediate program that requires entering students to have only minimal programming and math knowledge. Students entering iSDC should be comfortable reading and modifying code in at least one language (Python helps, since that is first language the program uses). Entering students should also be comfortable with high-school algebra. From there, iSDC teaches the trigonometry, calculus, linear algebra, statistics, and physics that are necessary to succeed in the advanced SDC program.
iSDC does not require an application to enroll, and everybody is welcome. However, students with no programming experience at all might consider starting their journey with Udacityâs Intro to Programming Nanodegree program, and then proceeding on to Intro to Self-Driving Cars. A slightly more mathematical (and more challenging) alternative first step would be Udacityâs Data Analyst Nanodegree Program.
Waymo is working with a number of California cities to set up driverless tests, several of which appear quite enthusiastic to be working with the leader in self-driving cars.
âAutonomous vehicle technology âis going to be crucial in helping the Silicon Valley reach its safety and transportation goals,â said Los Altos Councilwoman Jeannie Bruins.
âWaymo has done extensive vehicle testing on our local streets with a good safety record,â Mountain View City Manager Dan Rich, said in a statement. He commended the company for committing to âtransparency and information sharing.â
In Sunnyvale, Mayor Glenn Hendricks likewise said he looks forward to working with Waymo.â
One angle I found interesting is how Waymo will handle disengagements:
âIf one of the cars encounters something it doesnât understand, such as complicated road construction, the car will contact Waymo for help recognizing the situation. After human testers give it feedback, the car will then decide how to navigate the situation.â
I wonder what it means for a remote âhuman testerâ to âgive feedbackâ to a Waymo vehicle.
And donât forget, from my old colleague Oliver Cameron:
đ¤Â The real question here is who else applied to do driverless testing in CA? https://t.co/0rCZl54bsa
China recently released some basic guidelines for self-driving car development. As an American, I donât always fully comprehend the line in China between private companies and the government. How much guidance to self-driving car developers in China get from published laws and regulations, and how much comes from internal communication with the relevant government agencies?
âThe rules lay out requirements that vehicles must first be tested in non-public zones, that road tests can only be on designated streets and that a qualified person must always sit in the driverâs position, ready to take over control.â
As best I can tell from English translations, that is the extent of the rules. Presumably there must be more, but I donât know if the rest is available in Chinese, or if you have to be in the industry there and know the right people to figure it out.