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Published on November 8th, 2015 | by Kyle Field


As Tesla Speeds On Towards Autopilot, Toyota Veers Off The Beaten Path

November 8th, 2015 by  

Autopilot Today

Tesla’s release of its v7.0 firmware last month brought with it the first of its highly anticipated autopilot software suite to the streets. With the initial launch, the masses were nervous about taking their hands off the wheel, but managed to get over their fears enough to try it out. Videos began surfacing of people turning on autopilot and their nervous but excited reactions… then too quickly moving to over-confidence bordering on just plain stupid, and even a few near misses that seemed to have been the fault of autopilot.

Several days later, there were stories of autopilot saving the day, multiple stories sharing that autopilot was improving, and not just in small ways, but very quickly, dynamically, on a day-to-day basis. Tesla shared news of an early update in the works dubbed v7.1, which promised more large features and several bug fixes. Overall, the reception was positive and truly set the high-water mark for autopilot features across the industry.


Tesla’s approach has been different than others in the industry when the specifics are torn apart, but at a high level, it’s a suite of highly responsive sensors working together in tandem to give the car the best understanding possible of what’s happening. That data, combined with the already known vehicle mechanical logic (traction control, speed, etc) is then rolled up with fixed logic and dynamic intelligence that must decipher the wide variety of inputs being presented to drive the car. Easy, right? Not on your life.

Autopilot Looking Forward

A recent article posted on sister site Gas2 shared insights from BMW’s R&D Chief Klaus Fröhlich into just how challenging developing this logic is/will be:

The software is still far less capable of making instantaneous decisions when an unexpected situation occurs than a human driver is. In an emergency, Fröhlich asks, “Do I steer into a wall? Do I steer into the human being? Do I steer into the oncoming truck? What will I do? This technology causes many headaches,” he says, “And, honestly, because it has to prevent accidents, it has to be state-of-the-art.”

He also disagrees with those who say that autonomous driving will eliminate traffic accidents. “There will be accidents with autonomous cars, it is very clear, because people behave randomly. This… also places a particular burden on the vehicle manufacturer. A child runs on to the road. As a vehicle manufacturer, I have to prove that I have done everything to account for the environment as best as possible. And we need regulations for when these accidents occur.”

Toyota the Divergent

With most of the incumbent auto manufacturers touting R&D models that “did this 10 years ago” or have this one feature built in on a tech package nobody bought, one is taking a sharp turn from the raging river that is autopilot and throwing a cool $1 billion dollars at it — Toyota. Well known to be a deviant, having challenged the masses pursuing electric vehicles as the solution to zero-emissions personal transport with its hydrogen fuel cell–powered Toyota Mirai, we should have known it would be the one to chart a new course. Toyota has turned to one of Elon Musk’s arch nemesis — AI — to solve the riddle of autonomous driving. Musk has long been publicly cautious of AI to the point that he has intentionally invested in leading AI firms to keep tabs on them from the inside.


To translate its goal of autonomy through AI, Bloomberg View shared the news of Toyota’s announcement of a $1 billion dollar investment to found its new Toyota Research Institute in the US. It did not share timing on when it foresees autonomy or even autonomous features being available in its vehicles, but it did lay out some of the high-level goals of the Institute:

3 Goals of the Toyota Research Institute

Without a firm definition of its specific intentions with Artificial Intelligence, Toyota framed its approach with 3 high-level goals, with safety being the first and foremost. Like many other car companies, Toyota would like to use AI technology in its vehicles to improve the safety of its vehicles regardless of driver actions. This sounds on the surface like Tesla’s active safety features and can be found on many high-end cars with alerts, automatic braking, etc.

Second, Toyota aims to improve accessibility with its AI-enabled vehicles, making personal transport available regardless of physical challenges. As medical technology improves our ability to sustain and extend life, improving the capability of personal transport to accommodate and enable persons with accessibility challenges is a key to maximizing their quality of life.

Finally, robotics to allow our aging population the dignity of aging while providing mobility throughout.


Serial vs Parallel Autonomy

Toyota framed up these goals against two specific application classes — serial and parallel. With serial autonomy, the car will do everything — from driving a drunk driver home (who is presumably unable to back a “backup driver” in an emergency) or a driver who chooses to sleep while the car drives home/to work/etc. This is essentially the full autonomy that everyone is aspiring to, possibly with several iterations as features are vetted and released.

Parallel autonomy is essentially active safety features that can and will dynamically monitor for hazards and respond in parallel to a human driving the car to its destination. I can imagine this evolving over time into a more robust autopilot-style suite, though this was not discussed. It starts with the barebones safety — slow and/or stop when car in front slows, respond to a car merging into the lane, alert the driver when approaching an object in front too quickly, etc, then adds on features to manage cruising on the highway, staying in the lane, dynamic speed changes… much like the Tesla autopilot we know today.


Odd Bits

Much like the recent Tesla quarterly update call, there were 2 nuggets shared in the video that stood out to me.

  1. Toyota wants to apply AI much more broadly.
    Toyota plans for the AI generated from its new center to be applied much more broadly than in Toyota vehicles or even in the automotive industry. This presents a new opportunity for Toyota to leverage a single platform and technology to drive business (see what I did there? :P). The possibilities are quite open ended at this point, painting broad swaths of industry.
  2. AI can be used to schedule cars.
    Of note, Toyota shared that its AI could be used to schedule cars. The obvious connection is with Toyota cars, leveraging their integrated AI into a competitive advantage for the brand when being considered for transportation services like Uber, Lyft, etc to manage fleets and operations thereof. I’m not going to speculate like many have coming out of Tesla’s earnings update, but it did trigger me to listen closer for a bit.


In Summary

With Tesla’s autopilot live in the field, Toyota is behind the 8 ball to deliver solid serial and parallel offerings… and to do so quickly. Toyota acknowledged that “we are just beginning now” at least 3 times, so the company knows it has a bear of a task ahead and the sheer magnitude of its initial investment speaks volumes about its thoughts on what’s needed to deliver and where this falls in its order of priorities.

The full press conference where Toyota broke the news on its investment in a new Toyota Research Institute in the US is on YouTube. The actual talk is only ~15 minutes and is followed by Q&A and a photo session (yup).

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About the Author

I’m a tech geek passionately in search of actionable ways to reduce the negative impact my life has on the planet, save money and reduce stress. Live intentionally, make conscious decisions, love more, act responsibly, play. The more you know, the less you need. TSLA investor. Tesla referral link: http://ts.la/kyle623

  • Brent Jatko

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  • JH

    Google already have autonomous vehicles. And the accident statistics to prove that they are better than humans. So toyota have a bit of catching up to do

    • Brooks Bridges

      But Google’s approach requires minute information ahead of time about roads travelled – an enormous amount of data. Good for some scenarios but not applicable to everyman driving everywhere.

      • JH

        That is a popular but in many aspects faulty image of Googles solution. It is quite capable to interpret images and make it’s own decisions based on the current situation. It can, for instance, handle constructions works and redirections on its own. It is however true that a good map helps the car. But that is true in the tesla case as well. Both solutions collect map data on their own and transfers it to the cloud for other cars to grow their experience.

  • NRG4All

    I’ve driven over 300,000 miles by motorcycle and am here to tell about it with all of my faculties intact. In more ways than one, that was no accident. There are two rules that should apply to autonomous cars. First is the two second rule. After the car ahead passes some point, you count “one thousand one, one thousand two” at which you should be passing the same point. That shouldn’t be too hard for the AI car to do. However, the second point is the 12 second rule. You should be looking ahead about 12 seconds down the road. At that point you assess what possibly could happen. Is there a car on a side road waiting to enter? Or, is there a car facing you that may make a left turn in front of you when it reaches the intersection? Whatever the circumstance, the 12 second rule allows you time to assess the situation and to form a plan to avoid a collision if what you suspect can happen, does happen. That rule has allowed me trouble free motorcycle driving, but IMHO it will be a long time before AI can make such assessments at those distances.

    • JH

      Google already do this, and better than humans (and can back it by actual and public accident statistics). There are some interesting ted talks on the subject. So the real problem at the moment isn’t really technical as much as it is a legal and law problem. And yes, there is also the question of public acceptance. Technically the first generation is already ready and large scale test are being done in public. It will still take at least 5 years before it will be widely spread. But it will be spread and it will go very fast indeed.

  • mike_dyke

    The problem with full AI is that you’re completely replacing the human driver. The human is a complex device with a facility for working out “What happens if…” situations. Any replacement system has to be able to handle all of the situations – even those you haven’t thought of.

    With any large/complex system, there are basically two development approaches you can use – The “Big Bang” approach where you effectively throw a switch and go from the old system to the new without being able to go back to the old system. The other is the “Gradual” approach where you introduce small bits at a time gradually building up to the point where you can turn off the old system.
    Using the “big Bang” approach, you have to have trust that the system will work correctly in all situations first time – bit like a rocket being launched. This is probably not going to happen with AI as the customer has not got that trust in the system yet, so a better approach is the gradual approach that Tesla’s using – do a little bit at a time and let the customer build up trust to the point where they can take a nap and let the car drive if they want to.

    Toyota seem to be favouring the “Big Bang” approach – Highly risky and in my opinion a mistake.

    • Kyle Field

      Elon talks these two as autopilot (the gradual approach) and autonomous driving (big bang). Toyota calls them parallel (gradual) and serial (big bang). They have the same ideas and see that one can lead to the other. Google is going full auto and shooting for big bang from the get go with their cars that don’t have a steering wheel at all.

  • Wilibald Oplatek

    The fact that they used the generic “AI” term shows that they have no idea what to do. Throwing a pile of money into some research institute does not magically enable them to instantly overtake Mobileye and Google. Toyota management seems to be getting increasingly disconnected from the reality in their decisions.

    • Kyle Field

      I agree. I’m still disappointed that they are effectively handing over the reigns of eco leadership to Nissan, having developed no successor to the Prius.

      I am hopeful that something will come of this as while money can’t buy everything, this is a significant investment that can enable autopilot/autonomous driving through an external partner much faster than otherwise. Time will tell…

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