Chinese company unveils prototype of self-driving bus

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After three years of development, one of the leading Chinese bus manufacturers Yutong has sent the prototype of a self-driving city bus on a 32 km long circuit on an intercity road between Zhengzhou and Kaifeng in Henan Province. The bus drove the whole track in regular traffic without any human assistance, attained a peak speed of 68 km/h, passed 26 traffic lights and was able to change lanes and overtake autonomously. This is a significant accomplishment and clearly puts Yutong on the map for autonomous driving.

The bus is equipped with many sensors, including camera and Lidar. Two Lidar sensors are strategically placed in the middle of both sides of the car. This is the best way to monitor the adjacent lanes and mimics the approach Google has taken on their driverless pods (where the side Lidars protrude like the mirrors of conventional cars).

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Image source: Yutong, 2015.

The company’s press release points out that significant additional development is required. No further information about the timeline for the introduction of such a bus was provided.

Self-driving buses are very promising and will be a key ingredient of future mobility. On demand-buses will be able to service the complex mobility demands of our societies much better than today’s mix of scheduled buses, trains, and individual cars. They will lower the cost, resource consumption and ecological footprint of mobility. Because significantly lower costs will prompt many travelers to use buses on medium to long-distance trips instead of cars, these buses will increase the effective capacity of highways when measured in people-miles.

 

Source: Yutong Bus Company, Dailymotion video

Update 2016-02-21: The bus traveled between Zhengzhou and Kaifeng in Henan Province. The approximate route can be looked up on Google maps.

Autonomous vehicles could reduce Australian road infrastructure growth by a factor of three!

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A report issued by Australian telecommunications company Telstra shows that autonomous vehicles could save Australia billions of dollars in traffic infrastructure investment. With conventional vehicles, the capacity of the road network would need to more than double (to 250%) over the next 35 five years to accommodate increased mobility demand. Self-driving cars, however, use the road more efficiently and require less road capacity. Based on the assumption that autonomous vehicles will be introduced into the market by 2020 and their adoption will grow linearly until all vehicles can drive autonomously twenty years later the study finds that road capacity demands will peak around 2033 at a level 50% larger than today’s road infrastructure and then decline towards today’s road infrastructure levels by 2039.

The study clearly shows that infrastructure planners need to adjust their estimates of road network growth to the advent of self-driving cars. With these cars governments can  reduce road infrastructure spending by billions of dollars. It is time to fundamentally rethink the current approach to infrastructure planning!

Impressive as the potential savings identified in the study are, additional effects may further reduce infrastructure needs: The study did not consider impending structural changes in mobility: Autonomous vehicles will lead to an increased use of mobility-on demand services which change the distribution of trip patterns during the day and increase ride sharing in various forms. Both effects will further reduce the peak load on our roads.

It is time to seriously consider the implications of self-driving cars. Rather than investing in concrete and asphalt, governments should accelerate the adoption of autonomous car technology today. This lowers accident rates, reduces the ecological footprint of mobility and increases the competitive position of first-adopter countries.

Google restructures for its bet on self-driving cars

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Google has announced a major corporate restructuring where all Google shares are transferred into Alphabet, a holding company. The new structure is much better suited for Google’s self-driving car ambitions – which may quickly grow into a billion dollar industry . This restructuring is a well calculated move to position Google for the road ahead into self-driving cars/driverless mobility, robotics etc.

It shows how serious Google is about making a major impact in fields outside of its ‘traditional’ internet-centric business.  It is also interesting that Google’s announcement carefully avoids mentioning those activities with the highest revenue potential – such as self-driving cars. Instead they just speak of much smaller activities in Life-Sciences (glucose-sensing contact lenses), longevity and drone delivery.

The Alpha-bet is indeed – as the founders indicate in their announcement - a major bet on the future. A decade from now  Alphabet’s revenues from mobility and robotics could eclipse Google’s web business.

 

 

Misconceptions of autonomous cars

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Self-driving cars are a rapidly evolving technology which only a few years ago was still considered science fiction. In such a dynamic context, quick intuitions can be very misleading and misconceptions about the technology, its impact, and the nature of the innovation process abound. In a short article we examine the following four misconceptions:

  1. Driver assistance systems will evolve gradually into fully autonomous cars
  2. The first models of fully autonomous cars will be targeted to the consumer and will be available for purchase
  3. It will take decades until most of the vehicles on the road are capable of autonomous driving
  4. Self-driving cars are controlled by classical computer algorithms (if-then rules)

Driverless car revolution: Buy mobility – not metal

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driverless-car-revolutionA new book by Rutt Bridges examines the impact of autonomous vehicle technology on mobility. It is an excellent read, a thought-provoking book which paints a very detailed picture of the future of mobility. It is a wake-up call for the auto industry and a must-read for anyone involved with transportation policy.

Book description:

Imagine a future without congestion, car crashes, smog, or road rage. It’s coming sooner than you think. Summoned with an Uber-like smartphone app, driverless cars will revolutionize transportation. For less than bus fare you’ll enjoy the quiet, comfortable door-to-door service you’d get from a personal chauffeur. A chauffeur that is never distracted, never tired or testy, and always knows the fastest and safest route to get you where you’re going. No cash, no tipping, no crowds, no congestion – just hop in, enjoy the ride, hop out, and be on your way. These cars will be electric: quiet, clean, and so safe that deaths and disabilities will be rare. Instead of dealing with road rage and the frustration of bumper-to-bumper traffic, you’ll be free to text, Facebook with friends, or get a head start on your workday. Since you can cut your cost in half by riding with another passenger, seamlessly arranged by your mobility provider, traffic congestion will slowly fade away.
Owning a car means car payments, insurance, registration, maintenance, gas prices, smog, tickets, accidents, finding parking, and dealing with the stress of traffic. Buying miles instead of metal means you’ll save thousands a year for your dream vacation, the kids’ college education, or buying a home of your own. In addition to lowering stress and regaining the use of 5% of your waking hours, putting an extra $5,000 a year in people’s pockets will compel this change.
Driverless Car Revolution explains the benefits for people of all ages, from kids through seniors, plus the disabled, the working poor, tourists and other special groups. The book also discusses the economic disruption of major industries as well as potential geopolitical upheavals – all the pieces of the puzzle, and how they fit together.
Fasten your seatbelt, engage, and prepare to join the Driverless Car Revolution.

Get it via Amazon.com

This graphic shows the future of the auto industry

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It may have taken professional auto industry analysts some time to understand the impact of autonomous vehicles. But now Morgan Stanley’s Adam Jonas has come up with another ingenious 2-by-2 chart so much en vogue with international strategy consultants which highlights the core transformative forces at work. This is a major intellectual feat because it compresses the problem space and helps reason about changes, challenges and opportunities associated with self-driving cars. The chart is shown below. Because I don’t have access to the original Morgan Stanley report the following explanations may not exactly reflect Morgan Stanley’s reasoning.

End-of-the-auto-industry

Quadrant (1) shows the auto industry today which is exposed to to major forces of change: The sharing economy leads to the emergence of companies which provide mobility as a service. Uber, Car2Go, DriveNow, Lyft and others are examples for this trend. In parallel, the auto industry faces the trend toward autonomous driving. Several companies, including Daimler, Nissan, and others are working on models targeted toward the consumer which can drive autonomously. The fourth quadrant shows the confluence of both trends: The shared autonomy. Autonomous pods such as the Google electric autonomous 2-seater, the Lutz Pathfinder currently being deployed in the UK and CityMobil2 autonomous buses fall into this category.

The future of the auto industry can be found in this fourth quadrant. Economic reasons clearly show that this quadrant will capture the lion’s share of individual motorized mobility. Neither of the other quadrants will be able provide individual mobility at competitive prices compared with the providers of autonomous mobility services of quadrant (4). Of course the other quadrants – particularly the 1st and third quadrant will not disappear entirely. There will still be some privately owned cars but they will represent a much smaller share of the mobility market than today.

Adam Jonas conclusions about the future of the auto industry are in line with the scenarios I have outlined over the past years in many articles – including five years ago in my first paper on this topic:  ‘Autonomous cars: The next revolution looms‘ .

Source: Morgan Stanley, Los Angeles Times

Autonomous long distance trains moving forward

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Being fixed to a track, trains are much better suited for autonomous operation than road-based vehicles. But  most of the innovation in autonomous vehicles is occurring on the road. Worldwide there are only very few efforts to develop autonomous trains (automated subways and metro lines are not autonomous – their cars are usually controlled by a central server and these lines require significant extensions of the track-side sensors and safety mechanisms which doesn’t scale for long distance rail networks). Fortunately some isolated efforts are now moving autonomous trains forward:

Global mining powerhouse Rio Tinto operates its own 1700km rail network in Australia to transport iron ire from its 15 mines to the sea ports. The company is spending more than 500 million USD to equip all its locomotives with radar, sensors and mapping technology for autonomous operation. The first trial runs have been completed successfully at the end of 2014 and up to 41 autonomous trains may begin operation in the second half of 2015! Is it a surprise that these autonomous trains are being developed by a commercial company that has its own extensive rail network rather than a traditional railway operator?

Although autonomous trains could significantly lower costs, increase capacity and flexibility, most railways are heavily regulated and are unlikely to adopt autonomous driving technology on long distance trains soon. This is unfortunate because the extreme focus on safety actually prevents useful innovations from being adopted and pushes people to other transportation mediums such as the road – with much higher risks and casualty levels.

Fortunately, the effort to develop a European Railway Traffic Managment System (ERTMS) has laid some groundwork which could be leveraged for autonomous operation: ERTMS distinguishes four levels of train control: Levels 0 to 2 rely on standard trackside infrastructure for train control – including signs and balises (transponders embedded in the track which digitally transmit location and track constraint information to the train ). But level 3 allows trains to localize themselves via sensor and retrieve track constrains and movement authority via mobile internet (GSM-Rail). This greatly increases flexibility and should simplify the introduction of autonomous railways on the many routes that are not yet equipped with automated train control infrastructure.

Netherlands first to operate a self-driving shuttle in public traffic?

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The competition for low-speed self-driving vehicles in public traffic is heating up. Now the executive council of Dutch ministers has given the green light for running two driverless shuttles in the Dutch city of Wageningen starting in December 2015. The electric shuttles will carry up to 8 persons from a train station to the university on a stretch of approximately 6km on public roads with a maximum speed of 50km/h. Although these will be tests, the shuttles will operate autonomously without safety drivers on board. The shuttles’ operations will be monitored remotely. Before the shuttles be placed in service both chambers of the Dutch parliament need to amend Dutch traffic law. If everything goes according to plan, the world’s first fully autonomous shuttles without backup driver on board could make history in the Netherlands in December!

© Ligier Group

Image: EZ-10 Autonomous Shuttle of Ligier Group, Easymile

Sources: de Gelderlander, carrepublic.nl

Accident rates of self-driving cars: A critique of the Sivak/Schoettle study

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To what degree are self-driving cars likely to reduce accidents and traffic deaths? This is a very important but very hard question which has implications for testing, insurance, regulations and governments considering to accelerate or delay the introduction of autonomous cars. Now two researchers, Michael Sivak and Brandon Schoettle, of the Transportation Research Institute at the University of Michigan have examined this problem in a short study titled “Road safety with self-driving vehicles: General limitations and road sharing with conventional vehicles“ and arrived at four conclusions which – when read carefully – provide little insight into the problem but when read casually seem to raise doubts about the expectation that self-driving cars will be significantly safer than human drivers.

As an example the abstract summarizes their second conclusion as follows: “It is not a foregone conclusion that a self-driving vehicle would ever perform more safely than an experienced, middle-aged driver”.

Who could argue against this statement? Of course, this is not a foregone conclusion. This is a hard problem and a substantial question. Neither would it be a a foregone conclusion that a self-driving vehicle would ever perform more safely than an experienced, young driver (or even an unexperienced young driver). But many readers will interpret this conclusion that the authors – after having analyzed the issue – have found substantial problems that raise doubts as to whether autonomous cars could ever perform better than experienced, middle-aged drivers. But the full text of the report contains just one sentence which further examines this problem:

“To the extent that not all predictive knowledge gained through experience could exhaustively be programmed into a computer (or even quantified), it is not clear a priory (italics by the original authors) whether computational speed, constant vigilance, and lack of distractability of self-driving vehicles would trump the predictive experience of middle-aged drivers”. (Page 4)

Nobody can argue with this statement. It would be a good introduction to a chapter that looks at this problem in more detail, provides some framework, examines the different aspects etc. etc. But this does not materialize.

If we read the study carefully, then we find a pattern that valid questions are being raised, a small number of the aspects relating to these questions are outlined, and then the questions are rephrased into conclusions which themselves are questions. This is unfortunate because the topic is extremely important. More than a million people die in traffic accidents every year. If – twenty years from now – we might look back from a situation where traffic accidents have fallen by more than a factor of five, then we will be able to state with certainty how many lives could have been saved if self-driving cars would have been introduced a few years earlier. We might find that tens of thousands of people have lost their lives because governments and regulators did not realize the risk of delaying a highly beneficial technology and business and innovators were reluctant to advance the technology because of a climate of mistrust and skepticism with respect to the technology. Of course, from the perspective of today this is not a foregone conclusion but we need to make an effort to understand the risks and likely accident patterns of autonomous vehicles much better.

There are lives at stake both if we are too optimistic and too pessimistic over the potential of this technology. But the problem is not symmetric: If we are too pessimistic with respect to the potential of this technology, then we can easily find ourselves in a situation in the future where we find in hindsight that thousands of lives have been lost because of this pessimism and the resulting delay of the introduction. On the other hand, if we are overly optimistic with regard to the technology, and accelerate innovation in this area, it is unlikely that thousands of lives will be lost because the cars do not perform as safely as expected. We can be confident that certification bodies will do their work and uncover problems before they can cause thousands of deaths and regulators will most surely step in immediately when these cars do not perform as expected. At the current stage therefore, pessimism about the technology’s potential may be much more deadly than optimism (which should not be confounded with being blind about the risks).

We should work together urgently to formulate a theory of human traffic accidents and self-driving car accidents which can help us shed light on the issue and understand and organize the many different aspects of this problem. This is hard but it can be done. Please contact me at info.2011 ( at ) inventivio ( dot ) com if you are already working on this topic, if you know of a suitable approach for covering this problem or if you are interested in working together on this topic. I will post one approach on how this could be achieved next week.

Changes:
2015-01-23: Added link to the full text of the study.