Volvo’s liability promise for autonomous mode may cut out insurance companies and independent repair shops

Volvo has recently stated that they will accept full liability for accidents that happen while the car drives in fully autonomous mode. This takes the heat away from the discussion about liability issues for self-driving cars. But it also has side effects that strengthen the business model of the auto maker: By accepting full liability the auto maker in effect shoulders the liability not only for all defects of the software (which no auto maker can evade anyhow) but also for all other accidents that may occur in autonomous mode. Some accidents can not be prevented: Obstacles may suddenly appear on the way (animals, pedestrians, other objects) and make an accident unavoidable. Defects of the roadway, certain weather conditions, and certain questionable behaviors of other traffic participants may lead to accidents that even the best software can not prevent.

Therefore the acceptance of full liability contains both a promise regarding the quality of the software and an insurance element: Volvo must either add the total, non-zero, lifetime risk of driving in autonomous mode to the purchase price of their self-driving cars. This could have the disadvantage of making their cars more expensive. Or they could duplicate the insurance industry’s business model and request that their customers subscribe to a (low) supplementary insurance policy. The latter has the advantage that risk profiles – total number of miles driven per year and the area where the cars are driven (urban, country, highway) can be taken into account. But the insurance industry would surely mobilize against the latter approach and decry it as anti-competitive.

In the following we therefore examine the first case where Volvo decides to include the cost of insurance as a hidden element in the purchase price in more detail: It is hard to provide a good estimate of the risks but there are some numbers we can build from: In 2012 US insurance expenditures for a car had an average value of $815 per year. If we take this as a proxy for the risk of human driving, then factoring in the risk of human driving for a 12 year life expectancy of a car would increase the purchase price by $9780. How much lower will the risk of autonomous mode driving be? A representative study of more than 5000 severe accidents in the United States published by the NHTSA which was carried out between 2005 and 2007 provides some clues: The study found that human errors were the most critical factor in more than 93% of the accidents. In less severe accidents human error probably plays an even bigger, but certainly not smaller role. Other factors were: Technical failures: 2.0%, road conditions: 1.8%, atmospheric conditions (including glare): 0.6%. If we assume that autonomous vehicles do not add significant additional modes of error, then they should be able to reduce the number of accidents by at least a factor of 10 ( 1/(1-0.93) = 14.2). Because the vehicles drive more defensively, break earlier in critical situations, are much more consistent in their behavior in critical situations than humans (some of whom will not react at all in a critical situation, not even step on the brakes) the average damage per accident is likely to be significantly smaller than the average current damage. Therefore the costs of vehicle accidents are likely to fall even further; we estimate that autonomous vehicles have the potential of reducing accident costs by a factor between 15 and 50. This assumes that autonomous vehicles do not create major additional risks and don’t somehow cause rare but unusually enormous accidents. Under these assumptions, Volvo’s liability promise can be added into the purchase price: If we assume a reduction of damages by a factor of 15, the life-span risk (12 years) translates into 652$ of additional costs for each fully autonomous car which Volvo sells.

Accepting full liability for all accidents in autonomous mode may therefore indeed be a viable strategy for Volvo and other makers of fully autonomous vehicles. This move cuts out the insurance industry and – if copied by other auto makers – should not be a competitive disadvantage, because the risks are unlikely to differ greatly from auto maker to auto maker. In addition, auto makers might use this approach to open additional revenue streams for more risky use of vehicles where they might request additional fees – for example for heavily used fleet vehicles.

There is another side-effect of assuming liability for accidents in autonomous mode. Accidents are more likely if the cars are not maintained properly. Therefore auto makers may place more stringent requirements on maintenance, shorten maintenance intervals and require that the cars be maintained in certified repair shops only – which eliminates the business of independent repair shops. By increasing maintenance revenues, auto makers may be able to offset the costs of assuming liability for accidents.

In summary, Volvo’s shrewd move to assume liability may extend their revenue streams while cutting out insurance companies and independent repair shops.

US Secretary of Transportation: driverless cars all over the world by 2025

Anthony Foxx, Secretary of Transportation visited the Frankfurt Auto Show together with his colleagues from the G7 and German Chancellor Merkel. In an interview with German newspaper Frankfurter Allgemeine Zeitung, he stated that he is very optimistic with respect to driverless cars and expects to see them in use everywhere in the world within 10 years. He wants to accelerate the process for the introduction of new technologies such as self-driving cars and avoid the current legislative delays of five or six years. Of, course safety must always be assured.

The Frankfurt Auto Show clearly demonstrates how much more seriously politicians and the auto industry are taking autonomous car technology and the changes that they will bring.

Source: Frankfurter Allgemeine Zeitung, 2015-09-19

Chinese company unveils prototype of self-driving bus

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. 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).


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

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

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

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

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

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

This graphic shows the future of the auto industry

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.


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

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.