Singapore to start autonomous vehicle testing on public roads in 2015

Singapore clearly realizes the potential of autonomous vehicles for revolutionizing road transport. They already have several projects in place – including autonomous golf carts and a Navia shuttle. Now they have set up an oversight committee on Autonomous Road Transport which will support guidance on the research and implementation of self-driving cars. Besides government officials the board includes representatives from MIT, Nissan, Toyota and Continental.

Singapore wants to understand, shape and apply the technology to improve the road infrastructure. It envisions a greener future where a much smaller pool of cars provides urban mobility. In a first step, Singapore will allow testing driverless vehicles on select public roads of its one-north business district starting January of 2015. Of course, stringent safety measures must be in place. Another application of the technology for testing could be driverless buses that operate on fixed routes.
Singapore is the first city that systematically works towards a future with driverless cars. It recognizes that it needs to incorporate driverless technology into its long-term infrastructure plans already today. In addition, becoming a pioneer of this technology could lead to important competitive advantages for this city-state in the future.

Sources: Channel Asia 1,2

Proceedings of the Automated Vehicles Symposium available online

This year’s Automated Vehicles Symposium took place in San Francisco in mid-July. Most presentations are available in PDF format with some notable exceptions (both presentations by Google and one by Daimler are not available). The presentations provide a wide range of insights into thoughts of the auto industry and policy makers. I recommend the presentations from Bosch (Tue), Department of Energy (Thur) and theCalifornia Department of Motor Vehicles (Thur).

Many presentations reported statistical insights about attitudes toward autonomous vehicles, autonomous driving etc. Unfortunately, such data is not reliable to any degree because the attitudes are likely to change significantly as the technology matures and awareness about the technology increases.

Level 3 automation was still a major topic. But a quick poll among the participants seemed to indicate that the majority of participants now believe that full autonomy (level 4) is the way to go.

Google’s self-driving cars: Implications for the auto industry and the key role of machine perception

Google’s self driving car effort is a threat to the auto industry. The company is the clear leader in autonomous vehicle technology and several years ahead of all other auto makers, including Daimler and Volvo. By presenting an all-electric prototype of a fully autonomous two-seater in May, Google has also made clear that it is serious to become a player in individual mobility and intent on reaping the rewards of its investment in this project (which so far has likely cost a few hundred million Dollars – not an enormous amount by the standards of the auto industry for developing a new car model).

What are the implications for the auto industry? They have much more experience in all aspects of mobility and are also working on autonomous vehicles. Could Google really be a signficant threat?

The standard answer to this question has been denial: Last year the main argument was something like: They may be able to build great software but they don’t know how to design a car. Now that they have designed a steer-by-wire two-seater with redundant layout of all safety-critical components and skillfully navigated the regulations – including limiting the speed to 25mph – , the argument is updated: They may be able to build a slow-moving two seater, but they can’t build a real car. And even if they could, they could not produce it in any meaningful volume.

As they overcome each objection, denial becomes harder, and additional time is lost. The argument that Google would not be able ramp up production is misguided. Google has no intention to challenge the auto makers on their playing field. It will change the game by providing autonomous mobility services rather than selling cars. Each Google autonomous car will then reduce the demand for privately owned cars by a factor of 5 to 10. This will have an impact on auto makers. It will affect their strategies, stock prices and make production capacity much easier to acquire.

Instead of denial, auto makers need to understand the magnitude of the threat. Self-driving cars will be a disruptive force; they will change the business model of the auto industry and bring hard times to most auto makers because demand for passenger cars will fall significantly. From a global perspective this is a good thing because resources will be used much more efficiently, alternative propellants can be used much more readily within autonomous mobility services and the strain on the environment (both pollution and land-use) will fall.

But it will be hard for the auto industry to adapt to these changes. Cars have been produced for more than a century. The requisite knowledge is widely available. The same does not apply to a key ingredient for self-driving cars: Teaching a machine to perceive its environment. Perception is the core problem which determines the success of a self-driving car.

Perception is a multi-faceted problem. It has to do with sensors, with prior knowledge, machine learning and is sensitive to action and context. Unfortunately, perception is not limited to the context of driving. Self-driving cars need to understand the behavior of people and things that may be relevant to the driving context – even if their behavior has nothing to do with driving a car (e.g. kicking a ball).

Because perception is hard, it requires considerable financial and human resources to solve the problem. Google has not only the financial resources but has recruited many leading experts in this field. Even the leading auto makers would find it hard to build teams that match Google’s expertise. Joining forces with other auto makers may be the only viable strategy.

Because perception is a general capability, it is applicable to many fields beyond driving and consequently it can generate returns in many fields besides driving. This is an advantage for Google because it allows cross-fertilization with its other business areas. Google has recently bought several leading robotics companies. Advances in perception by the self-driving car group could also benefit these business areas and vice versa. Google has also started a mobile phone project (Tango) which aims to use a high end Android mobile phone to create 3D maps of the environment in real time. Advances in this space may also be useful for the self-driving car project.

As a consequence, auto manufacturers who want to beat Google to a fully autonomous car, will need to carefully consider the additional opportunities which advanced perception could bring and determine how to integrate these opportunities into their strategy. Instead of narrowing the perception task to specific driving scenarios, auto makers should consider whether they could leverage their perception activities in additional ways.

Machine perception is the core competence for succeeding with autonomous cars. Auto makers need to give this capability top priority if they want to recover the ground already lost to Google.

Google’s electric self-driving two seaters: A milestone towards autonomous mobility services

With the unveiling of their new electric-mini cars Google’s self driving car strategy is becoming more and more evident. By the standards of the auto industry, these cars have many obvious drawbacks: they are very small, can only seat two persons, speed is limited to 25mph, range is also quite limited, the big sensor on top is seen by some (including Daimler’s CEO Zetsche) as an eyesore. They will be hard to sell.

But this is not the point. Google has set their sight on reinventing mobility, not just on building a self-driving car. These cars no longer need to be tethered to a person; they can roam freely and provide shared mobility services to anyone at prices that are significantly lower than individually-owned cars. This is the picture, that Google’s project leader Chris Urmson has in mind when he envisions cities without parking lots (no more need to park these cars, they can transport others in the mean time).

Google’s investment in Uber, their clear focus on fully autonomous driving are all parts of the same picture. It will be very hard for the auto industry to compete on this field because it means cannibalizing their own products, completely transforming their purchase-oriented business model which has served them well for more than a century towards a service-oriented model and fundamentally rethinking the concept of a car.

Google won’t need to sell these cars. They will organize mobility. They already excel at mapping and travel planning, but in the future they will send a car to pick you up wherever you are and bring you where you want to go. They will predict, balance and aggregate mobility demand. Billions are spent for individual mobility. Google should be able to grab a significant share of this market once their mobility-on-demand services are ready.

Decisions on the path to future mobility – Research Forum

The 6th research forum on mobility took place on May 8 in Duisburg, Germany. With a good mix of presentations from academia and industry, a wide array of topics was covered. Electric mobility was regarded with much more enthusiasm as many speakers saw battery prices coming down faster than anticipated by most think tanks.

Futurist Lars Thomsen discussed many tipping points for the auto industry; he expects autonomous cars to perform better than the average driver by 2017 and also noted that fleets of autonomous pods will become the dominant medium for transport in mega cities, where most people will no longer own a car. At the same time he did not connect the dots and consider the impact on the demand side and the implications for OEMs.

This fit well with the topic of my presentation which focused on fleets of self-driving taxis. I presented detailed cost calculations for a fleet of urban autonomous vehicles. The data shows that driverless mobility services could halve the costs per person-kilometer compared to car-ownership. One of the key sources of savings is professional life-cycle management for all vehicle components which will greatly increase the economic life of the cars and thereby decrease the capital cost per kilometer traveled.

 

Convoys of self-driving trucks for the military

Since 2012 Lockheed Martin has been working on an autonomous driving kit for military trucks. An early but already quite impressive version has been demonstrated in January at Fort Hood, Texas. The ‘Automous Mobility Applique System’ can be quickly fitted to most tactical vehicles. It contains sensors – including a rotating 3D LIDAR and actuators to control the various car components. At the demonstration, several autonomous trucks drove in convoy mode, negotiated obstacles and had to dynamically re-plan their route.The system seems to be capable of negotiating some traffic including pedestrians and bicyclists.

Although the demonstration was impressive, there was no word on when the technology would be available in the field. Another demonstration is scheduled for later this year. The demonstration clearly shows that military is determined to make use of this technology and that military applications may not lag far behind the civilian.

 

Source: Lockheed Martin

Autonomous cars: Breakthrough for electric vehicles

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Rethinking mobility

Sometimes the breakthrough for a new technology does not materialize in one of those fields which receive most attention and where everybody expects the solution. When the British needed a practical method for determining a ship’s longitude in the 18th century, they spent many decades gazing at the stars, compiling lunar tables and searching for astronomic methods for determining longitude. But the breakthrough came with an entirely different technology: an extremely precise clock! Longitude could now be determined quickly and easily by comparing the clock’s Greenwich time with local time (which can be calculated by tracking the rise of sun).

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Today, electric mobility is in a similar situation: Billions of dollars have been invested in improving the usual components for electric vehicles: Battery technology – already quite advanced – is being perfected; charging infrastructures are being deployed; production processes are optimized and many of the legal and financial obstacles have been removed. Nevertheless, a real breakthrough is not in sight. As armies of engineers work on these problems, a much smaller group works on another technology which at first glance is not related to e-mobility: They develop autonomous vehicles that can drive themselves on regular roads and don’t require human input or modifications to the road infrastructure.
Only a deeper analysis shows how important fully autonomous vehicles will be for e-mobility: This technology changes fundamental aspects of mobility and enables alternative mobility scenarios which are more compatible with electric vehicles and where the biggest disadvantage of electric vehicles – their limited range – are much less of a concern. Range matters only in the current configuration of individual mobility which is based on individually-owned cars. If mobility is provided by fleets of driverless cars, then range limitations are no longer a problem because urban trips have an average trip length of less than 10km. They are much shorter than the range limits of current electric vehicles. Thus e-mobility may not need a breakthrough in vehicle range at all. It is sufficient to find new ways for reducing the range requirements for the vehicles!

Electric vehicles become competitive

Currently self-owned or leased cars are the cornerstone of individual mobility. Only a very small (even if growing) share relies on car-sharing and rental cars. These alternative mobility solutions currently have a big disadvantage: Every customer faces the problem of getting to the next available car and where it should be dropped off at the end of the journey. Once cars are capable of driving without any human intervention, however, this problem vanishes. Anybody will be able to request an autonomous vehicle by phone or mobile app. Within minutes a car will arrive to pick up the passenger and drop him off at the destination, where the car will then be ready to service the next customers.

Thus autonomous vehicles will initially provide the conditions for a breakthrough of car-sharing systems and autonomous mobility service providers. Compared to self-owned cars, they can provide individual mobility with a comparable level of service and comfort, and – because of better utilization and fleet optimization (see further below) – at significantly lower cost. In densely populated areas autonomous cars will therefore ensure that car-sharing systems greatly increase their share of individual motorized traffic.

This establishes the conditions for the breakthrough of electric vehicles. As part of fleets of autonomous vehicles, the advantages of electric vehicles can now be brought to bear: more robust and longer lasting motors, lower drive train complexity, lower service costs and lower emissions. Their shorter range is no longer a problem because fleet operators can dispatch vehicles that precisely match the mobility demands of their customers (local vs long-distance trips, number of passengers, baggage size etc.). As the vast majority of trips are local and short-range, most trips can be serviced with electric vehicles. A smaller number of fossil fuel vehicles can be used for long-distance trips. Thus fleets are likely to consist mostly of small electric two-seaters; only a smaller part will consist of larger vehicles or rely on fossil fuels. This potential for demand-based fleet optimization is a novelty that is only possible when cars can drive themselves to the customer. In this way total costs and resource consumption related to mobility can be reduced significantly.

Of course, fleets of autonomous cars do not have to use electric vehicles. However, there are three good reasons besides those already discussed above, why electric vehicles are particularly well suited for the first fleets of autonomous vehicles:
1) The first fleets with fully autonomous vehicles will appear in niche areas where it is easiest to control risk. Their speed and range will initially be quite low. At first, they may even travel partially on their own lanes and only later will increase their capabilities. An example is the project in Milton Keynes where 100 autonomous electric vehicles will be installed between 2015 and 2017 to ferry people between train station and city center. The requirements for these vehicles with respect to range, maximum speed, number of seats etc. differ markedly from the requirements for traditional cars. Current car models therefore do not constitute a good match for the first autonomous car fleets – even if they had been adapted for fully autonomous operation. At the same time, car manufactures are probably not eager to develop specialized low-volume models for use in early autonomous car fleets.
2) Current car models of the auto industry are not suitable for fully autonomous operation – even those with advanced driver assistance systems. They must be modified for pure fly-by-wire operation. All safety-critical components and systems have to be redundant. The modifications used in current prototypes and test vehicles are not suitable for productive use. It it is not at all trivial to adapt current car models for fully autonomous operation. Therefore the auto industry needs to develop a new vehicle platform from the ground up for fully autonomous operation. This could be a complex and time-consuming effort which will take longer than many fleet operators will be prepared to wait for.
3) The design and production of a small number of fully autonomous electric vehicles for local transport as part of fully autonomous fleets is much faster and easier than the design and production of classical cars adapted to the needs of fully autonomous mobility service providers. The complexity of electric vehicles is lower; relying on electric propulsion simplifies the redundant layout of all safety critical components. As an example, an electric motor has inherent safety benefits: It can be used for braking; if the motors are integrated into the wheels they could even play a role in emergency steering.

Whereas currently the lack of a national charging infrastructure for electric vehicles is often cited as a major problem, this problem also goes away when fleets of driverless urban cars are used. Because these vehicles are only used in local traffic in a specific region, it is sufficient to deploy the charging infrastructure for exactly that region and the actual number of electric vehicles and actual mobility demand. The infrastructure can then grow in synch with the fleet; it is no longer necessary to build up large infrastructures long before the first electric vehicles are placed into operation.

Economic pressures accelerate the transformation

Some innovations trigger intensive economic and societal changes which can advance with astonishing speed if they significantly change the cost structure and efficiency of processes. The power loom and the railroads are only two examples that highlight the potential dynamics.

Market forces work especially well, when they are brought to bear on inefficiently used capital-intensive resources. Such inefficiencies are very pronounced in transportation: Cars are among the largest single investments of private households; but their average utilization rarely exceed 6% – an incredible waste of capital. Therefore the potential for savings is enormous. The average US households spends more than 16% of its total expenses on car-based transportation.

A study of the Earth Sciences Institute at Columbia University has analyzed the savings potentials associated with fleets of self-driving cars in detail. They performed a simulation study based on the mobility patterns of Ann Arbor, a medium size city in Michigan which had about 285,000 inhabitants and 200,000 cars in 2009. 120,000 of these cars were used primarily for local traffic. Each day, 528,000 local trips occur in Ann Arbor with an average trip length of 9.3km and about 1.4 passengers per vehicle. The authors found that a fleet of 18,000 autonomous vehicles would be sufficient to satisfy the local mobility demand in Ann Arbor and ensure that no passenger would have to wait more than 60 seconds for their car – even during rush hours. This translates into a reduction in the number of cars by almost a factor of 7! Whereas a privately owned car with a range of 16,000km per year leads to costs of 0.46$/km, the fleet of driverless cars would reduce the costs per passenger-km to 0.25$. The study also examined the use of light electric vehicles instead of mid-size sedans which are typical used for car rentals. With electric vehicles, the costs would fall even further to 0,09$ per passenger-km. This is a cost reduction by a factor of five!

Although the study has not included all potential savings (not included were savings related to parking, congestion, aggregation of mobility demand, freed-up time) it clearly shows that this innovation has very high savings potential and can lead to a large increase in spending power for the individual. Even if not all consumers act rationally at all times, these calculations imply that a large number of households will choose autonomous mobility services instead of buying their own car in the future (we subsume the special case where a household purchases their own autonomous car but then rents it out to others as another variation of the fleet model). Only a smaller number of households will value the prestige of their own car or their love towards a car high enough to continue owning a car.

Another factor which will accelerate the growth of fully autonomous mobility providers is that even households which own a car will become customers of autonomous mobility services because they need their services in some situations: when a member of the family needs to be picked up somewhere, when multiple members of the household need to drive to different locations but the household does not have as many cars, when flying to other cities, etc. More and more people will then find that they can get around quite well without their own car. The number of situations in life where owning a car is almost a necessity will dwindle. Today there are many people for whom their own car is the only realistic way for getting to work. Fleets of driverless cars will greatly reduce such cases and therefore reduced the perceived need to purchase a car.

Paths towards new mobility

The transformation of mobility caused by fully autonomous cars will require some time. Despite the large advances of the last 30 years and the impressive prototypes which have been demonstrated by car manufactures (Daimler, Audi, Nissan), research institutes, Google and others, significant hurdles remain until fully autonomous cars will be able to drive on all roads without human intervention.

Currently there are two different visions of the path towards full autonomy. The conventional vision  assumes that autonomous technology will gradually evolve towards more and more advanced driver assistance systems until finally reaching full autonomy. It uses the typical diffusion process of automotive innovations (such as airbag and anti-lock braking) as a reference and assumes that the technology will slowly trickle down from the premium models to the middle-class models until it becomes standard for all new cars. However, there are significant hurdles Рincluding regulatory problems Рon this path. Several generations of models with ever more advanced driver assistance systems, with complete fly-by-wire and redundant layout of all safety-critical systems will be needed until models with full autonomy will appear on the market. If we follow this line of reasoning, then it may be well after 2030 that such cars are available in larger numbers and a decade or two more until fully autonomous technology is available in most cars. In addition, electric vehicles do not feature on this path, because it is based on personally-owned vehicles where range limitations of electric vehicles will continue to be a major problem.

However, there is a second path toward full autonomy which does not adhere to the standard car industry model of technology diffusion. Instead of trying to gradually integrate the technology into consumer cars, this path seeks to capitalize on the inherent advantages of full autonomy and targets those niches where full autonomy has the largest impact and can be implemented with a minimum of risk. We have seen above that full autonomy can greatly reduce mobility costs by providing mobility as a service using fleets of self-driving cars. A natural path towards full autonomy therefore starts with small, short range and most likely electric vehicles that provide local mobility at low speeds and in increasingly less controlled environments. The challenge for the pioneers is to find those settings which are best suited for limited, low speed operations of autonomous vehicles and which provide the best environment for their growth.

There is no shortage in candidates. Several systems with very low autonomy are already in operation: The ‘UltraPods’ at Heathrow Airport are electric autonomous four-seaters which ferry passengers between Terminal 5 and a parking lot. They run on separate lanes and use transponder chips embedded every few meters in the lanes for determining their position accurately. They also rely on internal lane maps for navigation. A similar approach has been adopted in the Netherlands where 6 autonomous electric buses carry people along a stretch of about 2km. A next step for such systems is to leave the confines of separate lanes at least in some cases and merge with regular traffic. Such an approach is planned for Milton Keynes, a British city, where 100 electric autonomous vehicles will be installed between 2015 and 2017 to transport people between the train station and the city center at low speed. Initially these vehicles will run on dedicated lanes (taken from current sidewalks); by 2017 they will expand their range and will be able to share lanes with pedestrians (there are currently no plans to put these cars onto the streets). This project has the advantage of minimizing risk while at the same time advancing the envelope of autonomous vehicles: algorithms will be perfected; approaches for the operational management of distributed fleets of self-driving vehicles will be developed; customer experience, preferences and service valuation will be understood better, a vehicular platform and technology architecture will be developed.

There are many areas where autonomous electric vehicles with even this limited capability are useful and can become economically viable very quickly. Similar approaches can be implemented in many cities where electric cars or buses may be installed for specific routes. Initially some infrastructure measures (such as separate lanes, fences which keep pedestrians away from the street, external sensors at critical locations) may be adopted; as experience and intelligence of the vehicle increases, these infrastructure measures can become obsolete.

Another variant of this approach would be if car makers or Google decided to implement their autonomous technology in a fleet of electric city vehicles that would operate on carefully selected routes in a suitable city. There are many ways in which this could unfold but there is no shortage of possible approaches for starting on a growth path for such fleets of autonomous electric vehicles. As the Milton Keynes Project shows, this is possible even with limited budgets.

Another advantage of this second path is a legal issue: A fleet of self-driving cars can be regarded as an intelligent transport system where the vehicles run on exactly specified paths. For such systems the legal limitations of the Vienna Convention on traffic which requires that every vehicle must be controlled by a driver at all times do not apply. This eliminates key legal problems which probably exist in countries which have ratified the convention (not ratified by: US, UK, Spain, China, Singapore and others). Even if the question has not been finally clarified, it is clear that countries have a considerable margin of interpretation which allows the implementation of fleets of driverless vehicles already today.

Overall, this alternative path to autonomous technology based on fleets of electric vehicles used for niche applications in controlled settings for urban local mobility is much more realistic and faster to implement than the vision of a universal fully autonomous car which can be used on all roads by anybody.

Conclusion

We are at the start of a development which could very quickly become an avalanche. Two years ago autonomous vehicles were widely regarded as utopian; by now it is clear that it is just a question of a few years until these vehicles appear on our roads. Right now, the view is still predominant that autonomous technology will do little to change the nature of cars and the nature of mobility. But a closer look reveals that the technology will lead to fundamental transformation from individually owned cars to mobility as a service and from mostly fossil fuels to electric vehicles. These fundamental changes hold many opportunities. Now is the time to take them…

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United Kingdom prepares to play leading role in driverless car revolution

The country which started the industrial revolution and the first revolution in mobility is determined not to sit on the sidelines as the next mobility revolution unfolds. The UK government wants to accelerate the adoption of autonomous vehicle technology and ensure that the UK plays a prominent role by establishing a UK city or region as a test and demonstration site for self-driving cars.

To start this process, it convened about 100 people in London in Mid-February to discuss the criteria for site selection. The city/region will be funded with 10 Mio Pounds. The very efficiently managed workshop rapidly generated insights about success criteria for such sites.

There seemed to be much consensus that fully autonomous vehicles hold the most promise; they will provide completely new opportunities in mobility services, applications and business models. There was some disagreement as to the state of autonomous technology. While some argued that the technology is basically there, others voiced concerns that significant challenges still remain. Disagreement was also visible with respect to standardization and interoperability. While some argued that the vehicles should be standardized and easily transferred to new locations, others argued that imposing such requirements would be too early and would accomplish little.

A representative from Google stressed the importance of speed in the implementation – a comment that reflected a sense of urgency which most participants seemed to share: There is only a short window of opportunity to gain a leadership position in this rapidly moving field.

Within Europe, the United Kingdom has some unique advantages for the early implementation of self-driving cars: It is not bound by the stipulations of the Vienna Convention on Traffic that every car must be controlled by a driver at all times. Unlike most European Countries (except Spain) it has never ratified the convention. In addition, its car industry is not as dominant as in many other countries (the UK is on position 17 of the 40 nations listed by the Organization of Motorvehicle Manufacturers (OICA) with respect to the number of employees in the car industry as percentage of the whole workforce; In contrast, Sweden, the Czech Republic, Germany and Spain are among the top five. This also means that the UK has less to fear from the disruption of the auto industry which fully autonomous vehicles might cause. At the same time, the UK has an excellent industry and research base, top universities including Prof. Newmanns Oxford Mobile Robotics Group, and already has a head start with more traditional electric driverless pods operating at Heathrow.

Given that another project is already under way to implement 100 self-driving pods in Milton-Keynes between 2015 and 2017(funded at much higher rates), the UK might indeed achieve a critical mass to become a key player in this autonomous vehicle revolution.

RAND report on autonomous vehicles

As policy makers are waking up to the potential and issues related autonomous vehicle technology, the US think tank RAND Corporation has released a comprehensive report which analyzes driverless car technology from a policy perspective. The report looks at costs and benefits, the state of the technology, current legislation, liability and concludes with recommendations for policy makers.

Rand-Study

The report wavers between more incremental, functional perspectives (where autonomous technology is seen as an incremental improvement of current cars with little change to patterns of car use and ownership) and transformational perspectives (transformation of mobility, fully autonomous vehicles, fleets of driverless taxis). On one hand, the authors point out that the technology may enable developing countries to¬† “leapfrog autonomous vehicle technology” and “skip some aspects of conventional, human-driver centered travel infrastructure”. They point out that much urban space may be freed up because much fewer parking space is needed when fleets of self-driving cars provide mobility services (which actually may increase the density of urban centers) and argue that the declining costs of mobility may increase the number of vehicles miles traveled.

On the other hand, they warn that the adoption of self-driving car technology could be hindered because the individual car owner does not profit sufficiently from the reduction in external costs of the technology (an argument that seems quite far-fetched) and fail to point out the obvious incompatibility of new regulations that would impose the “Irrebuttable presumption of driver control of vehicle” with fully autonomous mobility services. While the report warns about job losses in the transportation industry, they neither mention the risks for the auto industry nor their potential lack of incentives for deploying fully autonomous vehicles.

In the same vein, the sections on liability are mostly focused on the various alternatives of assigning liability to either the driver or the automotive manufacturer. The car’s owner and entity responsible for maintenance is not seen as another alternative. Neither are the additional concerns addressed that may arise when autonomous fleets are operated by mobility service providers.

The study is an excellent read and brings together many important aspects of autonomous vehicles. For those interested in the legal issues it also contains a good discussion of the theories of liability which are relevant in the United States. As their final conclusion, the authors recommend that policy makers let the technology evolve and abstain from premature regulation.