Transformations 2025: How Volkswagen prepares for the (driverless?) future

Echoing a growing sentiment in the auto industry, Volkswagen’s CEO Matthias Mueller warned last week of “a rapid and hard transformation” coming to the auto industry. He presented Volkswagen’s strategy “Transform 2025+” to cope with these changes. It includes major job cuts to prepare for the transition and many new initiatives.

But his strategy also shows how difficult it is to change the direction of the tanker which all major auto makers have become. Experience accumulated in the last 100 years, shared convictions and values make it difficult to adjust the focus and prepare for fundamental changes coming the industry. Many trends are currently competing for attention: electrification, mobility services, connected vehicles, digital platforms and finally the shift towards autonomous vehicles. It does not come as a surprise, that Volkswagen wants to become a leader in most of these topics:

It plans to establish an additional (thirteenth) major brand around mobility services. It wants to become a leader in electric vehicles. It has just established a digital lab to develop cutting-edge digital services related to mobility, connectivity, its brands and its products.

But the strategy fails to consider the tectonic shift which may be caused by autonomous vehicles and the way that self-driving car technology will affect the key aspects of the auto business. Mueller plans to lay the foundation for autonomous driving in the years from 2020 to 2025 and then have the necessary business models in place around self-driving cars after 2025. Given the rapid progress of the field, he may not have that much time.

But more importantly, self-driving car technology is associated with a very specific danger (and opportunity): It changes the dynamics of each of the auto industry’s strategic topics. Mobility services based on self-driving car fleets differ fundamentally from Uber’s, Car2Go’s and other mobility services fleets on parameters such as total cost per mile, optimal car model and characteristics, volume, utilization, profitability,  etc. Similarly electrification differs greatly whether it is targeted towards autonomous vehicles (which will initially predominantly be rolled out as elements of urban self-driving car fleets) or towards the consumer. The economic justification, battery cost, vehicle range, charging infrastructure requirements, innovation diffusion path and cost-effectiveness differ fundamentally!

A little bit of everything is not the right approach. Volkswagen, like most other auto makers, suffers from the problem hat it tries to address each and every strategic topic on its own without considering the relationships and interdependence with a paradigm-changing technology. Then, when autonomous vehicle technology enters the market they will find that the original assumptions no longer hold and that very little time remains to catch up and refocus the many different aspects of their business.

It is good that the auto industry is increasing their efforts to think about a radically different future. But they extrapolate forward from today to the next 5, 10, 15 years, and their thinking remains mostly rooted in the classic automobile world with a focus on volume leadership, consumer cars as primary product, traditional branding approaches, etc. However, in the face of transformational change, a different mode of analysis is needed: First the more distant future needs to be conceptualized, a future where autonomous vehicle technology has already matured, the current doubts and questions about viability, legality and acceptance have been overcome, self-driving vehicles are in the market and where laws and regulations have been updated (as we know they will) to allow productive use of the technology. The key aspects of this future need to be considered: Mobility service markets (separately for urban and non-urban regions, for local and long distance traffic), consumer segmentation and purchase decisions, impact on road infrastructure, impact on traffic flow (which will be enormous both for urban and for long-distance roads) and fleet management algorithms, truck, bus and autonomous machine markets. For such a future key changes (including the various types of mobility service business models) need to be calculated through in detail, using quantitative models. This analysis must be unencumbered by the current “realities” of the auto market. It must include the scenarios, business models and market dynamics that may entice investors to pour funds into promising opportunities.

After such an analysis, the focus can be turned back from the future to the present and the transition period. Many likely changes will become obvious and the paths and the relationships between the different technologies being considered today will be much clearer. For Volkswagen and all other auto makers it means allocating major resources to autonomous vehicle technology today: make sure that they catch up with the leaders in the space; prepare mobility services for  the autonomous fleet scenario rather than as also-run next to all the players already established in this field and make sure that they have electric vehicle models that can be used as backbone of self-driving car fleets.  Develop, consider and prioritize business models beyond consumer cars and fleet vehicles/mobility services, for trucks, buses, autonomous machines and beyond. Each of these activities is future-proof and establishes a beachhead  in the transition towards autonomous vehicles.

This is not a call to put all eggs into one basket. But auto makers need to take the fundamental changes that will be caused by self-driving car technology seriously and prepare to adapt to these new challenges today by making them a cornerstone of their strategy.

The race for fully self-driving cars has reached a pivotal point

Several events from the last months provide a strong signal that autonomous vehicle technology has led the auto industry to a pivotal point: The first auto makers are adapting their business model for fully self-driving cars and are providing explicit time frames!

Earlier this year GM invested 500 million USD in Lyft, purchased self-driving technology startup Cruise Automation for more than 1 billion USD and announced in July that GM will build its first self-driving cars for use within the Lyft fleet as self-driving taxi. In May BMW announced that they would have a self-driving car on the market within 5 years. Next came Uber, which acquired autonomous truck startup Otto for 680 Million USD and is now beginning field trials of fully self-driving taxis in Pittsburgh. But the key change at Uber is the way that its CEO Kalanick frames the issue. He makes it clear that Uber’s survival depends on being first (or tied for first) in rolling out a self-driving taxi network.

The latest announcement comes from Ford which plans to provide mobility services with fully autonomous self-driving Fords by 2021. This is a major effort: Ford is doubling its development staff in Silicon Valley, aims to have the largest fleet of self-driving car prototypes by the end of this year and will triple the size of this fleet again next year. It has also purchased 3 companies related to autonomous driving technology and has purchased a stake in Velodyne, the leading manufacturer of LIDARs for autonomous driving.

When we started to monitor the development of self-driving car technology in 2009 we expected that this technology would turn into an avalanche that sweeps through the auto industry. There have been many signs over the past years that the avalanche is picking up speed but until now we have been reluctant to claim that it is in full swing because even though the auto industry was continually increasing their activity around self-driving car technology all players had been very reluctant to openly call this a race and to publicly position fully self-driving cars as a key element of their strategy. There was a lot of posturing, many eye-catching public demonstrations of self-driving car prototypes but very little tangible action aimed at turning fully self-driving car prototypes into a real product.

After these recent signals, this situation has changed. It is now clear that auto makers have begun competing in earnest to adapt their business models to the coming wave of fully self-driving cars. No longer is Google the only company which is stepping on the gas; auto industry executives (and Uber) are now openly competing to bring the first self-driving cars on the market. It will come as no surprise to the readers of this blog that the initial business models are not concerned with selling cars but to provide mobility services.

These signals are important in themselves. They heat up the competition and force the rest of the auto industry to decide how to adapt their business model to fully self-driving cars and to explain this strategy to their investors, journalists and analysts. They increase the value of companies in the space and increase the competition for human capital (Google has probably lost between 500 million and 1 billion USD in human capital from the exodus of key members of their self-driving car group in this year (680 mio USD Uber paid for the Otto startup founded early 2016 by 4 Googlers (including Anthony Levandowski), plus Chris Urmson.). They also increase the effort of all parties involved (auto industry, suppliers, regulators, journalists, related industries such as transport & logistics, insurance, health care etc.) to understand the implications of fully self-driving cars which gradually drives away the many misconceptions and more clearly shows risks and opportunities. We are in the middle of a global, distributed innovation process around self-driving cars and driverless mobility where all parties are learning, refining their thinking, changing their vision of the future and adapting their actions accordingly. The avalanche is in full swing now and it will be a tough ride for those who fail to adapt while there is still time…

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.

First fully autonomous Audi expected by 2017

Several news media have reported that Stefan Moser, Audi Head of Product and Technology Communications, has announced that the next generation Audi A8 (expected by 2017) will be able to drive with full autonomy. Mr. Moser emphasized that Audi wants to be first to bring a self-driving car to market. He explained that the car will be equipped with cameras and LIDAR, that the car will drive much safer than humans could, and that their system will be based on a redundant hardware architecture where all computing will be performed by at least two independent processors. He also cautioned that legal hurdles remain for fully autonomous driving which could delay the availability of these features.

This announcement shows that car makers increasingly want to be seen as innovation leaders in the autonomous driving space. Audi has a mixed record in this area. They have have been very active in the field of driving dynamics – i.e. racing a self-driving car up Pikes Peak or around the Hockenheim race track. But the sensing and route planning algorithms of these prototypes are still quite primitive – they rely mostly on differential GPS supplemented with custom-built 3D maps for navigation. Audi has made great progress in autonomous racing on empty tracks  but driving in a dynamic, changing environment with other vehicles, pedestrians, etc. is a different ball game. It does not help that Volkswagen’s CEO Martin Winterkorn remains quite sceptical about fully autonomous technology (Audi is a subsidiary of Volkswagen). On the other hand, Audi has established itself as a technology-leader with respect to the computing platform for driver-assistance systems via its partnership with NVIDIA.

We hope that Mr. Moser’s statements are an indication of a change of heart within Volkswagen and that they will aggressively tackle the challenges of autonomous urban and highway driving. This requires an extensive program of computer-based learning and optimization and needs millions of kilometers of test-driving with autonomous car prototypes on regular roads.

Source: Motoring.com.au, CarAdvice

Autonomous vehicle roadmap: 2015-2030

Two and a half years ago I wrote a note on the various views about the paths for adopting self-driving vehicles. Since then, more and more signs point towards my ‘avalanche’ model, where the adoption of self-driving cars becomes a self-sustaining, accelerating process fueled by expectations of a fundamental transformation of the auto industry and major opportunities for profit.

As a thought exercise, I have sketched a hypothetical timeline which shows how this self-accelerating global innovation process could unfold. The purpose of the timeline is to show how autonomous vehicles could come into widespread use rather quickly and what kind of market and political forces could be involved. This is an extreme of many possible futures for self-driving cars:

2015 Google launches first short-range fully autonomous vehicle service in California at NASA Ames (not on public roads) and possibly in Mountain View (small scale pilot, limited to Google employees).

2015 The first auto makers (Daimler, Honda, Nissan?) announce major strategic initiatives and major investments to counter Googles’ threat and rapidly bring vehicles capable of full autonomy (Level 4) to the market.

2015 Car2Go (Daimler’s shared mobility service) announces a roadmap for autonomy in their car fleet.

2015 Automotive industry recognizes the implications of fully autonomous vehicles (transformation of mobility, significantly lowered worldwide demand). Analysts pound auto makers on their Level-4 autonomous vehicle strategy. Share prices begin a long decline.

2016 Google announces that their short range, limited-speed fully autonomous vehicle fleet will be built by Ford, Magna or others.

2016 China launches a major program to develop and deploy shared autonomous vehicles for local mobility. It recognizes that it can reduce infrastructure expenditure, jump-start their autonomous vehicle industry, reduce the ecological footprint of mobility etc.

2016 Google expands their short range autonomous vehicle service pilot to another US city that sees little rain and no snow, e.g. Las Vegas, NV or Sun City, AZ and starts their first overseas fleet.

2016 Price for semiconductor lasers used in LIDAR sensors falls below USD 150; this reduces the hardware/computing power costs for autonomous vehicles with 3D Lidars to below 10,000 USD.

2016 Transformative potential and benefits of autonomous vehicle technology are recognized widely. There is a bitter debate about the destruction of jobs.

2017 Several European countries have now adjusted their laws to allow the operation of fully autonomous vehicles on a national scale (not in international traffic).

2017 Autonomous long haul highway trucks start testing in the US, Europe or Japan.

2017 Rental car companies launch their own autonomous mobility inititiative.

2017 An international body for regulating autonomous vehicles is being formed in cooperation between the US, Europe and Japan.

2017 Google vehicles are now capable of driving in snow on pre-mapped routes.

2017 Automotive suppliers (Continental, Bosch, Valeo, or others) announce their own autonomous vehicles or special-purpose autonomous machines.

2017 Major road infrastructure projects are downsized because autonomous and connected vehicle technology have reduced the expectations on future transportation demands.

2017 Google moves their autonomous vehicle operations into a subsidiary which then merges with Uber and starts to roll out local autonomous vehicle mobility services in many more US cities.

2017 Singapore deploys the first autonomous bus for regular service. This is widely seen as a milestone for public transport and sends many transit corporations scrambling to update their strategies.

2017 The first countries mandate specific driving behavior for self-driving cars in certain driving situations.

2018 Car2Go starts to add autonomous vehicles to their fleet.

2018 The Google subsidiary/Uber merger rolls out autonomous vehicles internationally.

2018 Heavy investment into autonomous vehicle fleets and services based on autonomous vehicles. An almost unlimited amount of capital flows into startups and schemes. Countries compete trying to gain an advantage in the emerging new industries.

2018 Experience with autonomous vehicles shows that they are indeed much safer than the average human driver. People feel safe and comfortable in fully autonomous vehicles and there is no longer any question of user acceptance. No phenomenon similar to the ‘fear of flying’ can be found among users of self-driving cars.

2019 The Vienna Convention and European Laws are updated to allow the operation of fully autonomous vehicles.

2019 Autonomous vehicles now operate in over 50 cities worldwide.

2019 Rapid growth for autonomous trucks on specific routes. In many countries, truck drivers protest but this can only delay their adoption slightly.

2019 The first high-end consumer cars capable of fully autonomous driving on a large part of the national road network become available.

2020 The first countries introduce laws that prohibit bullying of autonomous vehicles (e.g. jumping in front of it to make it stop).

2020 Bleak outlook for automobile companies. Volume is down, consumers prepare for the transitioning to fully autonomous vehicles (which are not yet widely available for the consumer) or increasingly use/expect to use shared autonomous vehicle services. The fight for survival has begun: The auto industry has its “Kodak moment”.

2022 Prices for used cars decline. Too many people switch to shared autonomous vehicle schemes. Many others sell their old vehicles prematurely because they want to switch to the much safer fully autonomous models where they don’t need to drive if they don’t want to.

2022 The cost for autonomous vehicle hardware (sensors and computing power) has come down to 1500 USD.

2022 Mass transit companies increasingly rely on autonomous vehicles for transport. Transitioning the current workforce to a transit system based on autonomous vehicles is a major organizational and political challenge.

2022 Insurance rates favor operating cars in fully autonomous mode and prompt many people to stop driving on their own.

2023 Small autonomous buses are increasingly used for medium- and long distance trips. Trains have a hard time to compete on short to medium distances with autonomous buses.

2023 Most companies require that business trips with rental cars must occur in fully autonomous mode (for safety and productivity reasons).

2025 Fleets of autonomous vehicles now operate in most cities of developed nations.

2025 Automotive companies shut down more and more plants. Major automotive countries including Germany, Sweden and Japan desperately try to prop up their OEMs.

2030 Car ownership has declined dramatically. Only 20% of the US population still own a car (200 cars for 1000 people, today: 439 cars for 1000 people).  90% of all trips now happen in fully autonomous mode. Traffic accidents and fatalities have declined dramatically.

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

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.

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

The race for leadership in autonomous cars is on: Volvo to deploy 100 self-driving cars by 2017

2013 has been a year with a lot of buzz around self-driving cars. While Google has been mostly silent about their progress, many other players have demonstrated prototypes of  autonomous cars (including Mercedes, Nissan) and announced intentions to bring more and more autonomous features to the market.

Now Volvo Cars has announced a project to deploy 100 highly autonomous cars in the Swedish city of Gothenburg by 2017. The cars will drive without the need for human supervision on selected roads in Gothenburg (including motorways, regular surface streets etc.). In autonomous mode their speed will be limited to a maximum of 70km/h. The cars will not yet be able to drive fully autonously; they may have to return control to the driver in certain areas or traffic situations (however the car will be able to handle all short-term traffic situations without help from a driver). The cars will use 360 degree sensors including cameras, Lidar and radar. More information about the project is available in a video by Volvo.

The project is very significant because of its scope, short timeline until implementation and because it involves key partners such as the City of Gothenburg and the Swedish government (Swedish Transport Administration and Swedish Transport Agency) who may have to remove any remaining legal road blocks.

With this project the race has begun to establish autonomous vehicle technology in real-live urban settings. Much as we have predicted, the cars’ autonomous operation will be limited to a very specific region: Only selected roads in withing Gothenburg which  are carefully mapped. The cars will rely on the mobile communications to receive map updates as needed. Thus Volvo will have to build an operations center which supports the autonomous operation on a day-to-day basis and issues updates to the cars for changes, construction zones etc.

Volvo Cars has reported losses in the first half of 2013 of about 90 million USD on revenues of almost 9 billion USD; with the global economic recovery this may have improved in the second half of 2013. Nevertheless, as one of the smaller car makers,  leadership in the autonomous space may be a good strategy for survival.

It is not clear, however, whether Volvo realizes that much of the growth in this technology will come from fleets of self-driving cars operating in limited areas. If Volvo really wants to profit from the growth opportunities in this area, they will have to re-think their model structure and introduce smaller, probably even electric cars aimed at short-range fleet operations. Being owned by Geely, a Chinese automotive company, Volvo could be in an ideal position to introduce the new paradigm of autonomous mobility to China (which would greatly benefit from fleets of short-range autonomous electric vehicles for urban, pollution-free mobility).

The project shows that autonomous technology has entered a new phase where real projects are being implemented which require the cooperation of car makers, technology providers, cities and governments. The British project in Milton Keynes is another example as well as the project to rethink urban mobility in Singapore (where the French company Induct are involved with their Navia autonomous shuttle as well as MIT).

Sources: Lindholmen Science Park, Volvo

Nissan tests autonomous Leaf on Japanese highway

Underscoring their intention to develop vehicles which are capable of full autonomy, Nissan has shown one of their autonomous Leaf prototypes on a public Japanese highway to the press. The auto-pilot system not only kept lane and distance; it also was also able to switch lanes, overtake other cars and merge into traffic at on-ramps. Although the highway segment was short and no details were provided on the quality of the lane markings (or localization algorithms) and merging capabilities, this event certainly shows that Nissan is committed to its vision of fully autonomous driving and aims to be perceived as an innovation leader. The event does not yet show, however, that it prototypes are more advanced than similar prototypes by other auto makers (e.g. Daimler, BMW etc.).

Sources: Nissan, Japan-News