Self-driving vehicles: outlook for 2018

After the race for fully self-driving cars heated up in 2016, 2017 became a year with exciting developments – many billions of dollars changed hands for self-driving car related acquisitions(1) and many collaborations were started(2). But besides progress, 2017 also showed some limits: Tesla was plagued by defections from their SDC team and had to cancel their fully autonomous coast to coast test drive planned for the end of 2017 and shift the target date for their fully self-driving capability back by 2 years. Volvo effectively cancelled their planned Gothenburg self-driving car trials (by changing the scope to a test of driver assistance technologies).

Nevertheless an enormously important milestone for the adoption of self-driving cars has been reached in 2017: Waymo is now operating self-driving cars without test driver on public roads in Phoenix, Arizona. Five years ago we had expected this milestone to be reached around 2018. This unequivocally demonstrates to the world that self-driving cars are viable and that they can no longer be considered a technology that is half a decade or more away.

This milestone (and the multitude of achievements of the many actors involved up to the end of 2017) also change the dynamics of the global distributed innovation process around autonomous vehicles. It is beginning to shift from the typical chaotic process involving many different actors with little formal organization trying out different paths and approaches to a more mature process. The acquisitions we have seen in 2016 and 2017 are an indicator that the global innovation process is consolidating and getting closer to move from the early stage of an innovation process (called ‘fluid phase’ in innovation theory) to the ‘transitional phase’. This is a major step typically associated with deep structural changes in the innovation process. We may reach a peak in the number of companies competing to develop self-driving car technology in 2018 or 2019 before seeing a market shakeout thereafter.

For the auto-industry, 2018 will be a crucial year because the time is running out for most OEMs to ensure that they can weather the changes caused by self-driving cars and – maybe even more importantly – that they can identify, understand and profit from new opportunities. There can be no doubt that car sales will come under pressure in the early 2020ies as autonomous mobility services (both for local and long-distance travel) grab a significant share of the mobility market, consumers fundamentally change their car-buying behavior and some emerging markets adjust their traffic infrastructure policies to take advantage of self-driving car technology.

OEMS that have not yet committed to a serious self-driving car strategy risk their medium-term competitive position. With every year that passes, it will become more difficult to adjust to the changes coming to the auto industry. It is unlikely that OEMs will be able to offset losses in demand for privately owned cars by building self-driving cars and selling or leasing them to mobility service providers (or operating them themselves). When the industry gradually comes to accept the reality of shrinking demand for automobiles, it will become more and more difficult to adjust because profitability will fall rapidly and with it the ability to change. Several automakers are likely to fall into the Kodak trap: Kodak was the first company to develop a digital camera. It always understood digital cameras but it failed to reinvent its business model in time and then was unable to turn around the already sinking ship which was bleeding from all sides. The European, Korean and Japanese auto makers need to strongly accelerate their self-driving car activities if they want to survive the coming turmoils of the next decade. General Motors seems to be the only OEM which currently is well positioned in this space. It is pity that Daimler, one of the earliest pioneers of self-driving cars, appears to be content to mostly watch from the sidelines.

In 2018, we can expect another change in the maturing innovation process: The focus will start to move away from the core technical issues towards the implications for the automobile as a whole (its interior, exterior and structural design, its supporting and sales infrastructure etc.) and towards the business models associated with self-driving cars. There are many more use cases for self-driving technology than just ferrying people around; many of these use cases have strong services components which OEMs (or their challengers) need to embrace. 2018 may also be the year where players beyond the auto industry start to seriously consider the implications, opportunities and risks. Retail will be deeply affected by dramatically falling local distribution costs. In the next decade nany supermarkets will have to close their doors as products can be delivered conveniently (and with very customer-flexible timing) to the doorstep. Hospitals, care and emergency services will need to adjust to fewer traffic related injuries. Most industries will need to consider the implications and opportunities associated with significantly lower transportation costs (affecting both inbound and outbound logistics and possibly providing new product or service opportunities). Cities, countries, architects, construction firms need to start planning for a future where mobility is provisioned differently and where space and capacity requirements for transportation are changing. Railways and transportation companies need to consider the challenges which will be raised by autonomous mobility services providers. Self-driving cars and machines will also have major impact on construction and agriculture industries and provide new opportunities there.

2018 may also be the year where the opposition to self-driving cars finds their voice. While self-driving cars have enormous benefits they will eliminate many jobs (not just professional drivers but also in the auto industry and many other industries). Society needs to find ways to cope with the fundamental changes that result from software-based devices with capabilities which some call ‘artificial’ intelligence and we all need to consider in depth how the fabric of society will be impacted and what changes on the different subsystems of society will be necessary. This process should not be underestimated and requires a major, multi-disciplinary effort.

In 2018, every business, organization, political actor, and any forward-thinking individual should take the time to look beyond the technicalities of self-driving cars and carefully consider their implications, opportunities and risks!

Update: 2018-01-16: Removed a sentence stating that BMW seemed to have reduced the extents of its targets for autonomy in 2021.

(1) Acquisitions: Intel/MobilEye, Delphi/Nutonomy, Cruise Automation/Strobe, Ford/ArgoAI (Ford majority stakeholder), ArgoAI/Princeton Lightwave

2) Cooperations: Waymo with Lyft, Avis and others, Daimler/Bosch, Baidu/Apollo platform, Intel Alliance, Uber/Daimler

Intelligent vehicle symposium showcases advances in driverless technology

Driverless technology researchers gathered at the beginning of June for the IEEE Intelligent Vehicles Symposium. With almost 200 presentations from more than 600 authors probably no aspect of this technology was left untouched.

This was not just an academic get-together: many of the papers involved major car makers (BMW, Toyota, Daimler, Renault, Volvo, Opel, Volkswagen, General Motors, Hyundai) or automotive suppliers (Delphi, Bosch).

The conference started with a reportedly captivating keynote presentation by Google’s Chris Urmson. Unfortunately, I have not been able to obtain more detailed information about its content. Please contact me if you were there!! Robert Bertini (Intelligent Transportation Systems Lab) gave another keynote on the environmental issues related to intelligent transportation which took the perspective beyond technical issues towards societal and environmental impacts.

It is hard to pick out the most interesting papers. But Daimler presented a new approach for improving stereo vision using a ‘Stixel’-based approach for object recognition. They claim that they are able to reduce false positives by a factor of 8 over the state of the art while reducing the computational costs by a factor of 10.

China¬† also seems to be moving ahead with driverless technology. Two papers (1, 2) were presented from participants of the annual Chinese driverless vehicle competition (‘ Future Challenge of Intelligent Vehicles’) funded by their National Nature Science Foundation.

Several papers focused on pedestrian modeling and recognition. Volkswagen described their approach to systematically drive an autonomous car at the vehicle’s handling limits. DLR presented an approach to apply autonomous vehicles localization technology to trains.

The symposium was located in Alcala de Henares, Spain. It also included demonstrations of autonomous vehicle systems.