Monitoring the self-driving car innovation process: California AV permits

Since 2014, many companies have applied in California for testing self-driving cars. The list of companies which have received a permit can be used as a measure for the innovation process associated with autonomous vehicle technology. The graph below shows how the number of companies active in California has only increased gradually from 2014 to the third quarter of 2016. A steep increase follows in 2017. The slope softens in the first half of 2018.

Of course it would be premature to conclude that we are already seeing the beginning of the end of the S-curve which is so typical for innovation processes. And the California AV permits can only be seen as a proxy for the larger distributed self-driving vehicle innovation process currently unfolding across the world.

Active AV permits by month

Active California AV permits by month (Data from California DMV) Updated: 2018-08-07

 

 

But neither the number of California AV permits nor the number of companies providing self-driving vehicle solutions will grow indefinitely. The time will come where the industry moves into the next phase, where the exploratory modes of development will be replaced by more systematic, managerial approaches and where commercialization will be the primary focus. A shakeout is inevitable. Time may be running out for those who still want to jump onto the self-driving car train…

 

Notes:
– 58 permits have been issued by the end of June 2018; One permit has not been renewed (Uber), making it 57 active permits.

Updates:

The graphic is updated from time to time. You may need to hit reload to view the current version of the graphic.

– 2018-08-07: By the end of July 2018, 2 companies did not renew their permits (Wheego Electric and Bauer’s Intelligent Transportation) reducing the number of active permits to 55.

The big squeeze: How self-driving vehicles will put pressure on the car market

In the next five years the first fully self-driving cars will become available for purchase. This will happen after the first fleets of self-driving taxis appear in our cities. How will this affect the demand for private cars? We can expect consumers to react in multiple ways:

In the high end of the market, additional demand will be generated by price-insensitive customers who greatly value their personal time and greatly value their own life. For many affluent consumers who spend significant time at the wheel, full self-driving capability will be a must have and they will not wait until the end of the usage cycle of their current car but have high motivation to switch to a new, fully autonomous model early. People who lease their car will demand upgrades (for example via lease pull aheads) while affluent consumers who buy their own cars, will just replace their old model early. This will lead to a spike in demand for premium vehicles – which is positive for the auto industry.

At the same time it will produce a dent in demand in the run up until the first self-driving models become available. The more customers get the impression that reliable self-driving models will be available on the market soon, the more they will hold off on purchasing a non-self-driving model. Individuals and companies are likely to extend expiring leases on premium cars for a short time just to be sure to switch to fully-self-driving vehicles as early as possible. For any company the most rational path to take is to adopt fully self-driving cars as early as possible because this has a direct positive effect on the productivity and health of their employees.

It is important to recognize that this adoption path can not be incremental. Driver assistance systems are getting better and they indeed follow an incremental route. But the switch to full self-driving is a disruption: only from that moment on can the driver turn his attention away and go to sleep, go over documents, watch a movie or find other ways of using their time. For affluent people who value their time at just $50 per hour, this translates into enourmous benefits ($18250 per year with an average of 1 hour per day in a car) compared to a car model with a high performing driver assistance system.

These reasons have another consequence: The demand for new premium vehicles without fully self-driving capability will crash. The self-driving feature will be a critical benefit for almost every customer; only the exceptionally loyal will avoid switching from a brand that can not offer full self-driving to another premium brand with full self-driving. In this part of the market (excluding chauffeured cars and aficionado cars) competetion will be enormous. Brands which are late coming to the market will dramatically loose market share. We may see a very rapid shakeout in this part of the industry.

The picture looks different for more price-sensitive customers. A small part of this group will find that the obvious additional time and risk-reducing benefits of self-driving cars are reason enough to spend more on a car purchase and upgrade to a premium self-driving vehicle. This will add to the initial demand for premium self-driving cars.

A much larger group will find that they can not afford a premium self-driving car. This group has two major options: It can wait until self-driving capabilities trickle down to less expensive cars. Given the significant benefits of the self-driving feature this has the consequence that they will hold off on purchasing new cars in their segment until self-driving capabilities arrive. Demand for new cars in these seqments will therefore fall and OEMs will feel the pressure to accelerate the introduction of self-driving capabilities into the lower segments of the car market.

The other option for the more price-sensitive group is to switch to mobility services where available. Self-driving taxis are likely to provide mobility at a cost per kilometer that is not significantly higher than the total cost per kilometer of the average privately owned car without self-driving capability. Because this option will be available in many cities even before self-driving cars can be purchased many customers will already experience self-driving and its benefits. In high density urban areas, where space is at a premium, reducing the number of cars per household or even eliminating all personal cars will be the obvious solution. In many such areas the marginal costs of using a private car will be higher than using a self-driving taxi. In all areas where fleet services take hold (this will include many areas with lower density) we will see that households will reduce the number of vehicles they own.

For a part of this more price-sensitive group which can not afford premium self-driving vehicles, the most rational choice will be to switch to robo taxis early – even if they are more expensive than the marginal cost of using their own car – because this will allow them to use their personal time for something better than driving and increase their safety.

Thus even before the first fully self driving cars appear on the market, we will see a drop in demand for new vehicles caused by an increasing adoption of self-driving mobility services as well as the expectation that more affordable privately owned cars will be available in the near future. In this period, the demand for non self-driving vehicles in the lower segments must fall because some consumers are reducing the number of cars in their household by switching to self-driving mobility services and others hold off buying new cars with the expectation that more affordable self-driving cars will appear on the market in the near future.

This will have an effect on the used car market: As people switch to using self-driving mobility services in densely populated areas, they will sell their current cars prematurely; this will reduce prices in the used car market. A smaller group of customers will want to hold off buying a new car until self-driving features become available in their segment. This effect will be small and not be enough to counteract the price drop for used cars.

This will lead to a dilemma for the auto industry: because demand for cars drop and more hiqh quality used cars become available on the used car market, demand for new cars without self-driving capabilities falls. However if the auto industry rapidly switches to offering self-driving cars in the lower segments, then consumers will switch even faster to self-driving cars and cars without self-driving capability will become hard to sell. Prices for traditional cars will fall and traditional cars will depreciate much faster. OEMs that don’t offer self-driving capability will rapidly loose market share.

It is inevitable, therefore, that the advent of self-driving cars will squeeze demand for privately owned cars. It is not possible to rapidly roll out cheap self-driving capability in all segments. On the path to this future, demand for new cars must shrink because for some customers it is rational to hold off on purchasing a new car to wait for the availabity of the self-driving capability, for other customers it is rational to switch to using self-driving mobility services, and last but no least every price cut in self-driving technology makes the use of fleets economically more attractive compared with the use of a privately owned self-driving car.

Thus the auto industry is in a difficult position. As long as the advent of fully self-driving private cars is only a distant vision on the horizon, everything looks like business as usual. But when the first fleets of self-driving cars provide mobility services in an increasing number of cities across the globe over the next three years and as consumers take notice that the release of the first fully self-driving private vehicles appear imminent, then the auto industry will experience a major shakeout. Time to react will then be very short and the survival of more than one OEM will be in question!

Fleets of self-driving cars will not be limited to high-density urban areas

Self-driving mobility services are likely to be adopted quickly in high density urban areas. In these regions, car ownership is likely to fall significantly. Several studies have shown that one autonomous taxi might provide sufficient transport capacity to service the mobility needs which are currently fulfilled with 6 to 10 privately owned vehicles. These studies have considered local motorized mobility in large cities such as Ann Arbor, Lisbon, Austin and others.

But how will autonomous fleets impact mobility and car ownership in less densely populated areas? About 86% of the US population live in metropolitan statistical areas (i.e. areas that have a relatively high population density at its core). These are not limited to the great cities and agglomerations on the west and east coast but include much smaller areas such as the Grand Forks metropolitan area which comprises 2 adjacent counties in North Dakota and Minnesota with about 100,000 inhabitants (in 2014) and a population density of 11 people per km square. Of course, self-driving mobility services will be very viable in the urban core of this metro area where about 60,000 people live. The remaining 40,000 people living in rural parts of this area have significant, predictable mobility demands for trips towards and back from the urban core. Thus there is a potential for self-driving mobility services even in the outer, less densely populated parts of metropolitan statistical areas. A further 8.6% of the US population live in in micropolitan statistical areas (i.e. areas which are centered around an urban cluster with at least 10,000 but less than 50,000 people). The remaining 6% of the US population live neither in a metropolitan nor a micropolitan statistical area (see the white area in the map of metropolitan and micropolitan areas in US). It is instructive to consider their situation.

Let’s take Sidney, Montana as an example (Google maps): This is a small town with just about 5,000 inhabitants in eastern Montana. It is far away from more populated centers. The nearest larger city is Williston, ND with about 20,000 inhabitants at a distance of 70km. The next city with more than 100,000 inhabitants is Billings, MT at a distance of about 430km. There seems to be a significant mobility demand for trips to Billings: more than four flights leave for Billings every day (airfare about 40 USD). Uber is already active in this town and popular destinations/pick up spots include the airport, high school, health center and Holiday Inn Express.

The US currently has a stock of about 240 million light duty cars, which translates to about 750 cars for a thousand people. Because this ratio is higher in areas with lower population density, there should be significantly more than 5*750=3750 light duty cars in Sidney. Because a large share of the daily trips are local, and because their average speed is high compared to the speed in congested cities, autonomous fleets should be able to provide high-yield mobility services with a relatively small fleet. With a replacement rate of 1 to 7, about 535 self-driving vehicles could theoretically replace the town’s entire vehicle stock. The local mobility demands of 5000 people are also large enough that a mobility services provider can start with the smallest economically viable fleet size of probably somewhere between 10 and 20 cars and then grow the fleet as demand picks up. The low regional population density has an interesting consequence for non-local trips: The number of typical destinations is small; the number of routes people can travel from/to Sidney is quite limited. Therefore the potential for on-demand shuttles is high; Williston, with it’s Walmart (about a 1 hour drive) is an obvious target. Such shuttles have another side effect: they can provide the same mobility service to all locations which they pass on their route. Such shuttles therefore effectively will bring access to self-driving mobility services to some very rural dwellings.

Today, households in low density areas of the US have much higher car ownership rates than the rest of the population: there simply are  no viable alternatives. Self-driving cars fundamentally change this situation. Wherever there is a minimum of demand for personal mobility, self-driving mobility services become economically viable. The number of persons needed to sustain a self-driving taxi resource is rather small; towns with just a few thousand of inhabitants should always provide enough demand to allow a small fleet of self-driving taxis to operate. Initially it may only be the seniors who use these services but then households will start to think about the number of cars they really need and gradually demand for these services (and with it, supply) will increase.

In many lower density areas of the United States, car ownership is a prerequisite for finding work and – as a consequence – people without cars suffer and economic opportunities are lost. For seniors access to medical services and just getting around can be extremely difficult. The young face similar problems. These examples show that we can expect sufficient demand for self-driving mobility services in most parts of the United States – including many small towns and even in many areas that have low population densities. The impact of fleets of self-driving cars will not at all be limited to big cities!

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…

Cities around the world jump on the self-driving car bandwagon

Autonomous vehicles will have a major impact on urban transportation. Mayors, transportation companies and urban planners are increasingly taking notice. The number of cities which recognize the benefits of self-driving cars and buses increases rapidly. Below is a list of some cities around the world which have launched or are working to launch activities focused on self-driving cars and buses:

San Francisco, Austin, Columbus, Denver, Kansas City, Pittsburgh, Portland (Oregon):These seven cities strive to be pioneers in integrating self-driving car technology into their transportation network. Each of these cities has already received a 100.000 USD grant from the US Department of Transportation (Smart City Challenge) to refine their earlier proposals on how to transform their urban transportation systems. In June, Secretary of Transportation Anthony Foxx will award a 50 million USD grant to one of these 7 cities to become the first city to implement self-driving car and related technology into their urban transportation system. San Francisco, for example, has proposed phased plans to deploy autonomous buses and neighborhood shuttles. The city has also gathered pledges of an additional 99 million USD from 40 companies in case it receives the 50 million USD grant.

Milton Keynes, UK: Trials of self-driving pods have already begun in this British city. The electric pods will transport people at low speed between the train station and the city center. Additional UK cities which are experimenting with self-driving car technologies are London (self-driving shuttles, Volvo Drive Me London), Coventry and Bristol.

Singapore: This may be the most active and visionary city with respect to driverless transportation. Several years ago it has launched the Singapore Autonomous Vehicle Initiative, partnered with MIT on future urban mobility and initiated several projects aimed at improving urban transportation systems through self-driving car technology. The city has already set up a testing zone for self-driving cars and is conducting several trials in 2016.

Wageningen / Dutch Province Gelderland (Netherlands): A project with driverless shuttles is already underway. The self-driving Wepods aim to revolutionize public transport and provide a new, cost-effective way to bring public transportation to under-served areas.

Wuhu, China: According to Baidu’s head of self-driving cars, self-driving cars and buses will be introduced into the city of Wuhu over the next five years.

Beverly Hills, USA: The city council of Beverly Hills has just passed a resolution aimed at the long-term adoption of self-driving cars. The resolution starts first activities towards achieving that goal but does not yet commit major resources.

Google prepares for manufacturing of driverless car

Google continues to push for the introduction of their self-driving cars on public roads. After positive statements by NHTSA and overtures from the United Kingdom and Isle of Man to test their cars there, job postings show that Google aims to significantly grow their self-driving car team. The 36 job descriptions below show that Google expands activities on all aspects of their self-driving car, including manufacturing, global sourcing, automotive noise and vibration, electrical engineering etc. It remains unlikely that Google intends to manufacture their cars themselves but the job postings complete the picture that Google wants to build a manufacturing-ready reference design of a fully self-driving car which they can either use for having their cars manufactured by a supplier or which can inform licensing and cooperation discussion with OEMs from the auto industry.

The job postings below were obtained from the Google job search engine on 2016-02-13 with a reusable query. All 36 jobs are for the Self-Driving Car team at Google-X:

  1. Mechanical Global Supply Chain Manager
  2. Mechanical Manufacturing Development Engineer
  3. Manufacturing Process Engineer
  4. Manufacturing Supplier Quality Engineer
  5. PCBA and Final Assembly Global Supply Manager
  6. Automotive NVH (Noise, Vibration, Harshnees), Lead
  7. Manufacturing Test Engineer
  8. Reliability Engineer, Vehicle Test Lead
  9. Reliability Engineer
  10. Product Manager, Vehicle 
  11. Global Commmodity Manager
  12. Industrial Designer
  13. Marketing Manager
  14. Technical Program Manager, Vehicle Safety
  15. Operations Program Manager
  16. Policy Analyst
  17. Head of Real Estate and Workplace Services
  18. Product Manager, Robotics
  19. User Experience Researcher
  20. Mechatronics Engineer
  21. Electrical Engineer
  22. Mechanical Engineer, Lead
  23. Systems Engineer, Motion Control
  24. Systems Engineer, Compute and Display
  25. Reliability Engineer, Lead
  26. Vehicle Systems Engineer
  27. Perception Sensing Systems Engineer
  28. Embedded Software Engineer
  29. Electrical Validation Engineer
  30. Systems Engineer
  31. Radio-Frequency Test Engineer
  32. Researcher/ Robotics Software Engineer
  33. Radio Frequency/High Speed Digital Hardward Design Engineer
  34. Camera Hardware Engineer
  35. Mechanical Engineer, Laser
  36. HMI Displays Hardware Engineering Lead