Driverless Electric Cars as a Service – One Adoption Scenario

ap_16258099841091

Self-driving Uber vehicles are lined up to take journalists on rides during a media preview at the company’s Advanced Technologies Center in Pittsburgh earlier this month.

As I ponder the changes that driverless cars will cause across our societies, one of the difficulties is trying to understand what the speed of adoption might be. That is because speed of adoption has huge consequences on the levels of disruption that will occur. The speed of adoption linked into all sorts of factors including:

  • Production bottlenecks in the supply chain such as raw materials, and battery supply.
  • Production capacity for manufacturing of electric driverless cars.
  • Technical issues in achieving true Level 5 automation (think no steering wheel).
  • Political and legal issues around liability and insurance.
  • The balance between the numbers of cars in personal ownership, and the number owned by big companies providing transport services (think Uber/Lyft/Didi and new entrants like Waymo).

 

In turn these factors will be affected by the business models and strategic thinking of the major players. This includes car manufacturers, car ride companies, and governments.
The competition is going to be brutal. Existing car companies will be going up against each other, and new competitors. The new competitors include car ride sharing companies, and new car manufacturers.

Some of the major problems in implementing driverless electric cars as a transport service can be largely solved by car ride companies. The problems include the following:

The Initial Scale/Network Problem

The problem if you want to offer transport as service is you have to get to scale before customers will even contemplate using your service. You cannot put 100 cars on the road and say here I am. This is like the network problem of the first fax machine but on a much larger scale. Who buys the first fax machine? You might buy half a dozen of them so you can communicate between distant offices of the same company. The real value comes when it is a standard system adopted by many people. The problem with transport as a service is that it is much larger. The reality is that people will not use your service until they can consistently get a car in a reasonable time frame to take them wherever they want to go. That needs massive scale and is the reason why Uber was so aggressive in recruiting drivers in target cities. They needed a critical mass to drive customer demand.
A new entrant with electric driverless cars can provide this service but they will need a lot of cars. If you need 100,000 vehicles at peak time in Melbourne (where I live) to supply that service it requires a lot of capital. If the cars cost $50,000 each it is going to cost you $5 billion just for the cars.  That is apart from the costs of the platform to run the system, plus the initial trading losses that will be incurred before breaking even. Not many organisations will have that sort of money, and that might just be for one city. Waymo or Apple might be an exception given the masses of cash that they have. The existing car ride companies got around this problem by using other people’s cars. Difficult to do that for driverless cars although we will explore a model for that in a later post.
The existing car ride companies (Didi, Lyft, Uber, etc) are already at the scale needed to supply the services for their existing customer base. Adding driverless electric cars into that service is somewhat analogous to the electricity grid. Once the standard utility service is in place (think poles, wires, plugs and standards for electricity, and roads and traffic systems for cars) you can make additions as long as they fit the system. You can add a new coal generating plant, or a new gas plant, or new solar capacity and power comes out at the socket. My desk lamp does not care how the power was generated. In the case of a car ride service as long as the customers accept a driverless car you can put that into your system alongside your existing fleet. You may need to drive (sic) demand by offering discounts for the driverless vehicle to get people past their first stages of discomfort. In my case the safety factor is likely to be the key initial driver for change but I am an outlier.

The Capital Problem

If you are a company that wants to supply transport as a service you will want to scale as fast as you can. Ideally you will offer a service in 50 cities in the first 3 – 5 years. If we assume that takes 100,000 vehicles in each city and each car costs $50,000 you now have a cost of $250 billion. If you add in technology platform costs , and initial losses you might have to find $350 billion. That is a lot of coin in anyone’s language. Even if the required vehicle numbers are much lower it is still going to be a massive capital investment.
Even if you don’t move that fast you will have to make large bets in the target cities where you first invest.
If you are a car ride company you can scale by steadily adding cars to your existing services in all those cities. That should have the effect of reducing your costs, and improving your bottom line at a much slower capital burn rate. You can also play a much more agile strategic game. If you perceive a threat in a particular market you can scale faster in that market and slower in other markets. If adoption rates are faster in one city you can rapidly scale up volume in that city by slowing each of your other markets just a little.

The Technical Problem

The technical problem is getting to level 5 automation as soon as possible. Level 5 automation is when there is no driver required in any location or conditions. Any driverless car company will have to convince the regulatory authorities of safety at level 5.  The existing ride companies have an advantage here. They already have masses of data on the travel their existing cars undertake. They can also start with say 100 driverless vehicles within their existing service. That will consist of testing them in real conditions with paid drivers in the vehicles. While a lot of advances in driverless car systems are being made using computer simulations nothing fully substitutes for real world data. Especially for politicians and for regulatory authorities.  That real world data can then be fed back into simulation systems to gain an advantage in simulation programs

Existing car ride companies are the most likely path to adoption of driverless electric cars. These types of cars provide significant reductions in the cost structures for car ride services. This means that if they sit on their hands someone will come along and blow their existing services out of the water. The car ride companies have the competitive imperative to go down this path. They also have some significant competitive advantages in executing the strategy. That does not mean they will be successful, just that they have a head start.

In our next post we will take a closer look at some of the players, and the tactics that might be involved.

I am writing a book on autonomous vehicles with Dr Chris Rice from Texas. It is called Rise of the Autobots: How Driverless Vehicles will Transform our Economies and our Communities. Stay tuned for more excerpts as we finalise the book.

Note: Featured image is from NPR

 

 

Advertisement

Electric Cars and the Legacy Issue

Chris Rice and I are currently writing a book on the rise of autonomous vehicles and their widespread effects across our economies (entitled Rise of the Autobots: How Driverless Vehicles will change our Societies and our Economies). One of the keys to looking at what these changes might mean and the rate at which they will occur is the speed of adoption speed of electric cars and autonomous vehicles combined together.

There have been lots of excited announcements about electric cars over the last few months including:

India to make every single car electric by 2030 in bid to tackle pollution that kills millions
The Electric-Car Boom Is So Real Even Oil Companies Say It’s Coming
When Will Electric Cars Go Mainstream? It May Be Sooner Than You Think

The reality is that the adoption of electric cars will have several bottlenecks including but not limited to:

  • Battery availability.
  • Production capacity for manufacturing.
  • The reluctance of people to adopt the technology until they are completely sure that the charging issues and the range issue have been adequately dealt with.
  • The long-term nature of the turnover of the vehicle fleet.

Both battery production and electric car production are ramping up but the last point is very important when we start looking at the critical mass needed to disrupt a range of industries, including petrol stations and their supply chains, maintenance and repair systems, and the electric power grid. Even when it becomes a sensible economic decision to purchase a new electric car over an internal combustion engine (ICE) powered car, someone with a 7 year old vehicle is not going to immediately changeover. This is both due to the capital nature of the change and the fact that if electric cars are more economical than ICE cars the resale value of second hand ICE cars will fall dramatically, reducing the interest and capacity of people to purchase a new vehicle (if purchase is the model). This will be exacerbated if the new electric vehicles also have significant advantages in autonomy.

To illustrate this issue we took a look at the vehicle fleet in New South Wales in Australia If we look at the statistics at the end of the fourth quarter in 2016 it gives us a snapshot of the vehicle legacy issue. The following graph shows the year of manufacture for light vehicles registered in NSW at the end of 2016. The majority are passenger vehicles:

light vehicle registrations in NSW 2016 Q4

Source: http://www.rms.nsw.gov.au/about/corporate-publications/statistics/registrationandlicensing/tables/table113_2016q4.html  – accessed July 24th 2017

While the 2016 manufactured vehicles are under-represented in this graph as many 2016 vehicles are registered in 2017, it nevertheless gives a clear picture of the ownership structure of light vehicles. If we look deeper in the data we see that 20.1% of the registered light vehicles are manufactured prior to 2001.

If we look at heavy vehicles we get a similar picture albeit with different percentages:

heavy vehicle registrations in NSW 2016 Q4

There are some differences in the data between light and heavy vehicles:

  • The first is that there are significantly more 2007 heavy vehicles registered than any other year. This probably relates to GFC issues.
  • The second is that the heavy vehicle curve is lower than the light vehicle curve. This probably reflects a pattern of use where heavy vehicles are sold into a secondary market that will discount vehicles significantly if the economic model is significantly different than the new vehicle one, extending the useful economic life of the vehicles. This means that the percentage of total registered heavy vehicles prior to 2001 is 34.2%, much higher than light vehicles.
  • The third is that there are many more vintage models in the light vehicle category, reflecting the motoring enthusiast and restoration market. So there are 3,379 registered light vehicles manufactured 1900-1949, but only 21 heavy vehicles for the same period.

A very simplistic look at this data says that even if every vehicle sold new in Australia was electric from say 2025 was an electric car, and the purchase patterns remained stable after 5 years we would have between 31% and 40% electric light vehicles on the road and in 10 years it would be somewhere between 50 and 60%. This pattern is highly unlikely and so the real adoption rates will be well short of that. Every year that the purchase pattern is 50% electric and 50% ICE will slow the transition as those ICE cars will be on the road for a long time.

This adoption cycle is complicated by our view that increasing automation will result in more fleet ownership models, and shared car rides, reducing the total sales of new vehicles. While this means that battery and electric car manufacturing do not have to ramp up as much to get to 100% of new sales it changes the adoption curve.

Now both those simplistic analyses assume the normal pattern of car purchases and ownership will remain in place. That is also unrealistic. All we do know is that the adoption rates will be relatively slow because of the legacy issues and the turnover of the vehicle fleet as a whole. Cars are not smartphones. We will be doing some more modelling on the possible scenarios over the next few weeks. Follow us here if you want to see them and help us think through the changes.

 

Featured Image is from :

Top 8 Secrets for Competitive Electric cars-Tips for Auto Manufacturers by Ameen Shageer

 

 

Re-Purposed Electric Car Batteries and Its Effects on Electric Car Adoption/Driverless Car Adoption

Last night I attended the Churchill Club event in Melbourne on the future of batteries. There was a great panel presenting and the discussions covered a range of battery technologies, including Ecoult which is commercialising the CSIRO ultracapacitor technology for lead acid batteries.

In particular I was interested in the presentation by Relectrify CEO and Co-Founder Valentin Muenzel who talked about Relectrify’s mission to use electric car batteries that were no longer useful in energy storage applications. This was interesting because as part of my research for a book that Chris Rice and I are writing on the future of driverless cars I had been looking at the adoption rates of electric cars as part of the rise of driverless cars. In that research I had come across an assessment by Ark Investments that had calculated the net present value of an electric car battery in a specific energy storage scenario as shown in the following table:

Ark Invest battery depreciation table

source: https://ark-invest.com/research/ev-batteries-value – accessed June 20th 2017

The basic principle is that while a battery in an electric car might have its performance degrade to a point where it is no longer useful for driving, that battery will still have significant storage capacity (think about your phone battery after 18 months – it still works but its capacity is reduced).  If you can buy that battery cheaply and adapt it to storage use then you have a cost effective solution.

Of course the Net Present Value calculation in the table is for a specified energy reserve use which has a higher price, and nobody buys an asset for its Net Present Value otherwise all you do is get your money back over time. In discussions with Valentin he told me that without giving away commercial secrets the model for them is about 50% of the value of a new battery. This is important because the cost of new car batteries is falling. An analysis of battery prices by Bloomberg New Energy Finance in January showed the pace of that change:

battery prices falling fast from Bloomberg

source: https://www.bloomberg.com/news/articles/2017-01-30/tesla-s-battery-revolution-just-reached-critical-mass  

Now this is the price of the battery itself which is not the same as an installed battery system but the progress has been amazing, and mirrors what we have seen in solar energy. No great basic technology breakthrough, but significant technology improvements driven by the cost learning curve. In a separate report Mckinsey has stated that electric vehicle batteries fell to $227/kWh in 2016 with Tesla claiming to be below $190 per kWh (Electric vehicle battery cost dropped 80% in 6 years down to $227/kWh – Tesla claims to be below $190/kWh) Rumours have also circulated that Tesla has got the battery costs down to $125 per kWh (Tesla is now claiming 35% battery cost reduction at ‘Gigafactory 1’ – hinting at breakthrough cost below $125/kWh) although the truth of that remains to be seen. There is no doubt about the rapid pace of changes occurring, just the quantum of that change.

Valentin and I also discussed the model for autonomous vehicles given that a fleet model or a car sharing model means that cars would travel far more kilometres in a year. For an electric car this means that the battery will reach its degradation limit more quickly as the battery would be charged and discharged more often. Interestingly for Valentin this meant that the battery would be worth more for repurposing, because outside of the energy capacity the battery still retained, its relative newness means the technology is likely to be more advanced, and safety and physical deterioration characteristics would be much better.

Given that storage is likely to become far more important in the future given changes in the energy generation mixes around the world it puts a slightly different complexion on the costs of electric cars. It is our view that the end game for driverless cars is mass fleets supplied as a service with hardly anybody owning a car. If electric car batteries only last 3 years in shared driverless vehicle but have significant re-sale value it lowers the lifetime cost of a kilometre travelled and therefore accelerates us to the point where the cost of running an electric car is lower than running a fossil fuel car. Lifetime cost factors less into individual car ownership decisions but if you own 50,000 cars in a mass fleet in a highly competitive market it becomes it becomes a much more important factor. This changes adoption rates and also the balance between fossil fuel and electric cars.

The effects of this will be lumpy as Valentin advised that different batteries have different degrees of difficulty for repurposing as stationary storage. This is related to the original design decisions made for the battery technology which were originally made with the purpose of electric cars in mind, not stationary storage. For example apparently Tesla has stated that their car batteries will not be repurposed and that is due to the design constraints in their battery technology.

A note of caution:

In a discussion with John Wood (CEO of Ecoult) he quite rightly warned me to be careful of the public statements of battery manufacturers and suppliers on their lifetime use. Given that we are talking about changes in technology and lifetimes of 10-15 years which are therefore untested in the real world, those are wise words.

 

Image credit: The featured image is from http://www.relectrify.com/

Tech Toys When Simple Will Do – $100,000 V $500

Give me $500 and I will fix the problem

 

On Monday there was a story here in Australia about traffic lights being installed in the pavement to reduce the risk of pedestrians crossing the road against the lights because they were looking down at their mobile phone screens: (Lights installed in Melbourne footpath to help distracted pedestrians cross safely)

pedstrians on phones abc traffic lights

source: ABC

Apart from the chorus of responses that people who were hit by cars when crossing against the light while looking at their phones is Darwinian evolution in action what struck me was the insane cost at $100,000 for one intersection. Now some of that cost is for the trial process but it would be enormously expensive to role out across the city. I am always reminded of the lyrics of 21st Century Digital Boy when I see this sort of stuff happening:

‘Cause I’m a twenty-first century digital boy
I don’t know how to live but I got a lot of toys

Not because of the phones but that we look at technology solutions when simple ones will do. Now some will argue that we should not be arguing about costs when lives are at risk but the hard truth is that if we spend money on this sort of thing then money is not available to spend on other things which may more effectively save lives.

Surely the simple solution here is to paint the approaches to the intersection a bright neon yellow so people who are looking down at know they are approaching an intersection and look up at the traffic lights, which are already there! This works for bikes on bike paths approaching risk areas. I have just come back from the World Science Fair in Brisbane where we walked in to South Bank from Milton each day and the bike paths/walking areas are great:

Bikeway_&_footpath_along_Brisbane_River_in_Milton,_Qld_07

Source: Wikimedia Commons

This issue is symptomatic of a wider problem across the community. As a futurist I talk to lots of people about technology, its impacts, and its capacity to change the way we live and work. However my constant refrain is if you lead a strategy with “shiny new toy syndrome” you will almost certainly fail.

Give me $100,000 and I will fix every intersection in the CBD with a paintbrush and a can of paint

Implementation of Driverless Cars – A case for public subsidy of private transport systems

My family had a vigorous discussion over the Christmas break on driverless car technologies and the implementation timetable and pathway (yes we are like that, and if you don’t like it don’t turn up).

While we disagreed on the timelines there was general agreement that the technology is inevitable and desirable. My view was that there is a strong case for government subsidies to implement the technology which has some similar network effects as the fax machine: who buys the first fax machine?

Now, having a driverless car has some initial advantages, even if you are the only adopter. For instance if you can read/work/sleep instead of driving it is a great time saver while reducing your chances of having an accident. However the benefits of us all having driverless cars are far greater because network benefits accumulate exponentially as the number of vehicles with the technology grows.

This means that there is a significant case for a huge publicly funded effort for implementation to maximise early adoption rates. This was reinforced for me in the last week while reading several items:

The New Killer Apps: How Large Companies Can Out-Innovate Start-Ups

Audi’s traffic light assistance helps you hit every green light

The Men Who United the States: The Amazing Stories of the Explorers, Inventors and Mavericks Who Made America

In the New Killer Apps the authors describe some of the cost savings that implementation of driverless cars in the USA including:

“The American Automobile Association studied crash data in the ninety-nine largest urban areas in the United States and estimated the total accident-related costs— including medical costs, loss of productivity, legal costs, travel delays, pain, and lost quality of life— to be roughly $ 300 billion. Adjusting those numbers to cover the entire country suggests annual costs of about $ 450 billion. Now take 90 percent off these numbers. Google claims its car could save almost 30,000 lives each year on US highways, prevent nearly two million additional injuries, and reduce accident-related expenses by at least $ 400 billion a year”

Mui, Chunka; Carroll, Paul (2013-12-02). The New Killer Apps: How Large Companies Can Out-Innovate Start-Ups (pp. 19-20). Cornerloft Press. Kindle Edition.

They also go on to postulate that there would be other savings include fuel costs due to more efficient driving, and productivity improvements due to time saving. They also state that the demand for cars would be reduced by 90% due to improved utilisation of vehicles. While it is true there would be reduced demand for cars I highly doubt it would be at this level because the reduced demand theory is largely based on the fact that we only use use our cars a small percentage of the time. I no longer have a car for this reason and use Flexicar a local car sharing service. In Australia the data indicates we only use our cars on average 4% of the time and they lie idle the rest of the time. However the figure of 90% reduction in car demand is likely to be an exaggeration due to two factors:

  1. There will be a requirements for cars at peak times that will need to be filled, meaning that at other times there will still be a large capacity underutilisation.
  2. If we increase the overall capacity utilisation of our cars then they will not last as long. If we increase average car utilisation to say 20% then we will increase the mileage of our cars 5 times. In Australia that would mean moving average distance traveled to 70,000 km per year instead of the current 14,000 ( 9208.0 – Survey of Motor Vehicle Use, Australia, 12 months ended 30 June 2012 ). That means a 5 year old car would have traveled 350,000 km so changeover rates would be much higher. (there are some interesting design issues here – designing and building cars with greater durability while still allowing technology updates for instance)

There are clearly huge savings to be made in implementation of a true driverless car system if the Google assumptions are only partly correct.

In the Audi story the article states:

“Using both live and predictive data beamed into the vehicle’s navigation unit via onboard wifi, TLA doesn’t need a single camera to tell you when the light is going to change. Local data sources provide information about traffic light patterns, and the in car system uses that data and the motion of the car to predict exactly how long it’ll be until the green light goes red”

Clearly this does not work that well unless almost everyone is on the system. If drivers ahead of you are travelling too slowly for the system or brake suddenly then it would not be of much value. Also if you were travelling slowly to match your speed against when the next light would change and behind you was a trail of angry drivers trying to pass you then it could cause more problems than it solves. This magically disappears if all cars are on the system and fuel and time efficiency are gained as well as reduced accidents.

This is what I mean by network efficiencies. There must be a tipping point at which once there are enough driverless cars on the roads that benefits start to accrue more quickly and more adoption takes place. For instance if nearly all the cars on the road were driverless and communicating with each other then travel time information would be greatly improved. However the benefits accrue to different sections of the community rather than just accruing to the user, and accrue at different time frames, and there will be many self interested parties. The following are just a few examples:

  • Reduced accident rates mean a huge reduction in physical trauma and medical costs on top of the reduction in emotional trauma. This is largely saved in the government sector both in operating costs but also in continuing demand for new hospital facilities (this is also complicated by demographic changes, growth of cities, and urban intensification).
  • Individual car owners will save money in the longer term but will have the legacy costs of their current vehicles and their financing costs which may inhibit adoption and cause political backlashes. For instance if you new car is suddenly almost worthless and you have a car loan against the asset what do you do?
  • A number of sectors will miss out on income. The government will miss out on speeding fines and drink driving fines. Panel beaters, car insurers,and car manufacturers will all suffer significant revenue losses as will taxi operators and taxi licence holders.
  • If the general public came to the conclusion that large scale adoption of driverless cars was a good thing and about to happen in the next 3 years new car sales would plummet. Who would buy a new car today if it was virtually worthless in 3 years time?

Which brings me to Simon Winchester’s fine book,The Men Who United the States. In it he describes how a young Eisenhower was part of an army project to cross the USA by road in 1919 to test the capability the road system for military transport in case of war (Lt. Col. Dwight D. Eisenhower – Transcontinental Motor Convoy, 1919).Winchester claims that this experience led to Eisenhower’s long term commitment to the National road system which was later built at the cost of hundreds of billions of dollars and changed the nature of America.

There is a similar case for a large scale public investment in the adoption of driverless cars across the world. As many of the benefits accrue to government through lower costs in the health system then there is an overriding case for the government to get involved on several levels:

  • Implementation of the necessary technology systems outside of the cars themselves which link the cars to the rest of the transport system including traffic light systems.
  • A major effort to overcome any legislative barriers and risk issues, and coordinating national approaches to the problems. As an example the implementation of all this technology is likely to result in more accurate data on causes of accidents even if the overall numbers fall significantly. There will be cases where failures in the car technology causes an accident. In that case the manufacturers are likely to be held liable for the costs in that accident through the courts. At the same time the manufacturers would not accrue any of the benefits of the large reductions in accidents flowing from the technology adoption. There is a strong case for governments sharing those costs with the manufactures to reduce the costs of implementation ( I would be against indemnifying the manufacturers as they need some skin in the game).
  • Public subsidy of the system in a similar way that we subsidise private road use and public transport systems now but at least initially for a different reason. There is likely to be significant barriers to adoption of the technology which will be tied to initial costs and social attitudes. In a networked system such as large scale of adoption of driverless cars the advantages accrue much faster with higher rates of adoption. A pure business case can be made to government subsidising the system in the initial phase to significantly reduce costs and ramp up adoption rates with the payback being more rapid reduction in government costs.

Beyond all the economic arguments the human cost of road trauma is enormous and long lasting. As someone who was hit by a car 2 years ago and was lucky to escape with some serious injuries which I have mostly recovered from I have enormous sympathy for those who have not been so lucky. I was in hospital for 10 days and had 4 anesthetics and two lots of surgery but the day I left a patient in my ward was being moved to rehab after being in hospital for over 3 months, with the prospect of never walking normally again. I was able to compete in a triathlon again last Sunday in an embarrassingly slow time but at least I could finish. My thoughts go constantly to those who have not been so lucky.

My question is where are the visionary leaders of our time who will take on the huge challenge of implementing a system that can change the lives of thousands of people over the next 50 years? Who will hold the experience of meeting a severely injured car accident victim in their head in the same way Eisenhower held in his head the difficulties of crossing the USA in 1919 and set about changing the system?

Paul Higgins

Further Links:

Large-scale trial of driverless cars to begin on public roads

The world’s first large-scale test of driverless cars will involve 100 Volvos taking to the streets of Gothenburg in 2017

BMW FORECASTS CARS WILL BE HIGHLY AUTOMATED BY 2020, DRIVERLESS BY 2025.

U.K. town will build driverless podcar system

Milton Keynes, a town of more than 200,000 people, announced that it will begin a pilot program for a transit system that uses driverless, electric podcars starting in 2015.

The £65 million pilot project will use 100 podcars (that can hold two passenger each) which can be summoned by a smartphone. The initial test will have the podcars travel on a one mile route between the city’s train station and shopping centers and offices. Each ride will cost £2. The pilot will run for two years and continue if the test run is positive, possibly even spreading to other cities in the U.K.

Further links posted up by futurist P A Martin Börjesson:

New IHS Automotive study forecasts nearly 12 million yearly self-driving cars sales and almost 54 million in use on global highways by 2035

The Driverless City

 

Update:

Volvo’s first self-driving cars now being tested live on public roads in Swedish city