The key to understanding the cost improvements of TaaS vehicles is understanding vehicle degradation, which affects both maintenance costs and vehicle lifetime (in miles). The main causes of vehicle degradation are all vastly reduced in an autonomous electric vehicle (A-EV) due to:
- Reduced Friction - 20 moving parts in an EV compared to 2,000 moving parts in a gasoline vehicle leads to far less friction and means there is less that can go wrong. EVs are essentially batteries on wheels.
- Reduced heat and vibration - the simplicity of the powertrain dramatically reduces heat and vibration in A-EVs, which reduces wear and tear on the vehicle.
- Reduced time-based degradation - under the TaaS model, cars no longer sit idle for 96% of the time (as they do in private ownership), but are instead in operation 10 times more, covering 100,000 miles per year instead of 10,000. This reduces degradation like corrosion or partial battery degradation (driven by car lifetime in YEARS).
Longer vehicle lifetimes and fewer maintenance costs
Vehicles will last much longer in terms of vehicle miles (500,000-1M miles) and cost just a fraction to repair (conservatively estimated at 20% of gasoline vehicle repair costs).
Only TaaS will benefit from the increased lifetimes. In individual ownership, a 1 million mile EV would last 100 years. Given the increasing pace of fleet turnover, vehicles will be obsolete quickly in the individual ownership model, and so depreciation (or lease) payments will still be based on residual value calculations.
But in TaaS, the capacity to travel 1 million miles combined with fleet ownership, no secondary market, and high utilization means that depreciation will be calculated by spreading the costs over the lifetime miles evenly, leading to a dramatic saving: each mile travelled by TaaS will cost just 1/1,000,000th of the upfront cost.
The upfront cost of an EV compared to a gasoline vehicle is the key focus of commentators, but it has far less impact on cost per mile than the improvement in lifetime miles.
Further savings will come from:
· Insurance costs: 90% reduction as AI will be dramatically safer than human drivers and cars will be impossible to steal
· Fuel: 70% reduction as electricity is cheaper than gasoline per unit of energy and EV motors are far more efficient than combustion engines
· Finance costs: 90% cheaper per mile as the fixed annual interest cost is spread over 10 times as many miles.
Changing incentives will increase these savings further
Vehicle manufacturers will compete on cost per mile (rather than upfront cost of purchase or other attributes like performance, comfort, appearance etc.). Currently, manufacturers make money from selling vehicles and maintaining them, creating incentives towards planned obsolescence. In the future, they will compete to maximise vehicle lifetimes and minimise operating costs. Further gains are possible as vehicles are re-designed to strip out unnecessary accessories and platforms are created that can be easily maintained with all parts capable of simple replacement when required. Labour in maintenance will be minimised through automation.
This results in vastly lower cost for transportation
Put together these changes will deliver transport by TaaS or TaaS Pool at a cost-per-mile that is four-to-10x cheaper than purchasing a new car AND two-to-four times cheaper operating (maintenance, fuel and insurance) an existing vehicle.
This will disrupt both new car sales AND the existing fleet of vehicles
– leading to a much faster transition than is currently perceived by mainstream analysis, which focuses not on the disruption of car ownership but only the technology disruption of individually owned EVs replacing one-for-one ICE vehicles when they are purchased new – which leads to a multi-decadal replacement of the existing vehicle fleet. Existing owners will abandon their vehicles leading to the stranding of up to 100m gasoline and EV vehicles in the US.
There is a road to free transport
This decrease in cost opens the way to free transportation (initially in the TaaS Pool model) where the low cost of transport (1-2c per mile) is covered by other revenue sources – from advertising, data monetization, entertainment or product sales. Other revenue could come from grid stabilization and demand management, corporate sponsorship of fleets or government subsidy to provide access to transport. Indeed the success of the winners might be defined by their ability to exploit these new opportunities more than their ability to produce vehicles.
All things being equal, one would expect that the scale of this decrease in cost would lead to far faster adoption than is currently expected. However, “all else” is NOT equal. Once adoption of TaaS begins, ‘systems dynamics’ will drive it ever faster...
Speed and Extent of Adoption
So given this new economic analysis – how quickly will the disruption occur? To understand this we need to consider the drivers of decisions and actions by consumers (demand), businesses (supply) and policy makers (the regulatory environment). We also need to understand the non-linear impact of the accelerators and brakes that occur in technology disruptions – these are the feedback loops that make TaaS ever cheaper and better to use over time and individually owned ICE vehicles more expensive and harder to use. These are the network effects, tipping points and market forces that change dynamically over time