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Lux Research: self-driving cars will lead to a $87B opportunity in 2030, but fall short of full Level 4 autonomy; software leads
12 May 2014
|Software will capture the largest segment of the autonomous car market opportunity, according to Lux. Click to enlarge.|
In a new report—“Set Autopilot for Profits: Capitalizing on the $87 Billion Self-Driving Car Opportunity”—Lux Research projects that Level 2 self-driving will increase from about 3% of cars sold globally today to 57% in 2020, and 92% in 2030.
However, the firm also concludes, by that same year only 8% of new cars sold will attain the reasonable capabilities of Level 3 autonomy, and no Level 4 fully autonomous cars will be available. By 2030 automakers will be able to capture profits of about $9.3 billion from the emergence of autonomous vehicles, making this new technology an alluring proposition. Level 3 autonomy will be a premium option, opening the door to business model innovation if automakers hope to deploy it beyond some high-end vehicles.
The US National Highway Traffic Safety Administration (NHTSA) defines vehicle automation as having five levels:
Level 0: No Automation. The driver is in complete and sole control of the primary vehicle controls—brake, steering, throttle, and motive power—at all times.
Level 1: Function-specific Automation. Automation at this level involves one or more specific control functions. Examples include electronic stability control or pre-charged brakes, where the vehicle automatically assists with braking to enable the driver to regain control of the vehicle or stop faster than possible by acting alone.
Level 2: Combined Function Automation. This level involves automation of at least two primary control functions designed to work in unison to relieve the driver of control of those functions. An example of combined functions enabling a Level 2 system is adaptive cruise control in combination with lane centering.
Level 3: Limited Self-Driving Automation. Vehicles at this level of automation enable the driver to cede full control of all safety-critical functions under certain traffic or environmental conditions and in those conditions to rely heavily on the vehicle to monitor for changes in those conditions requiring transition back to driver control. The driver is expected to be available for occasional control, but with sufficiently comfortable transition time. The Google car is an example of limited self-driving automation.
Level 4: Full Self-Driving Automation. The vehicle is designed to perform all safety-critical driving functions and monitor roadway conditions for an entire trip. Such a design anticipates that the driver will provide destination or navigation input, but is not expected to be available for control at any time during the trip. This includes both occupied and unoccupied vehicles.
Lux notes that automakers and technology developers are closer than ever to bringing self-driving cars to market, with basic “Level 2” autonomous behavior already coming to market, in the form of relatively modest self-driving features such as adaptive cruise control, lane departure warning, and collision avoidance braking.
With these initial steps, automakers are already on the road to some level of autonomy, but costs remain high in many cases. It is the higher levels of autonomy that are grabbing the hype right now, Lux says
Demonstrations of autonomous cars by Google and Mercedes-Benz are technically impressive, but still depend on high-resolution special maps, are limited to certain routes and weather conditions, and need a trained professional driver behind the wheel. These “Level 3” cars are at the forefront today.
The future awaits a demonstrated truly autonomous “Level 4” car, wherein fully autonomous driving is enabled in any environment and in all circumstances, without any driver input.
Self-driving technology will create a new opportunity for the automotive value chain, and bringing in outsiders to join incumbents looking to capitalize on a new market, Lux proposes. Software will be the biggest autonomous vehicle value chain winner, with $25 billion in revenues in 2030, a 28% CAGR.
This software market will be a differentiated and high-stakes field, ripe for new partnerships beyond the conventional automotive value chain. Optical cameras and radar sensors will amount to $8.7-billion and $5.9-billion opportunities in 2020, respectively, due to Level 2 cars, Lux forecasts.
Because of the increasing complex processing requirements of Level 3 autonomy, in 2030 computers will be the biggest hardware opportunity on-board autonomous cars, amounting to a $13-billion opportunity.
Prospective suppliers in the value chain should anticipate significant changes both inside and outside the vehicle over time, inevitably creating opportunities for new entrants. Lux suggests.
Inside the vehicle, decreased driver involvement will require high-end automakers to find new ways to differentiate amongst each other, based less on outright performance and sportiness, and more on luxury, technology, and the human-machine interface.
In the foreseeable future, vehicles will be able to handle monotonous tasks. For example, to find a parking spot a driver would be able to get out of their car in front of their destination, and instruct the car to park itself nearby. The car would then safely proceed at low speed around the neighborhood, looking for available parking spots. Infrastructure developers can enable this use case through deploying parking sensors and associated communication devices to detect when spots become available.
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