Keep Your Eyes Off the Road
The emergence of autonomous vehicle technologies and its impacts on traditional insurance
As far back as we can remember, the story of the automobile tells us accidents are unavoidable. Accidents happen, the saying goes—that’s why they are called accidents.
The world’s first production automobile propelled by an internal combustion engine, the Benz Patent Motor Wagon, was awarded a German patent in 1886. One year prior to obtaining the patent, the vehicle had already been involved in an automobile accident when it crashed into a brick wall during a public test.
In 1869, a woman in Ireland was riding as a passenger in an experimental steam car when she was thrown from the vehicle and fell under the wheels as it rounded a bend. This is believed to be the first recorded automobile death, despite the fact that the “first automobile” had yet to be invented. Decades later in 1891, the first known automobile accident in U.S. history occurred in Ohio City, Ohio, 17 years before the introduction of the Ford Model T.
The inevitability of automobile accidents has grown U.S. automobile insurance into a multi-billion-dollar industry—in 2015, auto insurers collected nearly $231 billion in policy premiums, according to figures shared by the National Association of Insurance Commissioners (NAIC).
According to the National Highway Traffic Safety Administration (NHTSA), 94 percent of accidents are caused by human error. By 2040, covered losses on personal lines are estimated to decrease to 40 percent of current annual costs due to the rise of autonomous vehicles.
No longer will the attentive driver be the safest driver on the road. We will be the first generation to tell our children they don’t have to be in control of the automobile at all times. Are you ready for that? The answer might be yes if you’ve ever had to add a teenage driver to your policy. It is expected that the premiums collected annually by auto insurers will decrease sharply to stay competitive as costs decrease from the elimination of the human element.
A fully autonomous vehicle is one that integrates several technological systems that work together to perform all aspects of the dynamic driving task under all roadway and environmental conditions. Several of those technological systems, which were not available until recently, are being implemented by auto manufacturers and marketed as standard safety features. The technological systems include the following.
Lane Departure Warning Systems. A technology that can help prevent crashes by delivering auditory, visual, or haptic alerts or feedback when it detects an unintentional drift of the vehicle out of its travel lane. Lane departure accounts for 40 percent of single vehicle fatal crashes.
Lane Keeping Support. These systems use information provided by sensors in a lane departure warning system to determine whether a vehicle is about to move out of its lane of travel. If so, the system activates by correcting the steering or braking, or by accelerating one or more of the wheels, to return the vehicle back to its intended lane of travel.
Automatic Emergency Braking. These systems detect an impending forward crash with another vehicle in time to avoid or mitigate the crash. These systems first alert the driver to take corrective action to avoid the crash. If the driver’s response is insufficient, then the system may automatically apply the brakes to prevent or reduce the severity of a crash.
Pedestrian Automatic Emergency Braking. This is an emerging safety technology that provides automatic braking when pedestrians are in front of the vehicle and the driver has not acted to avoid a crash.
Forward Collision Warning System. An advanced safety technology that monitors a vehicle’s speed, the speed of the vehicle in front of it, and the distance between the vehicles. If the vehicles get too close due to the speed of the rear vehicle, the system will warn the driver of an impending crash.
Rear-View Cameras. Also known as a backup camera, this technology helps prevent back-over crashes by providing a live view of the area behind the vehicle. This technology is required in all new vehicles by May 2018.
Blind-Spot Detection. These systems warn drivers with audio or visual warnings if there are vehicles in adjacent lanes that the driver may not see.
Adaptive Cruise Control. Similar to forward collision warning systems, this feature will automatically reduce speed and provide braking while cruise control is engaged if the vehicle gets too close to the vehicle ahead.
Drowsy Driver Detection. This system utilizes a camera focused on the driver. Prompts will notify the driver to focus on the road should the system determine that the driver is not paying attention.
These safety systems are not possible without sensors that allow the vehicle to be aware of its surroundings. Manufacturers are choosing between two technologies for the purposes of object identification and mapping. The first is light detection and ranging—better known as lidar—which is a technology that measures distance using laser light. The technology can scan more than 100 meters in all directions, generating a precise 3-D map of the car’s surroundings. This information is then used by the vehicle to make intelligent decisions about what to do next.
The second, radio detection and ranging—more commonly known as radar—is a sensor system that uses radio waves to determine the velocity, range, and angle of objects. Radar is computationally lighter than a camera and uses far less data than lidar. While less angularly accurate than lidar, radar can work in every condition and can even use reflection to see behind obstacles.
The problem with lidar systems is that they generate a large amount of data and are still quite expensive for manufacturers to cheaply implement. Tesla, probably the best known semi-autonomous vehicle on the road today, uses a radar-based system. Meanwhile, General Motors has announced that its “Super Cruise” feature, which will initially be included in its Cadillac brand, will utilize a lidar-mapped system.
Both radar- and lidar-based systems require cameras for classification and texture interpretation. While fairly cheap and widely available, cameras use massive amounts of data, which makes processing a computationally intense and algorithmically complex job. However, the ability of cameras to see color makes them the best option for scene interpretation.
As manufacturers continue to integrate technologies with more advanced sensors and faster processors, we come closer to seeing fully autonomous vehicles outnumbering traditional vehicles. In anticipation of that day, the National Highway Traffic Safety Administration (NHTSA) has adopted the SAE levels of automation. The levels are based on who does what, when.
• Level 0 (No Automation): The full-time performance by the human driver of all aspects of the dynamic driving task, even when enhanced by warning or intervention systems.
• Level 1 (Driver Assistance): The driving mode-specific execution by a driver assistance system of either steering or acceleration/deceleration using information about the driving environment and with the expectation that the human driver performs all remaining aspects of the dynamic driving task.
• Level 2 (Partial Automation): The driving mode-specific execution by one or more driver assistance system of both steering and acceleration/deceleration using information about the driving environment and with the expectation that the human driver performs all remaining aspects of the dynamic driving task.
• Level 3 (Conditional Automation): The driving mode-specific performance by an automated driving system of all aspects of the dynamic driving task with the expectation that the human driver will respond appropriately to a request to intervene.
• Level 4 (High Automation): The driving mode-specific performance by an automated driving system of all aspects of the dynamic driving task, even if a human driver does not respond appropriately to a request to intervene (the automated system can operate only in certain environments and under certain conditions).
• Level 5 (Full Automation): The full-time performance by an automated driving system of all aspects of the dynamic driving task under all roadway and environmental conditions that can be managed by a human driver.
In addition to planning for a future of situationally aware vehicles, NHTSA has been researching a future in which vehicles speak to each other, as well. Vehicle-to-vehicle communication (V2V) is a crash-avoidance technology that relies on communication between nearby vehicles to potentially warn drivers about dangerous situations that could lead to a crash.
V2V uses dedicated short-range radio communication to exchange messages containing vehicle information such as speed, heading, and braking status, as well as information obtained from sensors, to advise of other vehicles and objects on the roadway. V2V devices use this information from other vehicles to determine if a warning to the vehicle’s driver is needed to prevent a vehicle crash. NHTSA estimates V2V will prevent or mitigate 80 percent of crashes among unimpaired drivers.
V2V is considered a valuable addition to autonomous vehicles due to the limitations of sensor technologies with respect to detection distance and field of view. Prevalent crashes, such as intersection crashes, would not be reduced by current sensing safety systems. NHTSA believes V2V-based safety systems can address the detection distance and field of view issues inherent in the vehicle-resident safety systems.
NHTSA estimates that a proposed rule requiring certain cars, trucks, and buses to be equipped with V2V communication technology that sends and receives basic safety messages could prevent up to 615,000 crashes and save as many as 1,366 lives annually. Additionally, $10.6 billion in savings would be realized from decreased vehicle property damage losses. NHTSA estimates full V2V adoption could require 43 years from rule introduction.
The transition to a world of fully autonomous vehicles that also communicate with each other to create safer roadways has started, but there is a long way to go. The most advanced commercially available vehicles on the road today are just entering Level 3 automation on the NHTSA/SAE scale.
The transition is expected to lead to reduced claims frequency and lower annual losses. As a result, competition will drive the traditional insurance industry to offer lower premiums. Theories of liability will shift from traditional negligence to product liability. To be sure, insurers are preparing for this shift and should be considering providing additional lines of coverage to account for lost revenue.
While no one believes that our roads will be free from accidents, the certainty of accidents that helped create a multi-billion-dollar industry is going to dramatically decrease, and insurers will need to be prepared. All we have to do is ignore the advice our parents gave us and not pay so much attention to the road.