2. Educating and incentivizing customers
Humans are not particularly safe drivers. 90% of accidents are caused by human error. Cars currently reducing reliance on human attentiveness with collision warning systems and automatic braking features have been shown to reduce collisions by up to 15%, according to a study by the Insurance Institute for Highway Safety.
The premise of driverless vehicles is that human driving is an inconvenience, an inefficiency and even a hazard, which should be cut out of the process of getting someone from A to B.
But this is only part of the story. Driving also offers the driver a sense of control over a potentially unsafe environment.
As a result, even if relinquishing control over a car to a machine is safer, it can feel unsafe, and this is a genuine barrier to driverless cars becoming a reality. Indeed, a recent EY survey found that 54% of drivers were worried about the prospect of traveling in a driverless car.
Like with any new technology, this discomfort is likely to subside once people experience it for themselves. This means that both dealers and automakers must play a role in educating and incentivizing prospective customers on autonomous features and technology - giving them a chance to try before they buy.
Driverless taxis are likely to be a vital transitional step to driverless car uptake – proving the viability of the technology in the real world, without people having to commit to their own vehicle. Driverless taxis were rolled out in Singapore in 2016, and are planned for deployment in Japan in time for the 2020 Tokyo Olympics.
3. Incremental improvement
A proven tactic for getting consumers accustomed to new technologies is to introduce it incrementally. In the case of car automation, the process has already started. Cars now help us park: some with sensors on the bumpers to detect how far you are from an obstacle and which beep to let you know. Other cars include graphical displays for the same purpose. Vehicles also employ reversing cameras, some of which show a 360-degree image.
In April 2014, the National Highway Traffic Safety Administration proposed that all new light vehicles have ‘rear-view visibility systems’, in effect, requiring backup cameras. If the proposal is adopted, these cameras may end up being mandatory in some regions.
Then there is parking assist. These systems work out whether or not a parking space is big enough for the car, and if so, help the driver steer the car into the space. The driver just controls the speed.
Many vehicles can park themselves too: parallel parking and parking in a bay, for example. Forward collision systems and automatic braking are all part of a trend of passing control from driver to car.
The shift required by manufacturers and those marketing driverless vehicles is to make the cars part of a spectrum of incremental improvements as much as possible.
4. How much human do driverless cars need?
Even after persuading people to trust driverless technology, there are additional challenges – not least of which is the mismatch in driving styles between human and self-driving cars. This will be the case as long as driverless and human-controlled vehicles share roads.
Driverless cars drive like computers programmed to follow the letter of the law. But despite that, a 2015 study that investigated a small sample of driverless cars found that they had a higher crash rate per million miles traveled than conventional cars.
And it wasn’t because they were unsafe. Quite the opposite: almost all the accidents in the study were caused by human drivers unaccustomed to responding to a robotic – ultra-safe – driving style.
The solution lies in convergence. Humans may have to adapt their driving style. But there is also a strong argument that driverless vehicles should be programmed to mimic humans, to better adapt to their irrational behavior – but not to repeat bad habits.
Learning systems could also mean individual cars can tailor their driving styles to best accommodate the driving styles that the occupant feels most comfortable with. “The processing systems used for autonomous vehicles are expected to rely on advances in ‘machine learning’ to better mimic the human brain’s ability to deal with unique situations,” explains Randy Miller, EY Global Automotive & Transportation Leader. “The software of a fully autonomous vehicle will need to be adaptive, intuitive and self-learning, like a chess supercomputer that learns from its opponents’ moves."
The road to a driverless world: the impact on insurance
These challenges – of mimicking human driving, learning to copy individual driving styles and educating drivers to get comfortable with self-driving cars – are only the tip of the iceberg. While the process of compromise that must be reached between human driving and driverless travel is well underway within the automotive industry, there are other considerations that need to be addressed from the outside.
Legal, regulatory and insurance issues still surround the deployment of driverless cars, and many of these could take years to fully tackle. The insurance industry has to be at the forefront of wrestling with these practical and theoretical considerations.
New liability challenges
How much risk can be transferred from the individual driver to the manufacturer – and who counts as the “driver”? It’s likely that most AVs will include both manual and computer control – which could lead to two types of insurance.
Longer term, autonomous vehicles should make driving safer – resulting in the need for less insurance. But for now, there are more elements to consider and insurers need to prepare.
Insurers will need to determine whether the human behind the wheel or the computer behind the dashboard was in control in an accident, much like how black boxes record the actions of pilots in planes. Manufacturers must work more closely with insurers – especially around data sharing – and may become insurers themselves to simplify the process.
Future legislation could force manufacturers to insure fleets of cars, rather than individuals. Shifting from personal motor to product liability insurance introduces risks related to system failures. Standard policy wordings do not cover such issues, so these potential risks may have to be insured elsewhere.
Broader insurance issues
New risks will require changes to traditional insurance industry business models. Some of the other implications include:
- In most countries, personal vehicle insurance is compulsory, keeping premiums artificially low. In an AV world, personal insurance may become voluntary – similar to mobile phones, bicycles or laptops. This could lead to pricing adjustments for individuals who insure their vehicles.
- If vehicle crashes decline when AVs are in automated driving mode, premiums may rise for individuals driving in manual mode. This might price some individuals out of the market, particularly those less able to afford them.
- Cyber risk offers the potential for malicious hacking of systems through which driverless cars receive instructions. Disrupting internet connectivity could wreak havoc or leakage of private user information. AV service providers and manufacturers must deliver robust cybersecurity processes to reassure customers.
- Driverless cars are far more complex and repair costs could increase significantly. Who is liable for losses if an AV is serviced incorrectly, or not properly maintained by its user?
As with any new technology that sees mass adoption, the true implications of driverless vehicles may not be immediately apparent.
Businesses must keep on top of shifting regulations while managing their insurance liability risks. For insurers, the challenge lies in making the most of vast volumes of data generated by this new technology. This means improving data analytics to strengthen pricing and underwriting, and recognizing that existing customer claims databases are less relevant.
“Just as technology has enabled other industries to redefine themselves, the insurance industry will need to create a business model that will help in the transition as more automated features – and ultimately fully autonomous vehicles – are on the road,” says Kristin Schondorf, EY Global Automotive & Transportation Mobility Leader. “There will be exciting new opportunities for those companies that recognize and create these new business prospects.”
As driverless cars approach reality, many potential applications and approaches remain unexplored, away from the buzz of the public highway. Autonomous vehicles could also turn industrial and agricultural supply chains and production into more efficient, fully automated systems with minimal need for human intervention. But what happens to the surplus manpower, freed up from driving for profit or pleasure, will present its own new set of challenges.
Only one thing is abundantly clear, says Miller: “As they move closer to reality, autonomous vehicles will not only play an integral role in the urban mobility ecosystem, but they will also support a number of new business models too.”
While the work is underway to remove human error from our roads once and for all, there are several knock-on effects that go beyond the highway that will need just as much attention as the technology before we will see vehicles becoming truly driverless.
Driverless cars aim to eliminate human error on the roads, but key factors need to be assessed before they can create true value for humans.