Tag Archives: LIDAR

Suddenly, Driverless Cars Hit Bumps

Recent tests by The Insurance Institute for Highway Safety on two key ADAS capabilities cast doubt on the efficacy of these technologies and thus on how soon full autonomy is likely to affect auto insurance premium.

Anyone insuring automobiles is paying a lot of attention to the development of ADAS (advanced driver assistance systems) and of fully autonomous vehicles.

Many of the underlying technolgies used in ADAS (e.g. cameras, radar, lidar, AI) will also be used in fully autonomous vehicles. However, the demands that a fully autonomous vehicle places on these technologies are quite different than the demands of an ADAS-equipped vehicle. ADAS-equipped vehicles will pass control to and from human drivers (or send warnings to human drivers) in various circumstances. Fully autonomous vehicles will have no hand-offs and no warnings because there are no human drivers to receive them.

The Insurance Institute for Highway Safety (IIHS) recently ran a series of tests of two key ADAS capabilities: adaptive cruise control (ACC) and active lane keeping. ACC maintains a set speed and a specified distance from a car in front of the car with ACC. Active lane keeping automatically maintains the car within its current lane.

See also: Autonomous Vehicles: Truly Imminent?  

Vehicles with ACC and active lane keeping are at Level 2 on the SAE International scale. This is a widely recognized framework demarcating degrees of autonomy — ranging from Level 0 (no automation) to Level 5 (fully autonomous).

Source: NHTSA https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety

Notice that Level 2 is a long way from Level 5.

The IIHS tested five well-regarded vehicles:

  • A 2017 BMW 5-series with “Driving Assistant Plus”
  • A 2017 Mercedes-Benz E Class with “Drive Pilot”
  • A 2018 Tesla Model 3 and a 2016 Model S with “Autopilot” (software versions 8.1 and 7.1, respectively)
  • A 2018 Volvo S90 with “Pilot Assist.”

The results of these tests were reported in IIHS and HLDI publication, Status Report (Aug. 7, 2018).

The results were not pretty.

  • In one test on a public roadway, the Mercedes was aware of a stationary vehicle in front of it but continued without reducing speed, until the human driver applied the brakes.
  • In a 180-mile test drive, the Tesla Model 3 slowed without an appropriate cause 12 times (including seven instances of tree shadows on the road).
  • In testing active lane keeping on curves; the BMW, the Mercedes and the Volvo were unable to stay in their lane without the driver providing steering assistance.
  • The vehicles’ active lane keeping capability was also tested when they reached the top of hills. At the top, some cars’ technologies essentially lost sight of the lane markings on the road. The BMW failed to stay in its proper lane (without driver intervention) in all 14 tests. The Volvo stayed in the lane in nine of 16 tests. The Tesla Model S swerved right and left as it attempted to locate the appropriate lane. Sometimes it also entered an adjacent lane or drove onto the shoulder.

There is evidence that ADAS technologies do reduce accidents and insured losses—here and here.

See also: Autonomous Vehicles: ‘The Trolley Problem’  

However, the real world test results of Level 2 technology in these five highly regarded models were certainly disappointing. Level 2 autonomy requires the driver to remain engaged and constantly monitor the environment. The key words are “remain engaged.” People, while driving, often do many things other than remaining engaged.


The shared responsibility between less-than-perfect humans and less-than-perfect technologies of Level 2 implies that either the technologies have to become intrinsically better — or they must find ways to compensate for imperfect humans.

As mentioned, you cannot make a straight-line projection of elapsed time from the current state of Level 2 ADAS technology to the arrival of ready-for-prime-time Level 5 fully autonomous technology.

Geospatial Solutions: A Vital Enabler

At SMA we have long been tracking the rise of smart things and their implications for the insurance industry. A variety of emerging technologies has been rapidly advancing to make everything imaginable smart. But participating in the ESRI User Conference in San Diego this year has driven home one key point: Geospatial solutions will have a critical role in making sense of all those smart things. The notion of a connected world is not an academic pursuit – possibilities to ponder about sometime in the future. It is a here-and-now issue affecting every industry, including insurance.

See also: Insurance and the Internet of Things  

The Internet of Things is already upon us. Sensors and embedded chips are present in buildings, infrastructure, agricultural settings, vehicles, devices in the home, medical facilities and government operations. Add to that billions of mobile phones and the capability to track location, movement and environmental conditions, and the result is many connections and massive amounts of data already measuring, monitoring and acting on the world around us. Predictions about the adoption of connected things vary widely, but, by any measure, the connection points and the data volumes will continue to increase exponentially. The problem, then, is not deploying smart things or collecting data from the smart things. The fundamental problem is the ability to combine and analyze data to gain some insights. In some cases, those insights might trigger decisions with global implications, solving some of humanities thorniest problems. In other cases, the insights might lead to a small action that improves the life of one individual.

Enter geospatial solutions. Analytics and big data, in general, have essential roles to play in understanding the data generated in the connected world. But visualizing that data in a way that tells a story and reveals insights is the province of geospatial solutions, an area that has much to contribute to the connected world. Unfortunately, old impressions of geographic information systems (GIS) linger, especially in insurance. Most insurers have GIS solutions to do geospatial analysis, but they tend to be used by a small number of specialists for very specific applications. Today, the advances in 3D; animation; digital capture through drones, satellites, or LiDAR; and other technologies offer new opportunities. Tools for spatiotemporal analysis (understanding changes over time), crowdsourcing of real-time data and cloud-based collaboration platforms for maps and apps have elevated the discipline and provided government and industry with the potential to gain a deep understanding of the world to aid in addressing both new and old problems.

See also: How Connected Will Connected World Be?

Many insurers are considering the implications of the connected world and how it will affect their particular lines of business. Connected cars, smart homes, the quantified self, smart cities, autonomous commercial fleets and many other new areas create both threats and opportunities for insurers. Evaluating how geospatial capabilities can be harnessed to gain a better understanding of these emerging areas should be part of every insurer’s strategy and planning initiatives.

Plunging Costs for Autonomous Vehicles

Personal auto liability is U.S. property/casualty insurers’ largest line of business, and personal auto insurers face a long and daunting list of challenges. But many of those challenges will merely alter competitive dynamics within auto insurance markets, enabling the best insurers to gain market share at the expense of weaker competitors (e.g., those insurers that master telematics and the associated big data issues can look forward to stealing share from those that don’t.)

Unlike the majority of other challenges, the advent of autonomous vehicles threatens all personal auto insurers, because liability will shift from vehicle owners to auto manufacturers or those who provide the systems and software that enable autonomous driving. Simply put, the market for personal auto liability insurance is likely to shrink dramatically at some point, with a number of auto manufacturers already committing to accept liability when their autonomous vehicles are at fault in accidents.

None of this would be of any consequence if the cost of autonomous vehicles placed them out of reach of the typical consumer. But technology costs for autonomous vehicles are plunging. According to a recent article in the Washington Post, the cost of LIDAR (the “eyes” for autonomous vehicles) is poised to drop from $75,000 to a mere $500 or less. (See here)

Yes, it will be years before autonomous vehicles constitute the lion’s share of the vehicles on the road, and today’s personal auto liability insurers have some good years ahead of them. But change is coming, and, as Sun Tsu said, all battles are won or lost before they are ever fought. Is it really too soon for personal auto liability insurers to begin positioning for the world just now coming in to focus on long-range scanners?