This chart summarizes the levels of automation for on-road vehicles, per SAE Standard J3016. Source: SAE International/J3016.

This chart summarizes the levels of automation for on-road vehicles, per SAE Standard J3016. Source: SAE International/J3016.

Autonomous vehicle technology is on its way. In 2004, the best performing autonomous car was only able to travel 7.5 miles. Now, we are seeing incredible technology take the same roads as human-driven automobiles.

The definition of what constitutes an “autonomous vehicle” can vary. The Society of Automotive Engineers (SAE) defines six levels of driving automation from “no automation” to “full automation” (see chart). Based on these varying levels, there are already vehicles with systems that provide differing levels of autonomy, including emergency braking, lane departure warnings, adaptive cruise control, etc., available in the marketplace.

The next 10 to 20 years will be shaped by progressive improvements to the technology and introductions of new features. The speed at which each of these features is adapted depends on many different factors such as cost, regulation, infrastructure changes, insurance and legal rulings on responsibility, etc. For example, the first rear camera was introduced in 2001. It was mandated on new vehicles in the United States in 2016 — 15 years from market introduction to regulated requirement.

While technology continues to change and adapt quickly, this is a real illustration of how long technologies can take to truly penetrate the market. In the recent Smithers Rapra Market Report, “The Future of Autonomous Vehicles and the Impact on Tire Markets to 2026,” forecasts for both autonomous vehicles as well as individual technologies are provided. The report finds that 12.5 million Level 3 and 4.5 million Level 4 autonomous vehicles will be on the road in 2026; however, vehicles equipped with various autonomous technologies are already on the road and growing within the luxury segment.

While Level 3-5 autonomous vehicles are not quite ready for public consumption, especially on a mass scale, they are advancing quickly enough for the automotive industry to start thinking about how to optimize tires for these self-driving cars.

The artificial intelligence systems aboard autonomous vehicles have dominated the conversation thus far, but the physical components of the vehicles are also vital to their success. The tires that are currently used on consumer and commercial vehicles are not necessarily the same tires that autonomous vehicles will require. The artificial intelligence in an autonomous vehicle, known as the controller, has far different expectations and needs than a human driver, and evaluation of vehicle components needs to be taken into account.

In the past, expert drivers evaluated tires based on ride and handling. As autonomous vehicles become more viable, evaluations will be conducted by controls system engineers, and factors such as subjective handling and steering will be of less importance. The feel of a tire on the road, or “haptic feedback,” is currently determined through vibrations in a steering wheel, but the lack of a steering wheel means this feedback must be monitored and acted upon differently. Ride will still be important, as passengers will be able to feel the impact of the road on tires, but aerodynamics, durability and rolling resistance will be more heavily emphasized than before.

Decision-making in vehicles often depends on tires. For example, grip on the road can determine whether a driver chooses to stop or swerve to avoid an oncoming obstacle. These decisions cannot be made without a proper feel for a vehicle’s tires. This is why a tire limit estimation must be determined in testing, especially for autonomous vehicles. This data allows the controller in the vehicle to make a decision based on a tire limit prediction. Additional testing for tire limits on wet and dry surfaces needs to be conducted, so the controller can adjust its actions based on the traction of the surface.

Tire sensors, which are in the concept stage, could help with traction concerns, but further testing on snow and ice would need to be completed to be sure the sensors would work in conditions that cover road markings and make driving especially difficult.

The controller needs to be aware not only of its own actions, but also of the actions of surrounding vehicles as well. When driving in a line of vehicles, it is important to detect potential problems before they cause an accident. This is usually accomplished through haptic feedback, but the lack of a steering wheel can prevent detection through normal cues. Detection and accident prevention can be achieved via vehicle-to-vehicle communication, but limiting the occurrences of tire problems in the first place is the best course of action.

Tire durability is expected to continue to be an important factor for maintaining vehicle safety. There are two main tests for determining the durability of a tire. One measure is cleat impact testing, which subjects tires to rolling under high load on a straight surface and over obstacles. This will show how a tire withstands extreme impact and weight.

The other measure of a tire is conducted through accelerated aging. Accelerated aging exposes the tire to high heat, pollutants and other factors that wear it down over time.

It is important to consider all the external elements that will affect a tire, but designing tires for autonomous vehicles will also depend on the structure of the vehicles themselves. They will likely be driven by an electric propulsion system, with a lightweight structure that is desirable for energy efficiency. Lightweight structures will put less weight on tires, but the tires will need to limit the force that is transmitted through them to the structure. If the tire is unable to absorb the punishing force created by driving on rough surfaces, the structural durability will be greatly affected.

Another factor that will influence what the tire of the future will look like is the impact of aerodynamics. A thinner tire will be more beneficial in limiting drag, but the tire will still require the same air cavity volume to achieve a suitable load capacity. This means that tires will need to be made taller to compensate. Increased tire diameter is generally better for ride, so it will not compromise the comfort of passengers.

Aside from diameter, the controller will need to be aware of other tire measurements, including cornering stiffness, braking stiffness, load transfer sensitivity, camber sensitivity and peak grip. Identifying these measurements through testing will make sure the controller is able to come up with quality initial steering and braking input. The measurements also will determine the controller’s compatibility with replacement tires.

As autonomous vehicles become standard, testing will be increasingly important in guiding the development of their components. Third party, independent laboratories are already conducting research to define the needs of these vehicles. Considering all the implications of an autonomous driving experience will better prepare manufacturers and laboratories as these vehicles move closer toward widespread availability.     ■

Dean Tener is the technical manager of Smithers Ravenna (Ohio) Laboratory, Smithers Rapra Technology Ltd.’s main center for tire testing in North America. He has been a tire researcher, designer and tester for more than 30 years, and has held positions at General Motors Corp., Honda R&D Americas Inc. and Bridgestone Americas Inc.

With more than 90 years of expertise in rubber testing, Smithers Rapra provides practical and scientific expertise, guidance and industrial know-how at every stage of tire testing, from initial ingredient evaluation to manufacture and end-use.

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