From the Lab to the Street: Solving the Challenge of Accelerating Automated Vehicle Testing

TL;DR

This paper presents an accelerated evaluation method for automated vehicle testing that significantly reduces testing miles by focusing on critical driving situations, enabling faster and more cost-effective safety assessments.

Contribution

The authors introduce a novel accelerated evaluation process that filters dangerous scenarios, reducing testing requirements by up to 100,000 times compared to traditional methods.

Findings

Reduces testing miles by a factor of 300 to 100,000.

Equivalent safety assessment achieved with 1,000 miles of testing.

Potential to significantly lower testing costs and time.

Abstract

As automated vehicles and their technology become more advanced and technically sophisticated, evaluation procedures that can measure the safety and reliability of these new driverless cars must develop far beyond existing safety tests. To get an accurate assessment in field tests, such cars would have to be driven millions or even billions of miles to arrive at an acceptable level of certainty - a time-consuming process that would cost tens of millions of dollars. Instead, researchers affiliated with the University of Michigan's Mcity connected and automated vehicle center have developed an accelerated evaluation process that eliminates the many miles of uneventful driving activity to filter out only the potentially dangerous driving situations where an automated vehicle needs to respond, creating a faster, less expensive testing program. This approach can reduce the amount of testing needed by a factor of 300 to 100,000 so that an automated vehicle driven for 1,000 test miles can yield the equivalent of 300,000 to 100 million miles of real-world driving. While more research and development needs to be done to perfect this technique, the accelerated evaluation procedure offers a ground-breaking solution for safe and efficient testing that is crucial to deploying automated vehicles.