Driving Safety Performance Metrics for ADS-Equipped Vehicles

What does it mean for an automated vehicle to drive safely? How does it compare to human-driven vehicles? In this three-phase, safety metrics project, IAM aims to define a concise set of metrics to inform an AV driving safety performance assessment. Through IAM’s test network, the team can test the metrics in a real-world intersection.

Phase I: August 2019 - April 2020

The first phases will include the design and validation of metric definitions, a data capture system and a detection and tracking algorithm. The definitions are a mix of existing, adapted and novel metrics. The data capture system is supported by IAM’s test network site operated by the Maricopa County Department of Transportation in Anthem, Arizona. The intersection’s cameras are infused with AI to sense objects, informing detection and tracking algorithms.

McDOT SMARTDrive Testbed

This compilation of footage from the IAM Test Network site in Anthem, Arizona features how the IAM team uses MCDOT intersection cameras to test and measure its safety assessment metrics.

Driving Safety Performance Assessment Metrics for ADS-equipped Vehicles

IAM published driving safety performance metrics and methods identified in this project’s first phase in the SAE International Journal.

Phase II: May 2020 - December 2020

In this second phase, IAM members will refine and evaluate the safety metrics, as well as the detection and tracking algorithm defined in Phase I. The team will also research assessment methodologies to analyze the driving safety performance of an individual vehicle and the vehicle’s impact on the overall traffic network.

Phase III: January 2021 - December 2022

The third and final phase will establish an assessment network to serve as a test bed for a statewide system deployment of the driving safety performance metrics.

Project Experts

Jeffrey Wishart
Ph.D. Manager Vehicle Engineering, Exponent
Adjunct Professor, Automotive Systems, Arizona State University
Yezhou Yang
Assistant Professor, School of Computing, Informatics and Decision Systems Engineering, Arizona State University
More IAM Experts