Objectives and Topics

One critical bottleneck to improving the safety performance of connected and automated vehicles (CAVs) is the difficulty of testing and evaluating safety performance. To date, there are no consensus or standard procedures on how to test and evaluate CAVs. During the past few years, although the problem of CAV testing has been investigated extensively by various CAV developers, government agencies, professional organizations, as well as academic institutions, the theories, methods, and best practices to support such testing and evaluation are still lacking.

This workshop focuses on sharing the state-of-the-art theories, methods, algorithms, metrics, datasets, simulations, and field implementation of safety performance testing and evaluation of CAVs, and identifies challenges as well as research needs, aiming to encourage cross-disciplinary cooperation and facilitate the development and deployment of CAVs. The specific topics of interest are listed below:

• Methodological frameworks for safety verification and validation

• Advanced data engines for large-scale, high-resolution, and rich-context data collection

• Naturalistic driving environment modeling with statistical realism

• Testing scenario generation for comprehensive behavior competency evaluation

• Testing environment generation for trip-level safety performance evaluation

• Adversarial attacks on vehicle perception, decision, communication, and control

• Safety assessment models development and evaluation

• Infrastructure-assisted CAV technologies testing and evaluation

• Advanced simulation of safety performance testing and evaluation

• Advanced field implementation of safety performance testing and evaluation