Verification and Validation Methods for Decision-Making and Planning of Automated Vehicles: A Review

Abstract

Verification and validation (V&V) hold a significant position in the research and development of automated vehicles (AVs). Current literature indicates that different V&V techniques have been implemented in the decision-making and planning (DMP) system to improve AVs' safety, comfort, and energy optimization. This paper aims to review a range of different V&V approaches for the DMP system of AVs and divides these approaches into three distinct categories: scenario-based testing, fault injection testing, and formal verification. Further, scenario-based testing is categorized into fundamental and advanced approaches based on the interaction between road users in generated scenarios. In this paper, six criteria are proposed to compare and evaluate the characteristics of V&V approaches, which could help researchers gain insight into the benefits and limitations of the reviewed approaches and assist with approach choices. Next, the DMP system is broken down into a hierarchy of modules, and the functional requirements of each module are deduced. The suitable approaches are matched to verify and validate each module aiming at their different functional requirements. Finally, the current challenges and future research directions are concluded.