Truck Automation: Testing and Trusting the Virtual Driver

Abstract

This chapter addresses the testing and evaluation of the virtual truck driver. While the primary focus of the discussion is on verification and validation in model-based systems engineering it also touches upon testing for certification, establishing regulations, public investment, and research and development. A reference architecture for automated driving coordinates designs at the vehicle and system levels for increased interoperability among components and improved efficiency. A model-based systems engineering approach exploits automated vehicle systems domain models as a primary means of information exchange to help manage the complexity and provide analytical support for efficient architecting, design, verification, and validation. These models support the testing and evaluation process for functional safety design and certification. Finally, demonstration pilots, operational testing, and natural use testing, combined with system design artifacts, are critical to public and regulatory acceptance of the virtual driver. Although safety must be assured, the primary challenge is how to make such assurances without relying on a human driver and vouching for the virtual driver under all allowable driving situations and conditions. This chapter provides some ideas on how all of this might come together and help bring fully automated vehicles to the market.