Abstract
Autonomous driving has drawn great interest from both industry and academia. Due to some serious consequences such as loss of life caused by autonomous vehicles, assurance certification has been proposed in the automotive industry to ensure safe self-adaptive behaviors at run-time in autonomous cars. Central to assurance certification are assurance cases that provide compelling, comprehensive, and valid argument structures showing a system is safe in a given environment. However, many existing approaches generate assurance cases as a by-product of a system. In this paper, we will present a novel development paradigm that employs assurance cases to guide an autonomous vehicle to operate correctly and safely at run-time. Specifically, we consider an F1TENTH racing car as an example to illustrate how the assurance case driven paradigm can guide the vehicle to achieve safe and reliable self-adaptive behavior at run-time.