DigiCAV project: Exploring a TestDriven Approach in the Development of Connected and Autonomous Vehicles Testing u0026 validation of highlevel autonomy features requires large amounts of test data, which conventionally is achieved by accumulating miles on the road and dedicated proving grounds. This places an extreme burden not only on original equipment manufacturers (OEMs) of connected and autonomous vehicles (CAVs), but also on Tier 1 suppliers of CAV components, both in terms of cost and delivery time. To this end, multiple simulation platforms and techniques have emerged, such as hardwareintheloop testing methods, while the concept of cosimulation is gaining popularity as a more comprehensive solution for testing and validating CAVs. The aim of the DigiCAV project is to explore the feasibility of a cosimulation platform adopting a testdriven development approach for CAVs, by enabling a seamless testing and validation process across all stages of development, supporting a wide range of testing from modelintheloop of a CAV component all the way to vehicleintheloop of a fully assembled vehicle on HORIBA MIRAu0027s dedicated CAV proving ground test facilities. Furthermore, emphasis will be put on quality aspects such as testing accuracy, usability and protection of intellectual property rights. This paper introduces the DigiCAV project and disseminates results from its first deliverable focusing on capturing user requirements for the proposed simulation platform.

Empirical Testing of Automotive CyberPhysical Systems with Credible SoftwareintheLoop Environments Automotive cyberphysical systems are constantly increasing in complexity, especially due to innovations like sophisticated advanced driver assistance features. The increase in system complexity, in turn, gives rise to complex distributed software which creates challenges for verification. Frontloading tests that are regularly performed in prototype vehicles or HardwareintheLoop (HiL) to simulation and SoftwareintheLoop (SiL) environments can be used to validate design decisions and to significantly reduce overall development costs. Novel Automated Driving features, and the Open Context problem, however, move the challenge from the statetotheart to a knowledge problem (knowwhat instead of knowhow). The ISOPAS 21448:2019 for Safety of the Intended Functionality (SOTIF) acknowledges this change but no guidance is provided to the industry to making verification processes ready for operating vehicles in an Open Context environment that may require functional changes during the useful life of a vehicle. Since verification with HiL or vehicles will be all but impractical, in this paper we provide insights into the design of credible SiL environments that address functional and nonfunctional verification and validation concerns of software related automotive system in a continuous lifecycle. With the help of a usecase we demonstrate the significance of the novel approach compared to traditional automotive industry methods.