1 December 2022-30 June 2023
Project manager
Beatriz Cabrero-Daniel

Full title: Digital twins for Accessible Real Testing grounds for automotive Engineers and Researchers

Academic researchers in the field of autonomous driving (AD) are key in evaluating the benefits and social and environmental harms that technological advances can pose. Nevertheless, compared to AD companies, academic researchers have limited access to real-world testing platforms to validate and experiment with their ideas. Due to this, academic researchers typically turn to virtual environments or Digital Twins (virtual representations of the real world) as a replacement to climb up technology-readiness levels. Nevertheless, there is still a gap between simulations and experimental evaluations on real world AD testing grounds. For this reason, a more thorough and seamless integration between virtual assets and physical test sites is required because these tools are not always adequate to ensure the safety and reliability of AD systems.

The goal of this pre-study is to create a validation and verification (V&V) strategy that is more effective and efficient in the early stages of AD development. The objective is to close the gap between virtual environments and testing sites in the real world. A comprehensive and seamless V&V strategy for early AD development is one of the anticipated outcomes of this pre-study. Additionally, we will work to lay the foundation (technologies, methodology, partners) for the development of a comprehensive, open, and reusable tool for academic researchers. To achieve this goal, the project will focus on the integration of virtual assets and physical test sites (e.g., AstaZero AD proving grounds), using tools such as digital twins and simulation environments (e.g., CARLA).

In order to draw in industrial partners, the project will also include a review of the literature, fieldwork, and the creation of a demonstration of the suggested technologies. A literature review will be used to determine the current issues and best practices in V&V for AD, and fieldwork will be used to compile information on the requirements and experiences of researchers and industry partners. In order to share knowledge and assist the AD community, the team will formulate a solution based on this data, create a demonstration of the technologies, record the outcomes for publication in peer-reviewed journals, and to motivate a subsequent research project.

Short facts

Research area
SAFER Pre-Studies Phase 5
University of Gothenburg
Computer Vision Center
Project type
SAFER Pre-study