4-CAD

Scenario-based tool chain for virtual verification and validation of automotive radar

The 4-CAD project aims to improve the safety and reliability of connected and automated driving by developing testing methods for vehicle and traffic systems. The research focuses particularly on the comprehensive verification and validation (VV) of radio technologies, which play a central role in environmental sensing and communication. As higher levels of automation are pursued, these technologies must be tested in a variety of traffic scenarios and radio network configurations, posing a challenge for existing VV processes.

The project comprises two sub-projects:

Sub-project 1: Over-the-Air (OTA) Multistage Test Environment for Dynamic V2X Scenarios
This sub-project investigates how the current OTA testing of V2X technologies can be adapted to future requirements. The goal is to link a system-level simulator for in-vehicle ad-hoc networks with an OTA test facility. Special attention is given to the modeling and emulation of the radio channel under typical dynamic conditions resulting from traffic situations.

Sub-project 2: Scenario-Based Toolchain for Virtual Verification and Validation of Automotive Radars
This sub-project focuses on the virtual verification and validation of automotive radar systems to increase the reliability of environmental sensing. Metrics and performance indicators for radar-based automated driving functions are identified, and multistage VV chains are implemented, ranging from Software-in-the-Loop (SiL) and Vehicle-in-the-Loop (ViL) to test tracks.

The ika is involved in the 4-CAD project in sub-project 2. A key focus of their work is conducting a data recording campaign to capture synchronized reference and perception data from radar sensors. This data will be collected both in real traffic and on closed test tracks and will serve as a basis for analyzing perception limitations. Based on this data, the ika develops machine learning algorithms to improve the detection performance of radar systems. These algorithms are then analyzed to determine whether they improve the previously identified perception limitations and possibly introduce new ones. Additionally, in cooperation with the HMT and the FAVF of TU Ilmenau, methods for the virtual verification and validation of automotive radar systems are developed and evaluated.

The two sub-projects work together to leverage synergies, particularly in the development of V2X and radar metrics as well as performance indicators for connected and automated driving. Together, the projects make a significant contribution to the VV of radio technologies, thus contributing to increased traffic safety at higher levels of automation.