Modelling, Simulation and Testing of automotive perception sensors
Sim4CAMSens is a CCAV funded project working on methods to quantify and simulate camera, radar and lidar sensor performance under all conditions.

LiDAR noise factor testing
This report systematically examines the effects of environmental noise factors, specifically LiDAR occlusion with clear and muddy water droplets, through controlled laboratory experimentation involving direct application to the active surfaces of tested LiDAR devices. The investigation encompasses comparative analysis of state-of-the-art automotive LiDAR systems, with particular emphasis on quantifying the degradation of point cloud data quality under recreated adverse conditions. Through examination of these interactions, this report contributes to a better understanding of how sensors occlusion phenomena could potentially impact vehicular safety.
The report can be downloaded: D2.2. Test Methodology Report
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Guidelines for the creation of a sensor model simulation handbook
As part of the project, the consortium worked on the validation of sensor models and produced a set of guidelines ...
Sim4CAMSens project final report
The Sim4CAMSens 1 project reached its conclusion in June 2025 and this report attempts to summarise the huge and diverse ...
Roadmaps and Standards Landscape of Perception Sensors and Simulation
This report provides a comprehensive overview of the current and emerging landscape of automotive perception sensors and the standards that ...