The Sim4CAMSens project focuses on improving the simulation and testing of automotive sensors
Primarily camera, radar, and lidar, to ensure safety and reliability in autonomous vehicles, it aims to enhance sensor performance by developing high-fidelity models and creating a new framework for sensor testing under various conditions.
Brief
Sim4CAMSens is a project focused on advancing automotive sensor technologies by improving the modeling, simulation, and testing of sensors like cameras, radar, and lidar. The project aims to enhance sensor performance in autonomous vehicles, ensuring their reliability and safety in various conditions. By developing accurate simulations and testing frameworks, the initiative accelerates sensor development while promoting vehicle safety. For further details, visit Sim4CAMSens.
Outcomes
The outcomes of the Sim4CAMSens project include:
1. Improved sensor modelling and simulation techniques for automotive sensors (camera, radar, lidar).
2. Enhanced performance of these sensors under diverse conditions.
3. A validation framework that supports autonomous vehicle safety through credible simulations.
4. Accelerated development of sensor technologies and testing procedures
Consortium
CLICK HERE to visit the project website
Activities
Sim4CAMsens: Weather measurements for the winter test campaign
When designing the Sim4CAMSens Winter testing campaign, as with any real world test work, one of the key concerns was to minimise the number of variables that could impact the experiments.
Sim4CAMsens: Evaluating the impact of temperature and ice accumulation for lidar
LiDAR is a crucial sensor for autonomous vehicles, providing detailed environmental mapping through point clouds. To develop a robust LiDAR model capable of simulating the sensors performance in winter conditions, real-world testing has been carried out.
Sim4CAMsens: Perception sensors under test
When developing the winter test programme, a key consideration was to make sure that we could capture data from a number of different sensors so that we can try to learn how the physics of different sensor technologies are affected by weather rather than measure the performance of a few specific devices.
