Quantifying Sensor Surface Contamination for Safe Vehicle Automation
| Reference number | |
| Coordinator | Högskolan i Halmstad - Högskolan i Halmstad Akademin f informationsteknologi |
| Funding from Vinnova | SEK 3 450 870 |
| Project duration | November 2023 - November 2025 |
| Status | Ongoing |
| Venture | Safe automated driving – FFI |
| Call | Traffic-safe automation - FFI - autumn 2023 |
Purpose and goal
The primary aim of this research project is to quantify how sensor surface contamination affects the sensor signal performance of exterior vehicle sensors. Specific objectives are: - Controlled Experimentation in Diverse Environments - Evaluating Different Sensors - Advancing Shift-Left Testing - Understanding Sensor Signal Performance Consequences - Enhancing Safety and Reliability of ADAS and AD
Expected effects and result
Overall, this project aims to significantly enhance the functionality and reliability of AD and ADAS systems across a wider range of environmental conditions, leading to safer, more inclusive, and sustainable road transport. Specific effects are: - Improved Vehicle Perception in Varying Weather - Foundation for Designing more Robust Systems - Better Understanding Current Perception Systems - More Sustainable Sensor Cleaning Solutions - Reduced Environmental Impact from Accidents: - Increased Vehicle Utilization - Advancement in Scientific Research
Planned approach and implementation
The structure is four work packages: WP1 (Q1 2024 - Q1 2025): focuses on studying sensor degradation from contaminants in anechoic chambers, integrating the findings with Volvo Cars findings. WP2 (Q2 2024 - Q4 2024): aims to measure surface contamination in wind tunnels, developing dynamic measurement strategies. WP3 (Q1 2025 - Q3 2025): tests sensors in wind tunnels, preparing for LiDAR integration. WP4 (Q1, Q3 2024, Q4 2025): involves real-time vehicle tests for sensor performance in adverse weather.