Infrastructure based 3D measurements to enhance traffic safety for automated vehicles
Reference number | |
Coordinator | XENSE Vision AB |
Funding from Vinnova | SEK 500 000 |
Project duration | April 2022 - April 2023 |
Status | Completed |
Venture | Traffic safety and automated vehicles -FFI |
Call | Road safety and automated vehicles - FFI - December 2021 |
End-of-project report | 2021-05064sv.pdf(pdf, 299 kB) (In Swedish) |
Important results from the project
The purpose of the project has been to evaluate how well infrastructure-based 3D measurements are suitable for enhancing the traffic safety of automated vehicles. The results show that the stereo cameras developed in the project are very suitable for enhancing the traffic safety of automated vehicles and that a good performance can be achieved in detection, classification, positioning and tracking of all relevant objects such as different vehicle categories and people.
Expected long term effects
The results show that infrastructure-based measurements have good prospects for improving the traffic safety of automated vehicles in the long term. Above all, the feasibility study has been able to contribute to objective at subprogram level within FFI Trafiksäker automatisering. It is mainly about integration between vehicles and infrastructure, including systems for vehicle location. The safety of road users outside the vehicle has also been an important part, and in follow-up projects this will be able to play a large role in helping to create safer automated vehicles.
Approach and implementation
The pre-study has primarily tried to understand what limitations exist for different areas and how good the performance in these areas could be. Since the performance will continuously improve and new functions will be added, it has not been the goal in this project to reach as high a performance as possible, but more to show functionality. In order to be able to test several different types of traffic situations, sensors have been installed at four different locations which together cover many different traffic environments. The performance has then been analyzed.