Today, most so called 'black spots' have been eliminated from the road networks. However, intersections can still be regarded as black spots. Depending on the region and country, from 30 to 60% of all injury accidents and up to one third of the fatalities occur at intersections. This is due mainly to the fact that accident scenarios at intersections are among the most complex ones, since different categories of road user interact in these limited areas with crossing trajectories.
The INTERSAFE-2 project aims to develop and demonstrate a Cooperative Intersection Safety System (CISS) that is able to significantly reduce injury and fatal accidents at intersections.
The novel CISS combined warning and intervention functions demonstrated on three vehicles: two passenger cars and one heavy goods vehicle. Furthermore, a simulator is used for additional R&D. These functions are based on novel cooperative scenario interpretation and risk assessment algorithms.
The cooperative sensor data fusion is based on:
- state-of-the-art and advanced on-board sensors for object recognition and relative localisation;
- a standard navigation map
and information supplied over a communication link from:
- other road users via V2V if the other vehicle is so equipped;
- infrastructure sensors and traffic lights via V2I if the infrastructure is so equipped to observe the complex intersection environment.
As a result, the deployment of the INTERSAFE-2 system could provide a positive safety impact of 80% with respect to injuries and fatal accidents at intersections. Thus a total safety benefit of up to 40% of all injury accidents and up to 20% of all fatalities in Europe is possible.
The utilisation of V2X communication for CISS at a small number of equipped intersections would boost the overall market penetration of communication in vehicles, since the benefit for those who buy first could be experienced at every equipped intersection.
The Cooperative Intersection Safety System (CISS) developed is able to detect static and dynamic components of an intersection environment. The road geometry is estimated. Obstacles are detected, tracked and subsequently classified to discriminate their type (e.g. pedestrians, vehicles, lantern poles) and thus their importance in traffic.
In other words: the system is able to detect, track and recognise most of the components of the traffic environment. However, future work is needed in order to increase and improve detection robustness. Future work will include among others: estimation of multiple types of road structures, detection and tracking of more objects and obstables, and enhancing the classification accuracy.
Cooperation between various sensors and data sources, such as the active sensors or GPS and map information, is also planned for the future.
Development of a CISS, able to detect, track and classify static and dynamics components in an intersection environment.
- Innovating for the future (technology and behaviour): A European Transport Research and Innovation Policy
- An efficient and integrated mobility system: Acting on transport safety (saving thousands of lives)
Further development is required to enhance detection, tracking and classification of objects.