Automated driving

Predicting the severity of accidents

22. April 2020, 11:49 Uhr   |  Irina Hübner

Predicting the severity of accidents
© Technische Hochschule Ingolstadt

Sometimes there is not enough time to prevent an accident. But if you know how serious the accident will be, suitable safety systems can be activated.

The Ingolstadt University of Technology is investigating how to increase traffic safety in the Save-Road research project. The aim of the project is in particular to predict the severity of traffic accidents using artificial intelligence and machine learning.

The research focus is on suddenly appearing objects in the vehicle environment as well as on reliable prediction under different environmental conditions such as rain, fog or unfavorable lighting conditions. As a result of the reliable detection of objects at very short reaction times, suitable safety systems, such as airbags, are to be activated.

However, suddenly appearing and partially concealed objects in the vehicle environment, such as a child chasing a ball, or concealed vehicles, present algorithms with great challenges. For this reason, an increase in automated driving functions requires seamless monitoring of the immediate vehicle environment, especially in populated areas. Information with a high degree of accuracy on the sequence and intensity of an impending accident helps to gain decisive milliseconds for the activation of safety systems in the run-up to an unavoidable accident, thus providing even better protection for vehicle occupants.

In the Save-Road research project, the scientists are developing a system based on artificial intelligence and machine learning for recording the vehicle environment using sensor data fusion. For this purpose, the researchers are merging data from high-resolution radars and optical systems, taking into account accident-relevant parameters such as type of object, speed or distance. The sensor technologies combined in this way are to be validated as part of a novel monitoring concept that makes safety-relevant decisions based on data quality and controls the activation of protective systems.

The project is being carried out by the Ingolstadt University of Technology together with industrial partners. Involved are EFS, a technology provider for software in the field of assisted and piloted driving, and PCO, a company specializing in the development and production of high-end camera systems. The research project is headed by Prof. Dr. Thomas Brandmeier, Scientific Director of the Carissima Research and Test Centre at Ingolstadt University of Technology, and Prof. Dr. Alessandro Zimmer, Professor specialising in computer vision, image processing and artificial intelligence in Carissima.

The Bavarian Research Foundation is supporting Save-Road with around 658,000 euros. This makes the project one of four Bavaria-wide projects selected by the Board of Trustees of the Bavarian Research Foundation in the first funding round 2020.

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