New paper: Plausibility check for C2C communication messages by data fusion with camera
We published a new scientific paper for data fusion and C2C experts that presents a vision-based multi-object tracking system for checking the plausibility of V2V communication to e.g. detect spoofing by an attacker. The plausibility check is implemented in a prototype and based on a state-of-the-art multiple-object tracking algorithm. The application is a result of the AutoNet2030 project, with contributors from Hitachi Europe, Chemnitz University and BASELABS.
Automated vehicles require an adequate and reliable perception of the surrounding world in order to make good decisions. Using vehicle-to-vehicle (V2V) communication to exchange location data (i.e. time, position, heading and speed) can improve the perception beyond the capabilities of traditional on-board sensors (e.g. radar, lidar). However, it is vital to trust the data before it is being used. Cryptographic mechanisms can protect the exchange and authenticity of data but do not guarantee the correctness of the content. In this paper a vision-based multi-object tracking system for checking the plausibility of V2V communication is presented. The system is addressing the challenge of fusing relative sensor observations as provided by a MobilEye vision-system with time-delayed absolute GNSS-based measurements from Cooperative Awareness Messages (CAMs) as provided by V2V. The plausibility check is implemented in a prototype and based on a state-of-the-art multiple-object tracking algorithm. The proposed system is evaluated and validated under real-world conditions by conducting several test drives under urban conditions.
Published with kind permission of the authors. Original publication at IEEE Vehicle Networking Conference 2014.
Read the paper.
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