Model-based Generation and Validation of different Sensor Information contributing to a Fusion Algorithm in Connected Vehicles

The automotive industry is changing from conventional driving into connected and later on autonomous driving. The key enablers for this conversion are the interaction between the highly precise detection of traffic objects, the accurate localization and communication. The paper on hand conducts this issue through an investigation of the involved sensor systems. Using Vehicle-to-Vehicle communication via WLANp, an approach for relative positioning between traffic objects was proposed and realized. In this context, particularly the time delays have been considered as a crucial component. For the precise object localization, a 360 LiDAR system recorded an usual intersection situation. For improving the absolute position of the ego vehicle, an investigation with RTK-capable GNSS modules was conducted. Here, a base station increased the positioning's accuracy significantly by transmitting the correction data to the rover at receiver side.

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