Predicting Car2X Connectivity: A Data Driven Deep Learning ApproachGrace Hopper Stage
Vehicle sensors are able to see the environment but in some city scenarios the car has to look around corners or behind obstacles to plan trajectory collision free. This could be solved with Car2X connectivity. To predict if there is enough signal to communicate, we developed a prediction model from real world Car2X data. In this talk you will get insights about the flow from data collection in the cars to production ready deep learning prediction model as API. This project is funded by the BMVI mFUND OpenData program.
Cédric Villani, Mathematician - member of the Academy of Sciences - 1st vice-president of the Parliamentary Office For Scientific and Technological Assessment (OPECST) – Member of Parliament Fields Medal,