Autonomous driving and e-mobility, technical challenges and benefits
From a first perspective, there are no functional differences between electrically driven vehicles and conventional fossil fuel vehicles with respect to automatic driving. The machine perception of the vehicle’s surroundings is enabled by various sensors, such as camera or radar sensors, fully integrated into the vehicle (see Fig. 1). Additional information about the static driving environment is usually provided by a highly precise digital map. However, these maps can only be used when the vehicle exactly knows its global position. Therefore, an automated vehicle also requires a selflocalization module for map matching. The result of the machine perception is referred to as environment model. It comprises of the dynamic state of the vehicle itself as well as objects of the surroundings, embedded in a static environment. It should also contain all the relevant infrastructure elements such as traffic signs and traffic lights, as well as structuring elements like traffic islands, curbstones, road markings, closed areas or pedestrian crossings.
KeywordsPrediction Module Automatic Driving Radar Sensor Automate Vehicle Autonomous Driving
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