Lateral Guidance Map Point Selection Under Vehicle Memory Constraints
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Solution Overview
Problem
Existing driver assistance systems face limitations in utilizing vehicle-external map data for lateral guidance due to memory and computing resource constraints, particularly when using swarm data for precise and efficient vehicle navigation.
Innovation Solution
The method selects support points from map data based on the vehicle's driving situation, converting them into a usable format for lateral guidance, optimizing memory and computing power usage by focusing on relevant data points and reducing unnecessary calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all map data are stored in the driver assistance system memory, then complete information is available for lateral guidance, but memory capacity is exceeded and resource utilization deteriorates
Solution Approach 1:
The patent extracts only the necessary support points from the complete map data that are relevant for current lateral guidance, storing them locally while keeping the remaining map data external. This selective extraction resolves the contradiction by maintaining information completeness for guidance purposes without exceeding memory capacity.
Solution Approach 2:
The patent segments the complete map data into relevant support points for lateral guidance and irrelevant data, storing only the segmented relevant portions locally. This segmentation allows the system to work with manageable data subsets while preserving access to complete information when needed.
2Measurement precision
If all map data are processed for lateral guidance, then comprehensive guidance accuracy is achieved, but computing power consumption increases excessively
Solution Approach 1:
The patent extracts only the support points necessary for accurate lateral guidance from the complete map data, processing only this extracted subset rather than all available data. This extraction maintains guidance precision while dramatically reducing computing power consumption.
Solution Approach 2:
The patent applies partial action by processing only the necessary portion of map data (support points) rather than the complete dataset. This partial processing achieves sufficient guidance accuracy without the excessive energy consumption that would result from processing all available data.
3Measurement precision
If comprehensive map data are used for lateral guidance, then guidance precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential support points from comprehensive map data, simplifying the data structure to what is actually needed for lateral guidance. This extraction reduces device complexity by eliminating unnecessary data elements while preserving guidance precision.
Solution Approach 2:
The patent segments comprehensive map data into relevant support points and irrelevant information, processing only the segmented relevant portions. This segmentation approach maintains guidance precision while reducing system complexity by working with simplified data structures.
Data Source
AI summary
The disclosure relates to a method for operating a driver assistance system of a vehicle. The driver assistance system is designed to effect lateral guidance of the vehicle. For lateral guidance, the driver assistance system uses data which are provided to the driver assistance system by a vehicle-external memory apparatus. Support points are selected from the map data, which are changed by means of a computing apparatus of the vehicle into a data format usable for lateral guidance, and are then used by the driver assistance system for lateral guidance. The support points to be changed into the data format and can be used for lateral guidance are selected depending on a driving situation of the vehicle. Furthermore, the disclosure relates to a corresponding vehicle.