Digital Map Verification for Automated Vehicles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Higher-level automated vehicles face challenges in maintaining accurate and up-to-date digital maps due to rapid road changes caused by construction or accidents, which can lead to insufficient updates, potentially compromising traffic safety and being costly with traditional mapping methods.
Innovation Solution
A method and device for verifying digital maps in higher-level automated vehicles using multiple information sources, such as car-to-infrastructure systems, car-to-car systems, navigation systems, and driver assistance systems, to determine the accuracy and necessity of map updates by comparing actual feature properties with setpoint properties and filtering data with algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional mapping methods (motor vehicles, aircraft, satellites) are used to update digital maps, then map accuracy can be maintained, but the cost becomes highly cost-intensive
Solution Approach 1:
The system enables vehicles to automatically verify and update digital maps using their own sensor data without requiring dedicated mapping vehicles or aircraft. The vehicle's navigation system collects data during normal operation and compares it against the digital map, performing self-verification and triggering updates only when necessary.
Solution Approach 2:
Instead of using expensive traditional mapping methods to continuously update maps, the system creates verification copies of map sections using vehicle sensor data. These copies are compared against the original digital map to identify discrepancies, allowing selective updates only where needed rather than complete re-mapping.
2Reliability
If traditional mapping methods are used to ensure up-to-date digital maps, then traffic safety can be improved, but the cost and time consumption increase significantly
Solution Approach 1:
The system performs periodic verification of digital map accuracy using vehicle sensor data at regular intervals or when specific conditions are met. Instead of continuous expensive re-mapping, the navigation system systematically compares actual sensor observations with stored map data, triggering updates only when discrepancies exceed predefined thresholds.
Solution Approach 2:
Vehicles automatically perform verification and assessment of digital map up-to-dateness during normal operation without requiring external mapping resources. The system autonomously determines when map updates are necessary based on detected discrepancies between sensor data and map information.
3Measurement precision
If digital maps are updated frequently to capture road changes, then localization accuracy improves, but the cost and resource consumption increase
Solution Approach 1:
The system changes the verification parameter from continuous expensive re-mapping to selective verification based on detected discrepancies. It monitors specific parameters such as position deviations, feature mismatches, and confidence levels, triggering map updates only when these parameters indicate actual road changes rather than normal variations.
Solution Approach 2:
Instead of performing complete digital map updates frequently, the system applies partial updates only to specific map sections where discrepancies are detected. This selective approach maintains localization accuracy in critical areas while avoiding unnecessary resource consumption in areas where the map remains accurate.
Data Source
AI summary
A method is described for verifying a digital map of a higher-level automated vehicle (HAV), in particular a highly automated vehicle, including the steps: S1 providing a digital map, preferably a highly accurate digital map: S2 determining an instantaneous reference position and localizing the reference position in the digital map; S3 establishing at least one actual feature property of a feature in the surroundings of the reference position, the establishment being carried out with the aid of at least one information source; S4 comparing the actual feature property to a setpoint feature property of the feature and ascertaining at least one difference value as the result of the comparison. A corresponding device and a computer program are also described.