Vehicle Trajectory Map Updating for Reliable Road Change Detection
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Solution Overview
Problem
The autonomous or semi-autonomous control of motor vehicles is hindered by inconsistencies between map data and the vehicle's surroundings, particularly in cases of temporary changes such as construction sites or altered traffic regulations, leading to navigation errors and unresolvable situations.
Innovation Solution
A method and device for updating navigation data by determining the vehicle's trajectory and road usage through scanning, allowing for accurate and rapid updates, with features like classification of roads and integration with satellite navigation systems, and communication with central facilities for data distribution and validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If map data is updated based on a single vehicle's trajectory deviation, then the system can quickly adapt to road changes, but the risk of propagating incorrect data increases
Solution Approach 1:
The patent combines trajectory data from multiple vehicles to update map data. When several vehicles independently report deviations from the stored map routes in the same geographic area, the system merges these reports to confirm a genuine road change before propagating the update. This merging approach enables faster adaptation to road changes while maintaining high reliability through cross-validation.
Solution Approach 2:
The system implements feedback by continuously monitoring trajectory deviations from multiple vehicles and using this collective information to validate and confirm map data updates. The feedback loop ensures that updates are only propagated when supported by multiple independent observations, preventing erroneous updates while enabling timely corrections when genuine changes occur.
2Reliability
If the system requires multiple consistent discrepancies before updating map data, then data accuracy improves, but the time to detect and update road changes increases
Solution Approach 1:
The system performs preliminary actions by continuously collecting and storing trajectory data from multiple vehicles in real-time. This preliminary data collection enables rapid validation when deviations occur, as the system already has accumulated trajectory information ready for immediate comparison and analysis, reducing the time delay while maintaining accuracy requirements.
Solution Approach 2:
The system dynamically adjusts parameters such as the threshold number of required discrepancy reports and the geographic area for validation based on traffic density and historical data. In high-traffic areas where more vehicles are available, the system can更快地 confirm changes with fewer reports, while in low-traffic areas it maintains higher thresholds, optimizing both speed and accuracy across different contexts.
3Measurement precision
If the vehicle scans surroundings to identify road changes, then navigation accuracy improves, but the complexity of the scanning and processing system increases
Solution Approach 1:
The patent makes the scanning system multi-functional by using the same sensors and processing units for both automated driving functions (detecting obstacles, lane markings, traffic signs) and map data update functions (detecting trajectory deviations from stored routes). This universality enables high positioning accuracy without increasing device complexity, as the system performs multiple functions with a single integrated set of components.
Solution Approach 2:
The system merges the processing of scanning data for automated driving control with the processing of trajectory data for map updates. By combining these functions in a unified processing architecture, the system achieves high measurement precision through comprehensive environmental awareness while avoiding the complexity overhead of separate dedicated scanning and processing systems.
4Reliability
If the system validates road usage permission before updating map data, then false data propagation is prevented, but the processing time and computational load increase
Solution Approach 1:
The system performs self-service validation by using its own automated driving control decisions and scanned environmental data to determine whether road usage is permitted. The vehicle's existing control logic, which already determines lawful driving behavior based on traffic rules and road conditions, is applied to validate map update candidates. This self-service approach prevents false data propagation without requiring external validation systems or increasing processing complexity.
Data Source
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AI summary
The invention relates to a method, which comprises steps of determining a trajectory of a motor vehicle; scanning an environment of the motor vehicle along the trajectory; determining, on the basis of the scanning, that the trajectory runs along a street; determining, on the basis of map data, a path between two points of the trajectory; determining a deviation of the trajectory from the path; and updating the map data on the basis of the trajectory.