Vehicle Map Data Processing Device for Accurate Traveling Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing map data processing systems for vehicles often suffer from inaccuracies due to discrepancies between detailed map databases and actual road situations, leading to reduced precision in traveling control, which requires constant updates to maintain reliability.
Innovation Solution
A map data processing device that includes a map database, a computing module to generate second map data based on the vehicle's environment and state, an update data computing module to assess reliability, and a determining module to decide when to update the database based on error and frequency thresholds, ensuring accurate traveling control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If map data is constantly updated to maintain accuracy, then traveling control precision is improved, but system complexity and resource consumption increase
Solution Approach 1:
The system implements feedback mechanisms by comparing newly acquired map data with existing database data, calculating discrepancy frequencies and reliability scores. This feedback loop enables intelligent update decisions based on actual data quality rather than constant updates, resolving the contradiction between maintaining precision and reducing system complexity
Solution Approach 2:
The update determination module dynamically adjusts update decisions based on calculated reliability values and discrepancy frequencies. Rather than following a fixed update schedule, the system adapts its update behavior based on real-time assessment of data quality and road usage patterns, balancing accuracy maintenance with resource efficiency
2Measurement precision
If map data is frequently updated, then accuracy of traveling control is improved, but data processing time and computational load increase
Solution Approach 1:
The system performs partial updates by selectively updating only those map database entries where the discrepancy frequency and reliability metrics indicate genuine improvements are needed. This avoids the computational overhead of processing and validating every possible data point, reducing data processing time while maintaining accuracy where it matters most
Solution Approach 2:
The system performs preliminary calculations of discrepancy frequency and reliability before committing to database updates. By pre-assessing data quality metrics and comparing multiple data points, the system filters out low-value update candidates early in the process, reducing the overall computational load and processing time required for meaningful updates
3Reliability
If the map database is constantly updated with new data, then precision in traveling control is maintained, but the risk of incorporating erroneous data increases
Solution Approach 1:
The system uses feedback from multiple data comparisons and reliability calculations to validate new map data before incorporation. By continuously monitoring discrepancy patterns and confidence levels, the system can identify and reject erroneous data points, maintaining precision while filtering out harmful inaccuracies
Solution Approach 2:
The system implements beforehand cushioning by calculating reliability scores and discrepancy frequencies before committing updates to the database. This preliminary validation creates a buffer against erroneous data, allowing the system to identify potential errors and prevent their propagation into the traveling control system, thus maintaining precision while minimizing data error risk
Data Source
AI summary
In a map data processing device for a vehicle, a map database has first map data of a road on which the vehicle travels. A map data computing module computes second map data of the road based on a surrounding environment and a traveling state of the vehicle. An update data computing module computes update data for updating the map database, based on a reliability of the second map data. An update determining module then compares the first map data with the update data. When both disagree with each other, the update determining module determines whether to update first map data with the update data, based on a frequency of discrepancy and the reliability. A data processing module executes a processing of updating the map database in accordance with a determination result by the update determining module.