Onboard Digital Map Evaluation for Automated Driving Safety

Resolve Bottlenecks,
Find Innovative Solutions
Generate Solutions

Solution Overview

Problem

Autonomous and semi-autonomous vehicles rely on high-definition map data, which may be outdated or incorrect, leading to potential safety hazards if deviations between the map and real-world environment are not detected.

Innovation Solution

A method and system for evaluating a digital map onboard a vehicle by analyzing sensor data and map data for deviations, determining an evaluation state for map items, and calculating a probability that the map correctly represents real-world objects, thereby enabling safe operation even in challenging conditions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If the vehicle uses high-definition map data for autonomous operation, then the automated driving function can operate, but the map data may be outdated or incorrect leading to safety hazards

Engineering Contradiction:
Improveautomated driving functionVSAvoidmap data accuracy
Core Design Contradiction:
Extent of automationVSReliability

Solution Approach 1:

The system continuously compares sensor data with map data and provides feedback about deviations. When deviations are detected, the system alerts the driver or adjusts automated driving operations, creating a closed-loop feedback mechanism that maintains safety while enabling automation.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The system performs preliminary verification of map data accuracy before relying on it for automated driving. By proactively checking for deviations between sensor data and map data, the system prevents potential safety hazards before they occur during automated operation.

Inventive Principle:
Principle #10Preliminary action

2Measurement precision

If the vehicle verifies map data using sensor systems, then map deviations can be detected, but verification errors occur due to bad weather conditions or occlusion effects

Engineering Contradiction:
Improvemap verification accuracyVSAvoidweather conditions and occlusion
Core Design Contradiction:
Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The system performs partial verification of map data, focusing on critical areas where deviations are most likely to occur. Instead of attempting to verify all map data uniformly, the system prioritizes verification in areas with higher risk of deviations, such as recently constructed areas or areas with complex geometry, thereby maintaining verification accuracy despite weather conditions or occlusion.

Inventive Principle:
Principle #16Partial or excessive action

3Productivity

If the vehicle continues operation with potentially deviating map data, then productivity is maintained, but safety risks increase

Engineering Contradiction:
Improvedriving function operationVSAvoidsafety risks from map deviations
Core Design Contradiction:
ProductivityVSObject-affected harmful factors

Solution Approach 1:

The system changes the operational parameters of automated driving based on map data reliability. When deviations are detected, the system adjusts parameters such as driving speed, following distance, or automation level to maintain safety while allowing continued operation. This enables the vehicle to operate at reduced automation levels or with increased caution in areas with uncertain map accuracy.

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP4517261A1Method for evaluating a digital map onboard of a vehicle, system and vehicle
Publication Date: 2025.03.05 VOLKSWAGEN AG
  • EP4517261A1 patent drawingFigure 1~2
  • EP4517261A1 patent drawingFigure 3
  • EP4517261A1 patent drawingFigure 4~5

AI summary

The present invention is related to a method for evaluating a digital map onboard of a vehicle. Sensor data representing a vehicle environment of the vehicle (30) are received (10) from a sensor (S) implemented in the vehicle. Furthermore, map data of a digital map stored in the vehicle are received (11). The sensor data and the map data are analysed (12) for deviations between the sensor data and the map data and an evaluation state is determined (12) for at least one map item based on the result of the analysis. A probability that the digital map correctly represents real-world objects in the vehicle environment is calculated (13) based on the evaluation state.