Road Network Inconsistency Detection for Local V2V Map Updates
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Solution Overview
Problem
Changes in road networks, such as weather conditions or infrastructure changes, are not accurately reflected in digital maps used by vehicles, affecting their ability to traverse the road safely and efficiently.
Innovation Solution
A vehicle apparatus that analyzes sensor data in real-time to detect inconsistencies between actual road conditions and digital map data, generates a notification message if the inconsistency meets vehicle-to-vehicle criteria, and broadcasts this information via short or medium-range communication protocols like DSRC, allowing other vehicles and infrastructure to update their maps and adjust navigation accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital map data is used for navigation, then route planning is efficient, but road condition accuracy deteriorates when changes occur
Solution Approach 1:
The system implements feedback by having vehicles continuously detect road conditions using sensors, compare them with digital map data, and propagate detected inconsistencies to other vehicles and infrastructure. This closed-loop feedback mechanism ensures that navigation systems receive timely updates about road condition changes, maintaining navigation accuracy even when digital maps are not updated in real-time.
Solution Approach 2:
The system performs preliminary action by pre-processing sensor data to detect inconsistencies before they become critical navigation issues. Vehicles continuously monitor road conditions and prepare inconsistency detections in advance, allowing receiving vehicles to proactively update their navigation plans before encountering problematic road conditions.
2Measurement precision
If real-time sensor analysis is performed, then road condition detection is accurate, but computational load increases
Solution Approach 1:
The system extracts only the essential inconsistency information from sensor data rather than processing and transmitting all raw sensor information. By identifying and extracting only the detected inconsistencies between sensor observations and digital map data, the system achieves accurate road condition detection while minimizing computational load and data transmission requirements.
Solution Approach 2:
The system segments the road network into discrete road segments and processes sensor data segment by segment. By dividing the continuous road network into manageable segments and analyzing inconsistencies at the segment level, the system reduces overall processing complexity while maintaining detection accuracy for each segment.
3Reliability
If inconsistency detection is performed for all road features, then detection completeness is high, but false positives increase
Solution Approach 1:
The system applies local quality by implementing V2V criteria that evaluate each detected inconsistency based on its specific characteristics and location. Rather than uniformly treating all detected differences as errors, the system assesses each inconsistency locally against relevant criteria (such as whether it affects navigation safety), thereby maintaining high detection completeness while reducing false positives through context-aware evaluation.
4Reliability
If map updates are propagated to all vehicles, then navigation accuracy improves, but communication bandwidth consumption increases
Solution Approach 1:
The system extracts and transmits only the essential inconsistency information rather than complete map updates to all vehicles. By identifying and propagating only the detected inconsistencies that affect navigation, the system maintains navigation accuracy across the vehicle fleet while significantly reducing communication bandwidth consumption and energy usage compared to distributing full map updates.
Data Source
AI summary
Changes in a road network may be detected and information/data regarding the change may be locally propagated in at least near real time with respect to the detection of the change. A vehicle apparatus onboard a vehicle analyzes sensor data collected as the vehicle traverses at least a portion of a road network. The sensor data is captured by sensors onboard the vehicle. The sensor data is analyzed in at least near real time with respect to the capturing of the sensor data. The vehicle apparatus detects an inconsistency between a result of the analysis of the sensor data and map data stored in the memory. Responsive to the detected inconsistency satisfying a vehicle-to-vehicle criterion, the vehicle apparatus generates a notification message comprising an indication of the detected inconsistency. The vehicles apparatus transmits the notification message via a communication interface using a short or medium range communication protocol.