Intersection Risk Extraction for Priority-Road Vehicle Support
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Solution Overview
Problem
Existing systems fail to accurately identify intersections where risk reduction measures are necessary due to varying environmental factors, particularly in scenarios where pedestrians or obstacles are not visible to the driver, leading to inadequate support for collision avoidance.
Innovation Solution
A system that extracts support target intersections by analyzing priority roads, risk reduction amounts, and visibility conditions using probe vehicle data, and executes vehicle support through collision damage reduction brakes with adjusted operating conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional risk evaluation systems are used to determine risk at intersections, then general risk assessment can be performed, but the system cannot accurately identify specific support target intersections where risk reduction measures are most needed due to varying environmental factors
Solution Approach 1:
The system applies local quality by extracting specific intersections as support targets based on their unique environmental characteristics. Instead of uniform risk assessment, the system identifies intersections with specific conditions (shielded roads, priority road configurations, risk reduction amounts below thresholds) and applies targeted support measures only to those locations, making the risk assessment both precise and adaptable to local environmental factors
2Reliability
If the system extracts all intersections for support, then comprehensive coverage is achieved, but the system cannot focus resources on high-risk scenarios where pedestrians or obstacles are not visible to the driver
Solution Approach 1:
The system segments intersections into different categories based on risk characteristics. By dividing the set of all intersections into support target intersections (those meeting specific criteria like shielded roads and priority road status) and non-support intersections, the system can focus computational resources and support measures only on high-risk scenarios, improving reliability without unnecessary complexity
3Measurement precision
If the system uses multiple criteria (priority road extraction, risk reduction amount calculation, shielding determination) to identify support target intersections, then extraction accuracy is improved, but the system complexity increases
Solution Approach 1:
The system applies preliminary action by pre-calculating and storing priority road information for intersections before runtime analysis. The priority road extraction unit identifies and stores which roads have priority status at each intersection, so that during support target extraction, the system can quickly reference this pre-computed information rather than recalculating it, reducing real-time complexity while maintaining high identification accuracy
Data Source
AI summary
A support target intersection extraction system that extracts a support target intersection that is a target of vehicle support in a support target vehicle among intersections included in map information includes: a priority road extraction unit that extracts a priority road among roads connected to the intersection, based on position information, travel information, and the map information acquired from a plurality of probe vehicles; a risk reduction amount calculation unit that calculates a risk reduction amount on the priority road side at the intersection where the priority road is extracted, based on the position information and the travel information acquired from the probe vehicles; and a support target intersection extraction unit that extracts the support target intersection from the intersections where a travel road of the support target vehicle is the priority road and the risk reduction amount is less than a risk reduction amount threshold.