Intersection Path Deviation Detection for Obstructed Lane Warnings
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional vehicle path prediction algorithms are not accurate for intersections due to varying turning radii and lack of intersection path information in map messages, making it difficult to predict and prevent collisions, especially with vulnerable road users.
Innovation Solution
A system that generates and transmits map messages with baseline static and dynamic vehicle path information, including nodal points and curvature radii, to predict vehicle paths through intersections and broadcast alerts for potential obstructions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional vehicle path prediction algorithms are used, then the system is simple to implement, but the prediction accuracy is poor due to varying turning radii and lack of intersection path information
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing baseline static paths for intersections in a database before actual vehicle traversal. These pre-computed paths serve as reference models that capture typical vehicle trajectories through intersections, enabling accurate prediction without requiring complex real-time calculations during vehicle passage.
Solution Approach 2:
The patent introduces map messages as an intermediary carrier that transmits intersection path information from remote stations to vehicles. These map messages contain encoded baseline static paths and dynamic path data, serving as a mediator that bridges the gap between intersection infrastructure and vehicle navigation systems, enabling accurate path prediction without direct complex communication between all system components.
2Reliability
If map messages include detailed baseline static paths and dynamic paths, then collision detection capability is improved, but data transmission volume and processing requirements increase
Solution Approach 1:
The system applies local quality by providing detailed path information only for specific intersections and relevant path segments rather than transmitting complete route data for all possible locations. The baseline static paths are selectively transmitted only for intersections where vehicles are currently operating, and only the necessary path parameters (nodal points, curvature radii) are included, reducing overall data volume while maintaining high collision detection capability where needed.
Solution Approach 2:
The patent implements partial action by transmitting only the essential path information required for collision detection - specifically baseline static paths defining typical trajectories and dynamic paths capturing current vehicle deviations. Not all possible path variations or edge cases are transmitted, but the critical information for detecting obstructed lanes and predicting vehicle behavior is selectively included, balancing data completeness with transmission efficiency.
3Measurement precision
If the system continuously monitors and compares dynamic paths to baseline static paths, then obstruction detection accuracy is improved, but computational processing time increases
Solution Approach 1:
The system employs periodic action by continuously updating dynamic paths at regular intervals as vehicles traverse intersections, but only performing the comparison with baseline static paths at specific triggering moments - namely when vehicles approach intersection nodal points or when path deviations exceed predetermined thresholds. This periodic monitoring maintains high obstruction detection accuracy while avoiding unnecessary continuous computational processing.
Solution Approach 2:
The patent implements preliminary anti-action by pre-establishing baseline static paths that represent normal, obstruction-free vehicle trajectories through intersections. These baseline paths serve as preemptive reference models that allow the system to quickly identify deviations indicating obstructions without requiring complex real-time analysis from scratch. The preliminary computation of normal paths enables rapid detection of abnormal conditions during actual vehicle passage.
Data Source
AI summary
A remote station including a transceiver, a memory, and a control module. The memory is configured to store baseline static paths and dynamic paths of vehicles through an intersection. The baseline static paths refer to at least one of previous predetermined paths, averaged paths or historical paths. The dynamic paths refer to current detected paths. The control module is configured to: (i) compare the dynamic paths to the baseline static paths; (ii) determine whether there is a statistical significance between the dynamic paths and the baseline static paths; and (iii) when there is a statistical significance between the dynamic paths and the baseline static paths, broadcast via the transceiver an alert message indicating that the intersection may include an obstruction.