Crossing Obstruction Detection With Collision Prediction and Braking
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Solution Overview
Problem
Existing systems for detecting obstructions at route crossings, such as rail-road intersections, often miss warnings or generate false positives, leading to inefficiencies and potential collisions due to missed alerts or incorrect vehicle movement.
Innovation Solution
A system that integrates onboard and off-board sensors, including cameras and controllers, to detect obstructions and predict potential collisions, using machine learning to autonomously adjust vehicle movement to avoid collisions, and includes a centralized control system for alert escalation and vehicle braking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radar systems are used to detect vehicles at crossings, then detection capability is provided, but false positives increase and efficiency decreases
Solution Approach 1:
The patent combines multiple detection technologies (radar, optical sensors, machine learning algorithms) into an integrated system that cross-validates detections. This merging approach filters false positives through multi-modal verification while maintaining comprehensive detection coverage, resolving the contradiction between reliability and efficiency.
Solution Approach 2:
The system dynamically adjusts detection parameters such as sensitivity thresholds, detection zones, and alert criteria based on contextual factors like vehicle type, crossing geometry, and environmental conditions. This adaptive parameter adjustment reduces false positives while maintaining high detection accuracy for genuine threats.
2Reliability
If warning systems alert personnel to obstructions, then safety awareness is improved, but warnings may be missed by personnel
Solution Approach 1:
The system implements multi-channel feedback loops where detection results are communicated through multiple pathways (automated vehicle communication, personnel alerts, centralized monitoring). This redundant feedback structure ensures that safety information is received and acted upon, preventing missed warnings while maintaining high alert reliability.
Solution Approach 2:
The patent introduces automated vehicle control systems and centralized monitoring platforms as intermediaries between detection sensors and human personnel. These intermediaries process, validate, and relay warning information, ensuring that critical safety alerts are not missed by personnel while maintaining system reliability through automated verification.
3Reliability
If autonomous vehicle control is implemented to avoid collisions, then collision risk is reduced, but system complexity increases
Solution Approach 1:
The autonomous control system is divided into modular functional segments (detection module, prediction module, decision module, execution module). Each segment performs a specific function and can be independently developed, tested, and maintained. This segmentation reduces overall system complexity while enabling sophisticated collision avoidance capabilities through coordinated module interaction.
Data Source
AI summary
Systems and methods for detecting or predicting potential collisions between vehicles are provided. The systems and methods may receive sensor output indicative of a location, a heading, and/or a moving speed of a first vehicle and/or a second vehicle. The systems and methods may predict a collision between the vehicles at an intersection between routes based on the received sensor output. The systems and methods may change movement of the first vehicle and/or the second vehicle responsive to predicting the collision.