Guideway Vehicle Localization via Optical Marker Detection
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Solution Overview
Problem
Communication interruptions between guideway-mounted vehicles and centralized or decentralized control systems can occur due to system failures, incorrect information transmission, or sequencing errors, leading to unnecessary braking of vehicles.
Innovation Solution
A vehicle localization system with a set of sensors on each end of the vehicle, configured to detect markers along the guideway, generates sensor data used by a controller to determine the vehicle's position and velocity, and performs consistency checks between sensors to identify and correct errors, eliminating the need for wheel spin detection and wheel diameter calibration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wheel-based position and speed determination is used, then the system can determine vehicle location, but the accuracy deteriorates due to wheel spin or slide conditions
Solution Approach 1:
The patent replaces the mechanical wheel-based measurement system with an optical sensor system that detects markers on the guideway. Sensors mounted on the vehicle capture images of markers, and the controller calculates position and speed based on marker detection rather than wheel rotation, eliminating the harmful effect of wheel spin and slide on measurement accuracy
Solution Approach 2:
The patent introduces markers as intermediary objects on the guideway that serve as reference points for position determination. These markers act as a mediator between the vehicle's motion and the measurement system, providing a stable reference that is independent of the vehicle's wheel condition
2Measurement precision
If wheel diameter calibration is performed to improve measurement accuracy, then position determination improves, but the system complexity and maintenance needs increase
Solution Approach 1:
The patent eliminates the need for mechanical wheel diameter calibration by replacing the wheel-based measurement system with an optical marker detection system. The position and speed are determined through image processing and geometric calculations based on marker positions, which do not require calibration of mechanical components
Solution Approach 2:
The system uses the known geometry of the marker arrangement and the sensor's field of view to automatically calculate position and speed without requiring external calibration procedures. The marker spacing and sensor characteristics are used as self-contained reference data that eliminate the need for additional calibration equipment or procedures
3Ease of operation
If centralized or decentralized control systems are used to monitor vehicle position, then communication and control are improved, but communication interruptions cause unnecessary braking and reduce productivity
Solution Approach 1:
The vehicle determines its own position and speed using onboard sensors and markers, enabling self-localization without continuous communication with centralized or decentralized control systems. This autonomous position determination allows the vehicle to maintain operation even when communication is interrupted, eliminating unnecessary braking events
Solution Approach 2:
The system pre-establishes marker positions along the guideway and equips the vehicle with sensors and algorithms needed for autonomous position determination before communication interruptions occur. This preliminary preparation enables the vehicle to continue operating independently when communication fails
Data Source
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Figure 3A~3B
AI summary
A system comprises a set of sensors on a first end of a vehicle having the first end and a second end, and a controller. The sensors are configured to generate corresponding sensor data based on a detected marker along a direction of movement of the vehicle. A first sensor has a first inclination angle with respect to the detected marker, and a second sensor has a second inclination angle with respect to the detected marker. The controller is configured to compare a time at which the first sensor detected the marker with a time at which the second sensor detected the marker to identify the first end or the second end as a leading end of the vehicle, and to calculate a position of the leading end of the vehicle based on the sensor data generated by one or more of the first sensor or the second sensor.