Rail Vehicle Path Detection Using Digital Route Network
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Solution Overview
Problem
Existing collision warning and avoidance systems for rail-bound vehicles face challenges in accurately determining the driving path and detecting collision-causing objects due to tight curves and the lack of optical markings, which limits the effectiveness of conventional optical sensor systems.
Innovation Solution
A method that converts the physical rail route network into a digital format using GPS, combined with recording vehicle position and movement data, allows for precise determination of the driving path and optimized sensor alignment to detect potential obstacles, enabling more accurate collision detection and prevention measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If optical sensor systems are used to detect the driving path and obstacles, then collision detection capability is improved, but measurement precision deteriorates due to tight curves and lack of optical markings on rail routes
Solution Approach 1:
The patent replaces optical sensor-based path detection with a digital route network system that uses GPS/position data and pre-stored rail route information. This substitution eliminates reliance on optical markings and enables precise driving path determination even in tight curves where optical sensors fail.
Solution Approach 2:
The patent introduces a digital route network as an intermediary between the vehicle and the physical environment. This digital representation stores pre-defined rail routes with curve profiles, allowing the system to determine the driving path through data matching rather than direct optical sensing.
2Device complexity
If sensor orientation is fixed for standard road detection, then device complexity is reduced, but measurement precision deteriorates in tight curves requiring non-aligned detection
Solution Approach 1:
The patent makes the sensor system dynamic by enabling rotation and reorientation of sensors based on the detected driving path. The control unit rotates sensors to align with the driving path direction, allowing accurate obstacle detection in tight curves while maintaining a relatively simple base configuration.
3Measurement precision
If GPS and digital route network are used to determine driving path, then driving path detection precision is improved, but device complexity increases due to additional positioning and data processing components
Solution Approach 1:
The patent makes the GPS positioning system multi-functional by using it not only for collision detection but also for determining the driving path through comparison with the digital route network. This universal use of positioning data offsets the added complexity by eliminating the need for separate path detection infrastructure.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables reliable and precise detection of the driving path and collision-causing objects, enhancing safety and efficiency for rail-bound vehicles by allowing the application of advanced driver assistance systems, including collision warning and avoidance systems.
Implementation Method 1
the current position of the vehicle on a stored route network is determined
Data Source
Figure 1
AI summary
In the field of rail vehicles, driver assistance systems such as collision warning and avoidance systems, which are well-known from the automotive industry, have so far seen limited adoption. This is primarily due to the inaccurate and unreliable determination of the track width, which is necessary for collision detection, resulting from the lack of steering angle measurement and the absence of optical track markings on rail vehicles. The present invention discloses a method for reliably determining the track width, utilizing the inherent limitations of rail vehicles, based on a digital route network stored in a database and the vehicle's current position and movement data. It thus forms the basis for the application of collision warning and avoidance systems in rail transport and therefore contributes to a significant increase in safety in modern road traffic.