Bicycle Parking Position Selection Under Poor GNSS Reception
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Solution Overview
Problem
Existing methods for determining the parking position of vehicles, especially electric bicycles, face challenges in accuracy due to increased positioning errors when the vehicle is moved into enclosed spaces, such as buildings or underground car parks, where GNSS reception quality decreases.
Innovation Solution
A method that records and stores positions and associated positioning errors by a GNSS receiver, determining the parking position by evaluating the distance and error of stored positions relative to the last position, with the option to scale the last positioning error, ensuring a precise selection based on the combination of distance and error, thereby accounting for potential movement and reception quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the vehicle is moved into enclosed spaces (buildings, underground car parks), then the vehicle can be parked in convenient locations, but the GNSS reception quality decreases and positioning error increases
Solution Approach 1:
The system performs preliminary action by continuously recording position data and associated positioning errors in memory before the vehicle is parked. This creates a historical record of positions with their respective accuracy levels, allowing the system to later select the most reliable position data even when current GNSS reception is poor in enclosed spaces.
Solution Approach 2:
The system applies parameter changes by evaluating multiple positions based on their associated positioning errors and selecting the optimal position. The method dynamically chooses between different recorded positions based on their accuracy characteristics, rather than relying solely on the current last position, thereby adapting to varying reception conditions.
2Ease of operation
If the last position is used as the parking position, then the determination is simple and fast, but the accuracy decreases when GNSS reception is poor
Solution Approach 1:
The system changes the selection criterion from simply using the last position to evaluating multiple positions based on their associated positioning errors. By introducing the error parameter as a selection criterion, the system maintains operational simplicity while significantly improving accuracy, especially in enclosed spaces where reception is poor.
Solution Approach 2:
The system implements feedback by using the positioning error information to evaluate and select the best position from recorded data. The error metric provides feedback on the quality of each recorded position, enabling the system to automatically select the most reliable position without complex manual intervention.
3Measurement precision
If multiple positions are stored and evaluated, then the accuracy of determining the parking position is improved, but the computational complexity and processing time increase
Solution Approach 1:
The system manages complexity by changing the evaluation approach to focus on a key parameter - the positioning error. Rather than complex analysis of all position data, the system evaluates positions based on their error characteristics and selects the optimal one, maintaining reasonable computational complexity while improving accuracy.
Solution Approach 2:
The system applies self-service by automatically selecting the optimal position based on pre-recorded error data without requiring external intervention or complex real-time processing. The evaluation process uses readily available stored information to make the selection, reducing computational burden.
Data Source
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AI summary
The present invention relates to a method and a device for determining the parking position of a vehicle.The process involves a GNSS receiver sequentially acquiring initial positions (11, 12, 13) of the vehicle and storing these positions in a memory, with an associated initial positioning error (15, 16, 17) being stored for each position; the GNSS receiver acquiring a final position (14) of the vehicle with an associated final positioning error (18) in response to the vehicle entering a parked state; and determining the vehicle's parked position, whereby one of the initial positions of the vehicle stored in the memory is identified as the vehicle's parked position if its distance to the final position plus the associated initial positioning error is smaller than the final positioning error or a final positioning error scaled by a predefined scaling factor.