Virtual Track Detection Using Image and Magnetic Positioning
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Solution Overview
Problem
Current self-driving bus navigation technologies, such as GPS and Lidar SLAM, face instability due to environmental variations and require frequent map updates, leading to recognition failures in curved sections where cameras may mistake track patterns for stop lines or road boundaries, limiting autonomous driving capabilities.
Innovation Solution
A virtual track detection system integrating image and magnetic tracks, using positioning elements, image capture devices, and processors to differentiate between straight and curved paths, calculating linear equations or curvatures to control vehicle dynamics, ensuring accurate navigation without GPS reliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If GPS navigation and map information are used for positioning, then preliminary positioning can be achieved, but signal transmission becomes unstable under certain environment or weather conditions
Solution Approach 1:
The patent introduces visual markers as intermediary objects placed on the road surface to serve as a reliable reference for positioning. These markers act as a mediator between the vehicle's vision system and the road geometry, providing stable feature points for localization that are independent of GPS signal availability or weather conditions.
Solution Approach 2:
The patent replaces the GPS radio frequency system with an optical vision-based positioning system. By using cameras to detect visual markers and compute position through image processing and geometric calculations, the system substitutes the mechanical/electromagnetic GPS infrastructure with a purely optical measurement approach that is more reliable in certain environments.
2Measurement precision
If Lidar SLAM or virtual SLAM is used for navigation, then positioning can be achieved, but positioning accuracy is affected by environmental variation requiring frequent base map updates
Solution Approach 1:
The patent employs preliminary action by pre-placing visual markers on the road surface during infrastructure construction. These markers are installed in advance and remain fixed, allowing the vision system to reliably detect them without needing to adapt to environmental changes. This pre-deployment of reference features eliminates the need for frequent map updates required by SLAM systems.
Solution Approach 2:
The patent changes the fundamental parameter of positioning from relative feature extraction (SLAM) to absolute feature detection (visual markers). By transforming the positioning problem from one requiring environmental adaptation to one based on fixed, known reference points, the system achieves consistent accuracy regardless of environmental variation.
3Ease of operation
If a camera is used to capture track images, then navigation can be achieved in straight sections, but the field of view is insufficient in curved sections causing recognition failures
Solution Approach 1:
The patent solves the field of view limitation by transitioning from a two-dimensional image capture problem to a three-dimensional spatial solution. Visual markers are placed at multiple positions along the curved track, allowing the camera to detect markers sequentially as the vehicle moves. This spatial distribution of markers compensates for the limited instantaneous field of view, enabling continuous navigation through curves.
Solution Approach 2:
The patent applies segmentation by dividing the curved track into multiple detectable segments through strategic placement of visual markers. Instead of requiring the camera to capture the entire curve at once, the track is segmented into discrete marker positions that can be detected sequentially, building up complete navigation information over time.
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
Enables fully autonomous driving by accurately distinguishing track patterns from stop lines or road boundaries, reducing operation costs and navigation errors, and allowing vehicles to navigate complex paths without human intervention.
Implementation Method 1
at least one image capture device, installed in a vehicle and capturing front road images, wherein the front road images include a track pattern of the track
Implementation Method 2
a sensor, installed in the vehicle, and used to detect positions of the positioning elements
Data Source
AI summary
A virtual track detection system and method is disclosed, wherein a track pattern is drawn on a track and positioning elements is disposed along a curved section of the track. The method includes steps: capturing front road images; recognizing the track pattern for determining whether a driving path of the vehicle is straight or curved. If the driving path is straight, calculating a linear equation of the driving path and outputting to a dynamic control end of a vehicle system. If the driving path is curved, detecting the positioning elements and calculating a curvature of the curved section, a turning speed and a modification angle according to the positions of the positioning elements to enable the dynamic control end to modify the driving speed and the heading angle. The present invention integrates image detection and magnetic track detection, exempted from environment influence and reducing operation cost.