Dynamic Detection Range for Vehicle Position Accuracy
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Solution Overview
Problem
Conventional navigation devices face accuracy issues in determining a vehicle's position near branch points, especially when lane changes occur outside the predetermined detection range, due to varying road conditions and lane change markings.
Innovation Solution
The navigation device sets adjustable detection sections based on road type, speed limit, and parallel extended distance to accurately detect lane changes using a camera, ensuring correct lane identification and position determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a predetermined uniform detection range is used for lane detection, then the processing load is reduced and detection is simplified, but lane changes occurring outside this fixed range cannot be detected, leading to incorrect position determination
Solution Approach 1:
The detection range is made dynamic by adjusting it according to the actual road condition (length of permissible lane change section) rather than using a fixed predetermined range. The arithmetic processing unit determines the detection range based on detected road elements, allowing the system to adapt the detection scope to match the actual lane change opportunity length, thus detecting all relevant lane changes while maintaining processing efficiency.
Solution Approach 2:
The system changes the detection range parameter based on the detected road condition. When a lane change permissible section is detected, the detection range is extended to cover the entire permissible section length rather than using a uniform fixed range. This parameter adjustment ensures accurate detection of lane changes throughout the actual permissible area.
2Measurement precision
If the detection range is extended to cover all possible lane change sections, then all lane changes can be detected, but the processing load increases significantly
Solution Approach 1:
The system performs preliminary detection of road elements (signs and road surface paints) to identify the start and end points of lane change permissible sections in advance. By detecting these boundary elements first, the system can determine the exact detection range needed before actual lane change detection begins, avoiding unnecessary processing of areas beyond the permissible section while ensuring complete coverage of the relevant area.
Solution Approach 2:
The detection process is segmented into distinct phases: first detecting road elements to determine the permissible section boundaries, then using those boundaries to define the detection range, and finally detecting lane changes within that range. This segmentation allows the system to process only the necessary data for each task, improving overall processing efficiency.
3Reliability
If lane detection is applied continuously, then all lane changes are detected, but the processing load and computational resources are excessively consumed
Solution Approach 1:
The system performs lane change detection periodically based on the detection of road elements rather than continuously. When a lane change permissible section is detected through road element recognition, the system activates lane change detection for that specific section. This periodic activation based on actual road conditions reduces processing load while maintaining detection reliability for all relevant lane changes.
Solution Approach 2:
The detection system uses road elements (signs and paints) that are already present on the road to define the detection range and trigger lane change detection. The road infrastructure itself provides the information needed to optimize detection, eliminating the need for continuous monitoring or external input to determine when detection should occur.
Data Source
AI summary
Provided is a technology capable of improving the accuracy of determining a position of an own vehicle in the vicinity of a branch point, in a current position determining device. The current position determining device identifies a detection range according to states of a road on which a vehicle is traveling to detect a lane change, to thereby determine a current position of the vehicle based on information on the detected lane change.