Observation Distance Estimation With Road Surface Feedback Correction
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Solution Overview
Problem
Existing observation devices face challenges in accurately estimating distances to observation targets due to discrepancies between virtual and real-world road surfaces, leading to inaccuracies in distance measurements.
Innovation Solution
The observation device includes an imaging device, storage, and a controller that corrects distance information using measured distances from moving bodies to adjust for discrepancies above a threshold, employing a conversion formula or table to align image positions with real-world coordinates, thereby improving distance estimation accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distance information is generated based on a virtual road surface model, then distance estimation can be performed efficiently, but accuracy deteriorates due to shape differences between the virtual model and the real road surface
Solution Approach 1:
The system uses measured distances from moving bodies as feedback to detect discrepancies between the virtual road surface model and the real road surface. When a discrepancy exceeding a threshold is detected, the system corrects the distance information by adjusting the vertical position of the virtual road surface model to match the real road surface at the discrepancy location, thereby improving accuracy while maintaining the efficiency of the model-based approach
Solution Approach 2:
The system dynamically changes the parameters of the virtual road surface model (specifically the vertical position Z) based on measured distances from moving bodies. When discrepancies are detected, the model parameters are adjusted to reflect the actual road surface geometry, transforming the static virtual model into an adaptive representation that improves distance estimation accuracy
2Measurement precision
If the virtual road surface model is adjusted to match the real road surface, then distance estimation accuracy improves, but system complexity increases due to the need for continuous correction
Solution Approach 1:
Instead of continuously adjusting the entire virtual road surface model, the system performs partial corrections only at specific locations where discrepancies exceeding a threshold are detected. This selective correction approach improves accuracy where needed while avoiding the complexity of global model adjustments
Solution Approach 2:
The system applies local corrections to the virtual road surface model at specific discrepancy locations rather than uniformly adjusting the entire model. Each correction is localized to the area where the measured distance deviates from the estimated distance, maintaining simplicity in areas where the model is already accurate
Data Source
AI summary
An observation device 10 includes an imaging device 17, storage 18, an acquirer 19, and a controller 20. The imaging device 17 generates an image. The storage 18 stores distance information. The distance information is a relationship between an image position and information pertaining to distance. The acquirer 19 acquires position information pertaining to the spatial position of a moving body. When the distance discrepancy between a measured distance and an estimated distance is at or above the first threshold, the controller 20 corrects the distance information using the measured distance. The measured distance corresponds to the position information. The estimated distance is obtained on the basis of the image position of the moving body in the image and the distance information.