Vehicle Object Detection Using Arc Intersection Geometry
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Solution Overview
Problem
Existing object detection systems for vehicles face challenges in accurately and simply detecting objects based on information from distance sensors and azimuth sensors, especially when dealing with complex scenarios involving multiple objects or varying sensor data.
Innovation Solution
The object detection device combines a camera as an azimuth sensor and a plurality of sonars as distance sensors, using an object determination section to calculate arcs of circles from distance data and find intersection points with the azimuth region, allowing for accurate detection of object positions and widths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple distance sensors and an azimuth sensor are combined to improve detection accuracy, then object position and width detection precision is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple distance sensors (sonars) and an azimuth sensor (camera) into an integrated object detection system. The distance sensors measure distances to objects from different positions, while the azimuth sensor measures the azimuth region. By merging these sensor types and their data processing, the system achieves accurate object position and width detection without requiring each sensor to independently perform all detection functions, thus improving precision while managing complexity through functional integration.
Solution Approach 2:
The patent transitions from one-dimensional distance measurements to two-dimensional object characterization by incorporating azimuth information. The distance sensors provide radial distance data, while the azimuth sensor adds angular dimension information. By calculating intersection points of arcs (from distance) with azimuth regions (from camera), the system determines both position and width of objects, effectively using dimensional augmentation to improve measurement precision.
2Measurement precision
If complex calculation methods are used to determine object position and width, then detection precision is improved, but processing time increases
Solution Approach 1:
The patent replaces complex iterative geometric calculations with a more efficient computational approach. Instead of using traditional triangulation or iterative optimization methods to determine object position and width, the system calculates arcs of circles from distance sensor data and directly computes intersection points with azimuth region boundaries. This substitution of calculation methodology reduces processing time while maintaining detection precision by leveraging the geometric properties of circular arcs and their intersections with angular regions.
Data Source
AI summary
An object detection device includes an azimuth sensor that measures an azimuth region of an object that is present around a vehicle, a plurality of distance sensors each of which measures a distance to the object, and an object determination section that calculates arcs of circles whose radii are the distances measured by the respective distance sensors and calculates intersection points of a tangent to adjacent ones of the arcs and the azimuth region measured by the azimuth sensor.