3D Roadway Calibration Targets for Long-Range Lidar Detection
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Solution Overview
Problem
Current sensor systems, particularly lidar sensors, face challenges in efficiently detecting and distinguishing between 2D targets on roadways due to limited range and resource constraints, leading to potential safety issues and collisions.
Innovation Solution
A method for generating optimized 3D targets with specific dimensions and surface depths, based on detection resolution and speed limits, to enable efficient identification by lidar sensors, involving a configuration device that estimates exposure time and determines target dimensions and surface depths to generate a unique code for each target, allowing for accurate detection and mapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If 2D targets are used on roadways, then the targets are simple to manufacture and install, but the lidar sensor cannot efficiently detect and distinguish between targets at extended ranges
Solution Approach 1:
The patent transitions from 2D targets to 3D targets by adding depth as a new dimension. The 3D targets include multiple surfaces at different depths from the mounting surface, creating a three-dimensional structure that lidar sensors can detect and distinguish more effectively at extended ranges while maintaining manufacturing feasibility.
Solution Approach 2:
The patent applies local quality by varying the depth of different portions of the target relative to the mounting surface. Different regions of the target have different depth characteristics, creating a unique depth pattern that enhances detectability and allows the target to encode identification information through its three-dimensional structure.
2Length of stationary object
If lidar sensors operate at extended ranges, then the detection coverage is improved, but the exposure time to detect and process target information is reduced
Solution Approach 1:
The patent changes the physical parameters of the target by introducing three-dimensional depth variations. The multiple surfaces at different depths create stronger and more distinct lidar returns, allowing the sensor to detect and process target information more quickly even at extended ranges where exposure time is limited.
3Measurement precision
If more computational resources are allocated to target detection, then the ability to distinguish between targets improves, but the resource constraints of the system are violated
Solution Approach 1:
The patent makes the target self-identifying through its three-dimensional structure. The unique depth pattern of the 3D target encodes identification information that the lidar sensor can detect and process with minimal computational resources, eliminating the need for complex image processing or extensive computational analysis.
Data Source
AI summary
Various aspects of the present disclosure generally relate to sensor targets. In some aspects, a method may include obtaining a detection resolution of a sensor that is to detect a target on a roadway; obtaining a designated speed limit of the roadway; estimating an exposure time of the target based on the detection resolution and the designated speed limit; determining, based on the exposure time, a target dimension of the target and a quantity of surface depths of the target; generating a code for the target based on the quantity of surface depths, wherein the code corresponds to a physical configuration of the target; and storing, in a mapping associated with the sensor, the code in association with the target to permit the target to be identified by the sensor. Numerous other aspects are provided.