Retroreflective Feature Detection Using LIDAR Intensity Filtering
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Solution Overview
Problem
The collection and processing of geographic data for navigation systems are time-consuming and intricate, requiring efficient methods to expedite the development of accurate map databases.
Innovation Solution
A method involving the emission of light along a travel path, using returning light to generate data points, which are filtered based on intensity to identify features treated with retroreflective substances, allowing for the determination and modeling of geographic features for map database development.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional data collection and processing methods are used to develop geographic data for navigation systems, then comprehensive map data can be obtained, but the process is time-consuming and intricate
Solution Approach 1:
The patent replaces traditional mechanical data collection methods (manual mapping, physical surveys) with optical detection systems. A light source emits light along the travel path, and sensors detect returning light to generate data points representing geographic features. This optical system automatically captures road signs, lane markings, and other features treated with retroreflective substances, eliminating time-consuming manual processes while maintaining high measurement precision through intensity-based filtering
Solution Approach 2:
The system uses retroreflective substances already present on road features (road signs, lane markings) to enable automatic detection. These substances naturally reflect light back to the sensor without requiring additional active components on the features themselves. The system leverages this existing property to automatically identify and classify geographic features, making the data collection process self-sufficient and eliminating the need for manual feature identification and classification
2Reliability
If detailed geographic features are identified and modeled for navigation systems, then map database quality improves, but data processing complexity increases
Solution Approach 1:
The patent uses return intensity values as a key parameter to automatically differentiate between various geographic features. By analyzing the intensity of light returned from different objects, the system can distinguish between road signs, lane markings, and other features treated with retroreflective substances. This parameter-based classification simplifies the processing complexity while improving reliability, as intensity thresholds can be objectively defined and consistently applied to generate accurate geographic data models
Solution Approach 2:
The system applies different processing and classification rules to different types of geographic features based on their local characteristics. Road signs, lane markings, and other features are identified and modeled with specific attributes appropriate to their type. This localized approach to feature processing maintains high map database reliability by capturing relevant details for each feature type while avoiding unnecessary complexity through targeted rather than universal processing
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
This approach enables the rapid and accurate collection and processing of geographic data, enhancing the efficiency of map database development and navigation-related services by identifying features like road signs and lane markings with high precision.
Implementation Method 1
light from a light source is emitted while on the travel path. Returning light is received based on the emitted light
Implementation Method 2
The returning light is used to generate data points representing an area about the travel path. The data points are filtered as a function of a return intensity value to identify a feature associated with the travel path, in which the feature is treated with a retroreflective substance
Data Source
AI summary
Systems, devices, features, and methods for determining geographic features corresponding to a travel path to develop a map database, such as a navigation database, are disclosed. For example, one method comprises emitting light from a light source, such as a LIDAR device, while on the travel path. Returning light is received based on the emitted light. The returning light is used to generate data points representing an area about the travel path. The data points are filtered as a function of a return intensity value to identify a feature associated with the travel path, in which the feature is treated with a retroreflective substance.