Surface Map Generation for Detecting Road Irregularities
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Solution Overview
Problem
Current mapping technologies face challenges in accurately identifying and distinguishing irregular surfaces in geographic regions, such as speed bumps and potholes, due to the limitations of relying solely on image data or sensor data, which can lead to incomplete or inaccurate navigation and vehicle control systems.
Innovation Solution
A computing system that combines image data with sensor data, using semantic information and LiDAR point cloud data to determine irregular surfaces by satisfying specific criteria such as depth and spatial characteristics, and generates map data to improve route planning and vehicle control systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only image data is used for mapping, then the system complexity is low, but the accuracy of identifying irregular surfaces deteriorates
Solution Approach 1:
The patent combines image data from cameras with sensor data from LiDAR and other sensors to create a comprehensive mapping system. This merging of multiple data sources enables accurate identification of irregular surfaces by cross-validating information from different modalities, resolving the contradiction between system complexity and identification accuracy.
Solution Approach 2:
The patent introduces semantic information as an intermediary layer that processes and interprets raw sensor data. This semantic layer acts as a mediator between the complex sensor inputs and the final irregular surface identification, enabling accurate detection while managing system complexity through structured information processing.
2Measurement precision
If only sensor data is used for mapping, then the measurement precision of surface detection is high, but the loss of information deteriorates
Solution Approach 1:
The patent merges sensor data with image data and semantic information to create a comprehensive representation of the environment. This combination prevents information loss by supplementing precise but limited sensor data with contextual information from images and semantic processing, ensuring complete understanding of irregular surfaces.
3Measurement precision
If multiple data sources are combined for mapping, then the accuracy of identifying irregular surfaces is improved, but the device complexity increases
Solution Approach 1:
The patent segments the mapping system into distinct functional modules: image acquisition, sensor data collection, semantic information processing, and integration layers. This segmentation manages complexity by organizing multiple data sources into manageable, independent components that can be processed and integrated systematically.
Solution Approach 2:
The patent implements a universal processing framework that handles multiple data types (images, sensor data, semantic information) through common integration logic. This multi-functional approach reduces overall system complexity by using unified processing pathways rather than separate specialized systems for each data type.
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 enhances the accuracy of identifying irregular surfaces, improves road safety, optimizes resource utilization for road maintenance, and reduces wear and tear on vehicles by providing more precise navigation and control of vehicle systems.
Implementation Method 1
sensor data that is indicative of one or more surface elements associated with one or more surfaces in the geographic region
Data Source
AI summary
Provided are methods, systems, devices, and tangible non-transitory computer readable media for mapping geographical surfaces. The disclosed technology can access image data and sensor data. The image data can include a plurality of images of one or more locations and semantic information associated with the one or more locations. The sensor data can include sensor information associated with detection of one or more surfaces at the one or more locations by one or more sensors. One or more irregular surfaces can be detected based at least in part on the image data and the sensor data. The one or more irregular surfaces can include the one or more surfaces associated with the image data and the sensor data that satisfies one or more irregular surface criteria at each of the one or more locations respectively. Map data including information associated with the one or more irregular surfaces can be generated.