Autonomous Vehicle Fleet Sensing for Infrastructure Quality Mapping
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Solution Overview
Problem
Current methods for monitoring infrastructure quality, such as manual inspections and aerial monitoring, are costly and inefficient for vast areas like roadways and urban environments, and are not compatible with existing infrastructure databases.
Innovation Solution
A platform comprising autonomous or semi-autonomous vehicles equipped with sensors and a fleet management module that can monitor, collect, and report data on infrastructure quality in unstructured open or closed environments, using sensors like cameras, LiDAR, and RADAR to assess and classify infrastructure elements, and apply algorithms for quality assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspections are used to monitor infrastructure quality, then measurement precision can be maintained, but productivity is significantly reduced and costs increase
Solution Approach 1:
The patent replaces manual mechanical inspection systems with autonomous vehicles equipped with sensors (cameras, LiDAR, RADAR) and onboard processors. These vehicles automatically navigate and collect infrastructure data, eliminating the need for manual inspection while maintaining measurement precision through sophisticated sensor arrays and algorithms.
Solution Approach 2:
The autonomous vehicles perform self-directed infrastructure monitoring without human intervention. The vehicles navigate independently, collect data using onboard sensors, process information through embedded algorithms, and automatically report findings, creating a self-service monitoring system that dramatically improves productivity.
2Area of stationary object
If aerial monitoring is used to cover vast areas, then area coverage is improved, but cost and complexity increase significantly
Solution Approach 1:
The patent divides the monitoring task across multiple autonomous vehicles operating in a fleet. Each vehicle covers a specific segment or zone of infrastructure, and the collective fleet achieves comprehensive area coverage. This segmentation reduces the complexity of individual vehicle systems while maintaining large-scale monitoring capability.
Solution Approach 2:
The autonomous vehicles are designed with multi-functional capabilities, serving both navigation purposes and infrastructure monitoring functions. The same sensor suite used for vehicle navigation (cameras, LiDAR, RADAR) is also employed for infrastructure assessment, eliminating the need for specialized aerial monitoring equipment and reducing overall system complexity.
3Measurement precision
If comprehensive sensor arrays are deployed on autonomous vehicles, then measurement precision improves, but use of energy and device complexity increase
Solution Approach 1:
The patent employs sensors that serve dual purposes: navigation and infrastructure monitoring. The cameras, LiDAR, and RADAR systems used for autonomous vehicle navigation are simultaneously utilized to collect infrastructure data, eliminating the need for additional dedicated monitoring sensors and reducing overall energy consumption.
Solution Approach 2:
The system selectively activates and processes sensor data based on operational needs. Not all sensors operate at full capacity continuously; instead, the system adjusts sensor activation and data processing intensity according to the specific monitoring task, energy availability, and data quality requirements, optimizing the balance between measurement precision and energy consumption.
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
Enables efficient and cost-effective monitoring of infrastructure quality across large areas, providing detailed data for infrastructure maintenance and updating existing databases, while being adaptable to various environments.
Implementation Method 1
The sensor comprises a camera, a video camera, a LiDAR, a RADAR, a microphone, a radiation sensor, a chemical sensor, a light sensor, a tactile sensor, or any combination thereof
Implementation Method 2
The sensor comprises a camera, a video camera, a LiDAR, a RADAR, a microphone, a radiation sensor, a chemical sensor, a light sensor, a tactile sensor, or any combination thereof
Implementation Method 3
The sensor comprises a camera, a video camera, a LiDAR, a RADAR, a microphone, a radiation sensor, a chemical sensor, a light sensor, a tactile sensor, or any combination thereof
Data Source
AI summary
Provided herein are platforms for determining a non-navigational quality of at least one infrastructure by a plurality of autonomous or semi-autonomous land vehicles through infrastructure recognition and assessment.