Autonomous Map Data Collection Routes for Two-Way Road Coverage
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Solution Overview
Problem
Current autonomous vehicle systems rely on manually controlled data collection missions that are resource-intensive and inefficient, leading to suboptimal route planning and insufficient data collection for high-definition maps.
Innovation Solution
Implementing a robotic system that autonomously identifies data collection mission areas, generates efficient routes, collects data, and updates maps, using a computing device to manage routes and ensure compliance with predefined rules and real-time updates based on traversal history and sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual control by driver and co-pilot is used for data collection missions, then data can be collected for map generation, but the process becomes expensive and human resource intensive
Solution Approach 1:
The robotic vehicle autonomously performs data collection missions without human operators. The system self-navigates using generated routes, self-monitors sensor functionality, and self-manages data collection processes, eliminating the need for manual control by drivers and co-pilots while maintaining high-quality map data acquisition
Solution Approach 2:
The patent replaces the mechanical human-operated control system with an automated robotic system. The robotic vehicle uses computational algorithms for route following, sensor data processing, and autonomous navigation, substituting human mechanical operations with automated electronic and software-based systems
2Ease of operation
If manual route determination by co-pilot is used during data collection missions, then vehicle routes can be established, but the routes are inefficient in terms of vehicle traversal through certain geographic areas
Solution Approach 1:
The system performs preliminary route generation before data collection missions begin. Routes are pre-calculated to optimize vehicle traversal through geographic areas, ensuring efficient coverage of two-way roads in both directions. This preliminary planning eliminates the inefficiencies of manual route determination while maintaining operational simplicity
Solution Approach 2:
The route determination system dynamically optimizes paths based on geographic area characteristics. The automated system adapts routes to maximize data collection efficiency, adjusting traversal patterns to cover required areas effectively rather than following fixed manual routes that may be suboptimal
3Productivity
If automated robotic system is used for data collection missions, then human resource costs are reduced, but the system requires complex route generation and management algorithms
Solution Approach 1:
The patent introduces a route generation module as an intermediary between the automated vehicle control system and the data collection objectives. This module handles the complex algorithmic operations of route optimization and generation, mediating between simple operational commands and complex navigation requirements, thereby managing system complexity while maintaining high productivity
Data Source
AI summary
Disclosed herein are systems, methods, and computer program products for generating and using map information. For example, the method includes: identifying data collection mission area(s) (DCMAs) within a geographic location that is to be covered by robotic device(s) during a data collection mission (DCM); generating a route to be traversed by robotic device(s) in DCMAs (the route being configured to cause robotic device(s) to traverse each two-way road at least one time in two opposing directions); causing robotic device(s) to perform DCM by following the route and collecting data; causing robotic device(s) to discontinue collecting data in response to a trigger event; and using the data collected during DCM to generate or update the map information. The map information may be used to facilitate controlled movement of a vehicle.