Dynamic Map Layer Updates via Sensor Data Analysis
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Solution Overview
Problem
Maintaining accurate and up-to-date maps for autonomous vehicles and transportation systems is challenging due to various changes in the real world, such as temporary or permanent changes in the environment, which can lead to localization failures and inefficiencies in navigation and route planning.
Innovation Solution
A framework for dynamically updating map layers based on collected sensor data, including detection of changes, derivation of change information, and updating affected map layers, with the ability to revert updates when changes are no longer present, using a multi-layer map structure that includes real-time, semantic, geometric, and prior data layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If map data is maintained statically without frequent updates, then system complexity and energy consumption are reduced, but map accuracy and localization reliability deteriorate due to environmental changes
Solution Approach 1:
The map is divided into multiple layers (base map layer, real-time dynamic layer, seasonal variation layer) that can be independently updated. This segmentation allows the system to update only specific layers when environmental changes are detected, rather than recalculating the entire map, thus maintaining localization reliability while reducing system complexity
Solution Approach 2:
The system pre-establishes a multi-layer map structure with designated layers for different types of environmental changes. By preparing this structured framework in advance, the system can quickly respond to environmental changes by updating only the appropriate layers, avoiding the need for complex real-time decision-making about complete map recalculations
2Reliability
If frequent map updates are performed to maintain accuracy, then map accuracy and navigation effectiveness are improved, but loss of time and energy consumption increase
Solution Approach 1:
The system implements periodic sensor data collection and evaluation at predetermined intervals, rather than continuous updating. This periodic action allows the system to maintain map accuracy by regularly detecting environmental changes while avoiding unnecessary continuous processing, thus reducing time loss and energy consumption
Solution Approach 2:
The system updates only the specific map layers and geographic areas where environmental changes are detected, rather than performing global map updates. This localized updating approach maintains map accuracy in changed areas while significantly reducing the time and computational resources required compared to complete map recalculations
3Measurement precision
If comprehensive sensor data collection is performed to detect all environmental changes, then detection accuracy is improved, but energy consumption and processing complexity increase
Solution Approach 1:
The system extracts and processes only the relevant sensor data needed for detecting specific types of environmental changes (road conditions, traffic conditions, geographic features) rather than processing all available sensor data. This selective extraction maintains detection accuracy while reducing energy consumption and processing complexity
Solution Approach 2:
The system collects sensor data at a frequency and detail level that exceeds minimum requirements for basic detection, but processes only the essential portions needed for map updates. This partial processing approach ensures high detection precision for critical changes while avoiding the energy cost of processing excessive data
Data Source
AI summary
Examples disclosed herein may involve a computing system configured to (i) maintain a map that is representative of a real-world environment, the map including a plurality of layers that are each encoded with a different type of map data, (ii) obtain sensor data indicative of a given area of the real-world environment, (iii) based on an evaluation of the obtained sensor data and map data corresponding to the given area, detect that a change has occurred in the given area, (iv) based on the collected sensor data, derive information about the change including at least a type of the change and a location of the change, (v) based on the derived information, determine that one or more layers of the map is impacted by the change, and (vi) effect an update to the one or more layers of the map based on the derived information.