Unmapped Speed Limit Sign Detection for Autonomous Vehicle Maps
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating with accurate speed limit information due to unmapped speed limit signs, which can lead to traffic violations, as their maps may not reflect recent changes such as new or updated speed limits.
Innovation Solution
A system and method for dynamically updating vehicle maps by identifying unmapped speed limit signs using sensor data, associating them with lane segments, and propagating these updates to all relevant components in real-time, ensuring all systems receive accurate and timely information without altering motion planning tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the map is updated frequently to reflect new traffic signs, then the accuracy of speed limit information is improved, but the system complexity and computational resources required increase
Solution Approach 1:
The system performs preliminary actions by continuously monitoring and detecting traffic signs during normal vehicle operation, preparing map updates in advance before they are officially implemented. This allows the system to have updated speed limit information ready when needed, improving accuracy without requiring complex real-time update mechanisms during critical decision-making moments.
Solution Approach 2:
The system implements feedback loops where detected traffic signs are continuously compared against the existing map data, and discrepancies trigger automatic map update processes. This feedback mechanism ensures that speed limit information remains accurate by constantly verifying it against actual observed signs, while the automated nature of the feedback reduces manual intervention complexity.
2Loss of time
If the map is updated in real-time to reflect new traffic signs, then the timeliness of speed limit information is improved, but the risk of traffic violations due to unmapped signs increases
Solution Approach 1:
The system performs preliminary detection and recording of traffic signs during normal operation, preparing map updates in advance. By the time a new speed limit sign becomes relevant for navigation decisions, the system has already detected it and updated its internal representation, ensuring both timeliness and reliability without conflict.
Solution Approach 2:
The system dynamically adjusts its map data based on real-time sensor detections. When new traffic signs are detected, the map is dynamically updated to reflect current road conditions. This dynamic adaptation ensures that the system always operates with the most current speed limit information available, preventing violations while maintaining up-to-date maps.
3Productivity
If the system uses existing map data for navigation, then the operational efficiency is maintained, but the ability to adapt to new traffic conditions deteriorates
Solution Approach 1:
The system maintains a dynamic balance between using existing map data for efficient navigation and adapting to new conditions. The base map provides stable, pre-processed navigation information for operational efficiency, while simultaneous sensor monitoring enables real-time detection of new traffic signs. When changes are detected, the system seamlessly integrates this new information into its navigation decisions, maintaining both efficiency and adaptability.
Solution Approach 2:
The system uses an intermediary layer that sits between the static map data and the vehicle's navigation decisions. This intermediary continuously monitors actual traffic conditions via sensors and mediates between the pre-stored map information and real-world observations. When discrepancies are found (such as new speed limit signs), the intermediary facilitates smooth integration of updated information, allowing the system to adapt to new conditions while maintaining operational efficiency based on the reliable base map.
Data Source
AI summary
Disclosed herein are system, method, and computer program product embodiments for handling unmapped speed limit signs. For example, the method includes receiving sensor data from a sensor of a vehicle, identifying a traffic sign within a field of view of the vehicle based on the sensor data, identifying one or more lane segments of a road associated with the identified traffic sign based on a determination that the identified traffic sign is not mapped in a priori map, and updating an attribute associated with a segment of the one or more lane segments of the road based on a determination that a detected attribute corresponding to the identified sign is more restrictive than an attribute associated with the lane segment in the a priori map.