Autonomous Vehicle Map Updating via Sensor Inconsistency Detection
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Solution Overview
Problem
Autonomous driving systems face challenges in maintaining accurate navigational maps due to environmental changes, leading to potential safety hazards when relying on outdated maps.
Innovation Solution
A control system for autonomous vehicles that uses sensor data to detect inconsistencies in the driving environment, triggering real-time mapping and updating of navigational maps, with a processor and memory executing instructions for anomaly detection and mapping, and determining sufficient new data for updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time mapping is continuously performed to update navigational maps, then map accuracy is improved, but computational resource consumption increases
Solution Approach 1:
The system performs mapping operations selectively rather than continuously. The processor triggers real-time mapping only when inconsistencies between sensor data and navigational map exceed a threshold, performing partial mapping actions only in affected areas rather than complete re-mapping of the entire environment.
Solution Approach 2:
The system uses periodic anomaly detection to monitor the navigational map against current sensor data. The processor periodically compares sensor output with map data and triggers mapping updates only when anomalies are detected, creating a periodic check-update cycle rather than continuous operation.
2Reliability
If real-time mapping is triggered frequently to maintain map accuracy, then navigational reliability is improved, but system response time increases
Solution Approach 1:
The system triggers mapping operations selectively based on anomaly thresholds rather than continuously. When inconsistencies are detected, only the specific affected map regions are updated rather than performing complete re-mapping, reducing the time penalty while maintaining reliability.
Solution Approach 2:
The system implements a feedback mechanism where sensor data is continuously compared with navigational map data, and mapping updates are triggered only when discrepancies exceed a threshold. This feedback loop ensures updates occur reliably when needed while avoiding unnecessary updates that would increase response time.
3Measurement precision
If comprehensive sensor data processing is performed to detect all inconsistencies, then detection precision is improved, but device complexity increases
Solution Approach 1:
The system extracts and processes only the relevant portions of sensor data that pertain to detected anomalies. Rather than comprehensively processing all sensor data continuously, the processor identifies specific regions of interest based on anomaly detection and focuses processing resources on those areas, reducing overall system complexity.
Data Source
AI summary
Systems and methods for updating navigational maps based using at least one sensor are provided. In one aspect, a control system for an autonomous vehicle, includes a processor and a computer-readable memory configured to cause the processor to: receive output from at least one sensor located on the autonomous vehicle indicative of a driving environment of the autonomous vehicle, retrieve a navigational map used for driving the autonomous vehicle, and detect one or more inconsistencies between the output of the at least one sensor and the navigational map. The computer-readable memory is further configured to cause the processor to: in response to detecting the one or more inconsistencies, trigger mapping of the driving environment based on the output of the at least one sensor, update the navigational map based on the mapped driving environment, and drive the autonomous vehicle using the updated navigational map.