Autonomous Vehicle Sensor Calibration Using Road Map Alignment
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Solution Overview
Problem
Autonomous vehicles face challenges in accurately calibrating their sensors due to discrepancies between sensor-generated object locations and those provided by map data, which can affect navigation and obstacle avoidance.
Innovation Solution
An autonomous vehicle system that utilizes map data to compare and adjust sensor parameters, such as orientation and focus, to align sensor-provided object locations with those in the map data, thereby enhancing calibration accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensor parameters are adjusted to align with map data, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system performs self-calibration by automatically comparing sensor-generated object locations with map data and adjusting sensor parameters without requiring external intervention. The processing system autonomously identifies discrepancies and configures sensor orientation, position, or focus to resolve them.
Solution Approach 2:
The system establishes a feedback loop where sensor data is continuously compared with map data, and the discrepancies feed back into parameter adjustments. This closed-loop approach ensures ongoing calibration accuracy by using the map data as a reference standard.
2Reliability
If sensor calibration is performed using map data, then reliability is improved, but loss of time occurs during calibration process
Solution Approach 1:
The system performs calibration actions proactively by continuously comparing sensor data with map data during normal operation. Rather than requiring dedicated calibration sessions, the system opportunistically calibrates sensors whenever map data is available, transforming calibration from a time-consuming separate process into an integrated ongoing function.
Solution Approach 2:
The calibration process operates continuously alongside normal sensor functions. The system maintains ongoing comparison between sensor-generated locations and map data, ensuring calibration is an uninterrupted process rather than a periodic interruption, thereby minimizing time loss while maintaining reliability.
Data Source
AI summary
Example methods and systems for calibrating sensors using road map data are provided. An autonomous vehicle may use various vehicle sensors to assist in navigation. Within examples, the autonomous vehicle may calibrate vehicle sensors through performing a comparison or analysis between information about the environment received by sensors with similar information provided by map data (e.g., a road map). The autonomous vehicle may compare object locations as provided by the sensors and as shown by map data. Based on the comparison, the autonomous vehicle may adjust various sensors to accurately reflect the information as provided by the road map. In some instances, the autonomous vehicle may adjust the position, height, orientation, direction-of-focus, scaling, or other parameters of a sensor based on the information provided by a road map.