Autonomous Vehicle Position Error Estimation and Control
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Solution Overview
Problem
Autonomous driving systems rely on accurate position estimates for automated operation, but existing methods may not adequately account for error margins, potentially leading to reduced system reliability and safety.
Innovation Solution
A method and system that utilize multiple input systems, including GPS, inertial sensors, and cellular communication, to estimate the current position of a vehicle and calculate an expected error radius, which is then used to control automated driving functions, ensuring accurate positioning and error management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If position estimates are used for automated operation, then automated driving capability is enabled, but position estimation errors reduce system reliability and safety
Solution Approach 1:
The system continuously monitors position estimation errors from multiple input systems (GPS, inertial sensors, cellular communication) and uses this feedback to dynamically adjust automated driving operations. When error thresholds are exceeded, the system provides feedback to switch from automated to manual mode, ensuring safety while maintaining automation capability when conditions are favorable.
Solution Approach 2:
The patent implements error threshold monitoring and mode switching mechanisms in advance to prevent unsafe automated operation. By establishing predetermined error thresholds and automatic switching protocols before critical failures occur, the system cushions against reliability issues while maintaining automated driving functionality within safe operating parameters.
2Measurement precision
If multiple input systems are used to improve position accuracy, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system merges multiple independent position estimation input systems (GPS, inertial sensors, cellular communication) into a unified position estimation framework. By combining these diverse sources and monitoring their collective error margins, the system achieves superior position accuracy while managing the complexity through integrated error threshold monitoring and automated mode switching logic.
Data Source
AI summary
Methods, systems, and vehicles are provided for controlling an automated system of a vehicle. In one example, the vehicle includes one or more automated driving systems, a plurality of input systems, and a processor. The plurality of input systems are used in connection with the vehicle, and are configured to provide inputs. The processor is coupled to the plurality of input systems, and is configured to at least facilitate: estimating a current position of the vehicle using the inputs from the plurality of input systems generating a current position estimate, estimating an error for the current position estimate, the error comprising an expected error radius for the current position estimate, and controlling the one or more automated driving systems using the current position estimate and the expected error radius.