Vehicle Positioning via Ambient Condition Verification
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Solution Overview
Problem
Existing methods for determining a vehicle's position data, such as the strapdown algorithm, require initial data or an external anchor, which is unreliable when GNSS signals are unavailable, leading to inaccurate position determination after system restarts, especially in environments like tunnels or indoor carparks where inertial sensors lack a valid reference position.
Innovation Solution
A method that associates a defined ambient condition with the vehicle's position, using features like images or temperature, to establish an external anchor, allowing position determination even without GNSS signals by verifying the ambient condition upon restart, and utilizing inertial sensors to extrapolate the vehicle's position based on saved data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If initial data is saved for position determination, then position data can be determined without GNSS signals, but the initial data may be outdated or incorrect after system restarts
Solution Approach 1:
The system performs preliminary actions by saving ambient condition data (images, temperature, humidity) together with initial position data before system shutdown. Upon restart, these pre-saved ambient conditions are automatically compared with current sensor readings to verify whether the saved initial data remains valid, eliminating the need for manual re-calibration and ensuring continuous position determination accuracy.
Solution Approach 2:
The system implements a feedback mechanism where ambient condition sensors continuously monitor the environment and compare current readings against pre-saved reference values. When a mismatch exceeds a threshold, the system automatically detects that the initial data has become invalid and triggers an update, creating a closed-loop verification system that maintains data reliability without continuous GNSS coverage.
2Measurement precision
If ambient condition sensors are added to verify external anchors, then position accuracy is improved, but device complexity increases
Solution Approach 1:
The system achieves multi-functionality by utilizing ambient condition sensors (camera, temperature sensor, humidity sensor) that serve dual purposes: they monitor environmental conditions for comfort/safety and simultaneously provide reference data for position verification. This eliminates the need for dedicated position verification hardware, reducing overall system complexity while maintaining high measurement precision.
Solution Approach 2:
The system employs self-service by using the vehicle's existing sensor suite (camera for interior/exterior monitoring, temperature and humidity sensors for climate control) to perform position verification. Rather than adding specialized equipment, the system makes the existing sensors serve the additional function of external anchor verification, thereby improving position accuracy without increasing device complexity.
Data Source
AI summary
A method for determining initial data for determining position data of a vehicle based on driving dynamics data, the method including: assigning a determined environment status at a determined position of the vehicle to the determined position of the vehicle; detecting on environment status; and—using the determined position as initial data if a contrast of the detected environment status and the determined environmental status satisfies a predetermined condition.