Vehicle Lifeform Tracking Beyond Sensor Field of View
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Solution Overview
Problem
Vehicles equipped with sensors often have limited fields of view, leading to undetection of lifeforms such as children and animals in their vicinity, which can result in safety risks due to operators being unaware of their presence.
Innovation Solution
A lifeform notification system using machine-learning models to identify and classify lifeforms outside the sensor's field of view by analyzing data from cameras and other sensors, providing notifications with timestamps of their last detection to ensure operator awareness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are used to detect lifeforms around a stationary vehicle, then detection capability is improved, but the field of view remains limited causing lifeforms to go undetected
Solution Approach 1:
The system transitions from relying solely on direct sensor detection within the limited field of view to tracking lifeforms that have entered and exited the field of view. By adding the temporal dimension of tracking past detections, the system effectively expands its monitoring coverage beyond the immediate sensor range, allowing it to detect and alert about lifeforms that were previously outside the detectable area.
2Area of stationary object
If the sensor field of view is expanded to detect all lifeforms, then detection coverage is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary tracking of lifeforms as they enter the field of view and maintains this information in a tracking record. This preliminary action allows the system to continue monitoring and providing alerts even after lifeforms have left the immediate sensor coverage area, effectively extending detection coverage without requiring physical expansion of the sensor field of view or additional sensors.
3Loss of information
If tracking of lifeform movement is implemented, then awareness of lifeforms outside field of view is improved, but processing requirements increase
Solution Approach 1:
The system extracts only the essential information needed for tracking - the presence and last detected position of lifeforms - from the continuous sensor data stream. By taking out only the critical detection events (when lifeforms enter or exit the field of view) rather than processing every sensor frame, the system maintains comprehensive awareness while minimizing processing requirements and energy consumption.
Data Source
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AI summary
Systems, methods, and other embodiments described herein relate to notifying vehicle operators of lifeforms in the vicinity of a stationary vehicle. In one embodiment, a method includes identifying, from sensor data collected from a sensor of a stationary vehicle, a lifeform in a vicinity of the stationary vehicle. The method also includes tracking a movement of the lifeform in the vicinity of the stationary vehicle determining, from the sensor data, a last time the lifeform was in a field of view of the sensor. The method also includes presenting a notification identifying the lifeform and the last time the lifeform was in the field of view of the sensor.