Vehicle Occupant Action Prediction for Early Danger Warning
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Solution Overview
Problem
Current occupancy monitoring systems (OMS) can only alert when a danger has already occurred, failing to prevent the danger from happening.
Innovation Solution
A method and apparatus that determine a target object in a vehicle, predict its future actions based on its trajectory, and execute a control strategy, such as a prompting message, to prevent potential dangers by identifying and addressing the situation before it becomes hazardous.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current OMS systems use alarm-based detection, then they can identify when danger has occurred, but they cannot prevent danger from happening
Solution Approach 1:
The system performs preliminary action by predicting future dangerous actions of occupants before they actually occur. The prediction module analyzes current occupancy data and forecasts potential dangerous behaviors (such as children opening doors or windows), then issues warnings in advance, allowing preventive measures to be taken before the danger materializes.
Solution Approach 2:
The system applies preliminary anti-action by issuing warnings and alerts before dangerous actions occur, creating a counter-force to potential harm. The control module sends notifications to occupants or authorities about predicted dangerous behaviors, enabling them to take corrective actions before the actual danger happens.
2Reliability
If the system monitors all occupants continuously, then it can detect dangers early, but the system complexity increases
Solution Approach 1:
The system applies local quality by focusing monitoring resources on specific high-risk occupants (such as children or elderly passengers) rather than treating all occupants uniformly. The prediction module identifies and prioritizes monitoring of vulnerable individuals based on their characteristics and behavior patterns, allocating computational resources efficiently to where they are most needed.
Solution Approach 2:
The system uses partial action by selectively applying advanced prediction algorithms only to occupants identified as high-risk, rather than uniformly applying complex monitoring to all passengers. This approach achieves high safety detection accuracy for vulnerable groups while keeping overall system complexity manageable.
Data Source
AI summary
A method and apparatus for controlling vehicle-riding safety, an electronic device and a product are provided. The method includes: firstly determining, from the objects that ride in a vehicle, a target object that is required to be monitored; obtaining an action trajectory of the target object; based on the movement trajectory of the target object, predicting a target action of the target object at a future moment; and based on the target action performed by the target object at the future moment and the vehicle state, further determining the dangerous situation of the target object, and executing a control strategy corresponding to the dangerous situation. In other words, when it is predicted that a danger happens at a future time, then the control strategy is executed, thereby the object of early warning is realized, and a danger is prevented from happening.