Vehicle Object Detection for Stationary Fall-On-Car Prevention
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Solution Overview
Problem
Conventional systems and methods for detecting objects around vehicles are ineffective in predicting and preventing fall-on-car accidents when vehicles are stationary, as they assume vehicles are in running mode and do not account for stationary scenarios.
Innovation Solution
The system activates a fall-on-car prevention function, using sensors to detect objects around the vehicle and monitor changes in parameters such as location and posture of the object. When significant changes are detected, the system notifies the driver to prevent potential fall-on-car accidents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional systems and methods are used to detect objects around vehicles, then collision risk assessment during running mode is improved, but detection accuracy for fall-on-car accidents during stationary mode deteriorates
Solution Approach 1:
The system dynamically adjusts its operational mode based on vehicle state. When the vehicle is in running mode, it operates in collision detection mode. When stationary, it automatically switches to fall-on-car accident detection mode, optimizing performance for the current operational context
Solution Approach 2:
The system changes detection parameters based on vehicle state. During stationary mode, it monitors parameters such as object distance, object type, and environmental conditions that are specific to fall-on-car accident scenarios, rather than using collision detection parameters designed for running mode
2Productivity
If conventional systems assume vehicles are in running mode, then running mode detection is optimized, but stationary mode detection capability is lost
Solution Approach 1:
The detection system is designed to perform multiple functions by detecting the vehicle's operational state and automatically adapting. It can detect both collision risks during running mode and fall-on-car accidents during stationary mode, making it universally applicable to both scenarios without requiring separate dedicated systems
3Measurement precision
If the system monitors objects around stationary vehicles, then fall-on-car accident detection is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary detection of objects around the vehicle and stores their initial positions and characteristics. When the vehicle is stationary, it continuously monitors for changes in these pre-identified objects, enabling fall-on-car accident detection without requiring a completely new complex detection framework
Solution Approach 2:
The system uses feedback from the vehicle's operational state sensors to automatically activate or deactivate the fall-on-car detection function. When the vehicle transitions to stationary mode, the system receives feedback and activates the appropriate monitoring parameters, managing complexity through state-driven control
Data Source
AI summary
Systems include a controller programmed to instruct a sensor to detect an object in an environment of a vehicle in response to an activation of a fall-on-car prevention function, determine a first value of a parameter pertaining to the object at a first time with the sensor, determine a second value of the parameter pertaining to the object at a second time with the sensor, and automatically cause an action to occur based on a comparison of the first value of the parameter and the second value of the parameter.