Vehicle Falling Load Detection Using Depth Image Analysis
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Solution Overview
Problem
Existing vehicle systems with Adaptive Cruise Control (ACC) fail to immediately detect a fallen load, leading to a high probability of collision when the inter-vehicle distance is short.
Innovation Solution
A falling object detection apparatus installed in a vehicle, comprising an acquisition unit to capture depth images of a preceding vehicle and its surroundings, a determination unit to assess movement differences, and a detection unit to identify a fallen load based on these images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a camera is used to detect stationary objects for ACC control, then the system can identify loads between vehicles, but it cannot immediately detect when a load falls from a preceding vehicle
Solution Approach 1:
The patent combines depth image data from a depth sensor with optical flow data from a camera to create a comprehensive detection system. The depth information provides accurate spatial positioning while optical flow detects motion patterns, together enabling immediate fall detection that neither sensor could achieve alone
Solution Approach 2:
The system continuously captures depth images and calculates optical flow in advance, maintaining ready-to-use data streams. This preliminary action ensures that when a load falls, the system can immediately compare current data against previous frames without waiting for new sensor acquisitions, reducing detection latency
2Productivity
If the inter-vehicle distance is short, then the ACC function operates efficiently, but the vehicle has insufficient time to react to a fallen load
Solution Approach 1:
The system continuously processes depth images and optical flow data without interruption, maintaining constant monitoring of the space between vehicles. This continuous action ensures that falls at any distance are detected immediately, eliminating the reaction time problem that plagues intermittent or event-triggered detection systems
3Device complexity
If only stationary object detection is implemented, then the system simplifies ACC control, but it fails to detect the dynamic event of a load falling
Solution Approach 1:
The patent introduces optical flow analysis to detect dynamic motion patterns in addition to static object detection. By analyzing pixel displacement between consecutive depth images, the system identifies the characteristic motion of falling objects while maintaining relatively simple implementation using existing sensor data
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables immediate detection of a fallen load, allowing the vehicle to avoid collisions by determining movement differences using depth images and distance information from sensors like millimeter wave sensors.
Implementation Method 1
an acquisition unit to acquire a depth image of a second vehicle, on which a load is mounted and which is traveling in front of the first vehicle
Implementation Method 2
a determination unit to determine whether the load has not made a movement different from a movement of the second vehicle, using the depth image acquired by the acquisition unit
Data Source
AI summary
An acquisition unit of a falling object detection apparatus installed and used in a first vehicle acquires a depth image of a second vehicle, on which a load is mounted and which is traveling in front of the first vehicle, and of the area around the second vehicle. A determination unit of the falling object detection apparatus determines whether the load has not made a movement different from that of the second vehicle, using the depth image acquired by the acquisition unit. A detection unit of the falling object detection apparatus detects a fall of the load based on a result of determination by the determination unit.