Cargo-Falling Prediction for Preceding Vehicles
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Solution Overview
Problem
Existing driving assistance systems fail to predict and warn drivers about falling cargo from preceding vehicles in a timely manner, potentially endangering both the subject vehicle and oncoming vehicles, and do not account for the risk to saddle-ridden type vehicles.
Innovation Solution
A driving assistance device equipped with an imaging unit, a cargo-falling predicting unit, and an information providing unit that continuously monitors the cargo on a preceding vehicle, predicts potential falls based on changes in the cargo's profile or accompanying objects' appearance, and alerts relevant vehicles to improve preventive safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a falling object is detected only after it crosses the horizontal line set with reference to the loading platform, then the detection system is simple, but the driver cannot avoid the falling cargo in time
Solution Approach 1:
The system performs preliminary detection by monitoring cargo position before it actually falls. The cargo position monitoring unit continuously tracks the cargo's location on the loading platform, and the falling determination unit predicts potential falls by analyzing position changes relative to the vehicle's acceleration and curvature. This preliminary monitoring enables early warning to the driver before the cargo actually detaches and falls, providing sufficient time for avoidance maneuvers.
2Device complexity
If the driver monitors falling objects manually, then the detection system is simple, but the driver burden increases and reaction time is delayed
Solution Approach 1:
The system performs self-monitoring of cargo position without requiring driver intervention. The cargo position monitoring unit automatically tracks cargo location, the vehicle state acquisition unit continuously obtains acceleration and curvature data, and the falling determination unit autonomously predicts potential falls. The warning output unit then notifies the driver of predicted falling events. This automated self-service approach eliminates the need for manual driver monitoring while providing timely warnings.
3Measurement precision
If cargo falling is detected only after it occurs, then the detection accuracy is high for actual falls, but preventive safety is reduced
Solution Approach 1:
The system continuously monitors cargo position and compares it against predicted safe positions based on vehicle state (acceleration, curvature). The falling determination unit receives feedback from both the cargo position monitoring unit and the vehicle state acquisition unit, analyzing whether cargo position changes are consistent with normal vehicle operation or indicate impending failure. This feedback mechanism enables accurate prediction of falling events before they occur, maintaining high detection accuracy while enabling preventive safety measures.
Data Source
AI summary
There is provided a driving assistance device configured to be equipped in a subject vehicle. An imaging unit is configured to acquire an image of a preceding vehicle running in front of the subject vehicle equipped with the driving assistance device. A cargo-falling predicting unit is configured to predict whether a cargo loaded on a loading platform of the preceding vehicle will fall off, from change with time in an image of the cargo or an image of an accompanying object of the cargo on the basis of the image acquired by the imaging unit. An information providing unit is configured to provide information on falling of the cargo if the cargo-falling predicting unit predicts that the cargo will fall off.