Vehicle Impact Data Retrieval via Inter-Vehicle Communication
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Solution Overview
Problem
Current vehicle systems face limitations in analyzing accidents using only image data from a single vehicle, as they often require immediate data from other vehicles, which may not be readily available, especially when the accident vehicle's plate number is unknown.
Innovation Solution
A vehicle system equipped with a transceiver, acceleration sensor, camera, and controller that communicates with other vehicles to request and receive accident-related data, including image data and plate numbers, using image processing to identify the involved vehicles and transmit relevant information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If image data from other vehicles is requested immediately after accident, then the ability to obtain accident data is improved, but the system complexity increases due to inter-vehicle communication requirements
Solution Approach 1:
The system performs preliminary actions by detecting accidents through acceleration sensors before formal data exchange occurs. The accident detection trigger is prepared in advance, so when an accident occurs, the system can immediately initiate data requests without delay, resolving the contradiction between immediate data availability and system complexity.
Solution Approach 2:
The system uses its own acceleration sensor data to trigger the data request process autonomously. The vehicle's own accident detection capability serves as the trigger mechanism, eliminating the need for external initiation signals and reducing communication overhead while ensuring timely data exchange.
2Measurement precision
If image processing is performed to identify plate numbers, then the precision of vehicle identification is improved, but the time required to obtain identification information increases
Solution Approach 1:
The system performs partial image processing by focusing only on identifying the plate number region rather than analyzing the entire image. This selective approach maintains high identification accuracy while significantly reducing processing time compared to comprehensive image analysis.
Solution Approach 2:
The system extracts only the essential plate number information from the image data using image processing, rather than analyzing complete vehicle details. This extraction of critical information maintains identification precision while minimizing processing time requirements.
3Reliability
If radar data is integrated with image data for impact direction determination, then the reliability of accident analysis is improved, but the device complexity and energy consumption increase
Solution Approach 1:
The system uses partial sensor fusion by combining radar and camera data only when impact direction determination is required, rather than continuously operating all sensors. This selective integration maintains high reliability for critical analysis while reducing overall energy consumption of the sensor system.
Data Source
AI summary
A vehicle includes: a transceiver configured to communicate with another vehicle; an acceleration sensor configured to detect an impact of the vehicle; a camera configured to acquire first image data of an external field of view of the vehicle; and a controller configured to determine whether an impact of the vehicle with a first vehicle has occurred based on an output value of the acceleration sensor, perform image processing for the first vehicle that generated the impact of the vehicle based on the first image data when is the controller determines that the impact of the vehicle has occurred, and to control the transceiver to request the another vehicle for second image data corresponding to an occurrence time of the impact of the vehicle when the plate number of the first vehicle is not identified based on the image processing.