Cloud Platform Emergency Event Detection via Vehicle Acceleration
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Solution Overview
Problem
In the field of automatic driving, there is a need to accurately and quickly determine the traveling states of surrounding vehicles to prevent traffic accidents, as existing methods are inadequate in analyzing video data to detect emergency events such as sudden braking or acceleration.
Innovation Solution
A method and apparatus that acquire video data from cameras in the road environment, detect target vehicles, calculate their acceleration, and determine if an emergency event occurs, enabling early warning systems to alert surrounding vehicles through a cloud control platform and edge computing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video data is analyzed to detect emergency events, then detection accuracy is improved, but processing time and system complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-defining emergency event types (emergency braking, emergency acceleration, etc.) and their corresponding detection criteria before actual analysis. This allows the system to quickly match video data features against pre-established patterns, reducing real-time processing time while maintaining high detection accuracy.
Solution Approach 2:
The video data analysis process is segmented into distinct modules: target vehicle detection, trajectory tracking, acceleration calculation, and emergency event judgment. Each module processes specific aspects independently, allowing parallel computation and reducing overall processing time while maintaining comprehensive detection capability.
2Area of stationary object
If multiple cameras are deployed to monitor road environment, then detection coverage is improved, but system complexity and cost increase
Solution Approach 1:
The cloud control platform serves multiple functions: it receives video data from multiple cameras, performs target detection, tracks trajectories, calculates accelerations, and identifies emergency events. This multi-functional approach consolidates what would otherwise require separate systems, reducing overall complexity while maintaining extensive detection coverage.
Solution Approach 2:
The cloud control platform acts as an intermediary between multiple camera systems and the emergency detection algorithm. It centralizes data processing and coordination, allowing the system to manage multiple cameras uniformly through standardized interfaces and protocols, thereby reducing operational complexity.
3Speed
If real-time acceleration calculation is performed, then response time is improved, but computational resources increase
Solution Approach 1:
The system performs acceleration calculation only for detected target vehicles that are deemed relevant to safety monitoring, rather than processing all possible objects in the video frames. This selective processing approach maintains fast response time for critical events while reducing overall computational resource consumption.
Data Source
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AI summary
An event detection method and apparatus, a device, and a computer storage medium are provided, which are related to intelligent transportation and automatic driving. In a specific implementation, a target vehicle located in a target area is detected according to a surveillance video of the target area; acquisition time for the target vehicle and location information of the target vehicle in image frames corresponding to the acquisition time are determined; an acceleration of the target vehicle is obtained according to at least the acquisition time and the location information; and it is judged whether an emergency event occurs for the target vehicle according to the acceleration of the target vehicle. The acceleration of the target vehicle calculated by the embodiments of the present disclosure has a high accuracy, so that a more accurate judgment result can be obtained when subsequently judging whether an emergency event occurs for the target vehicle.