Traffic Accident Identification Model Using Multi-Source Feature Fusion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional methods for identifying traffic accidents are limited by low coverage rates and poor timeliness, relying on manual reporting which often results in incomplete and delayed information, failing to provide accurate and timely assistance to drivers.
Innovation Solution
A method and apparatus that utilize pre-trained models to identify traffic accidents by acquiring and processing road features, environmental features, and road traffic stream features, enabling automatic and timely detection with higher coverage rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual reporting methods are used to identify traffic accidents, then device complexity is reduced, but timeliness and coverage rate deteriorate
Solution Approach 1:
The patent replaces manual reporting mechanisms with an automated electronic identification system that collects and processes traffic data through electronic sensors, communication networks, and computational algorithms. This substitution of mechanical/manual processes with electronic automation directly improves timeliness while accepting increased system complexity as a necessary trade-off for achieving real-time accident detection and notification.
2Reliability
If manual reporting methods are used to identify traffic accidents, then device complexity is reduced, but coverage rate deteriorates
Solution Approach 1:
The patent replaces manual reporting with comprehensive electronic data collection from multiple sources including sensors, communication networks, and processing systems. This electronic substitution enables continuous monitoring and broader coverage of traffic conditions, ensuring more complete accident detection while requiring complex integrated systems to manage multiple data sources and processing operations.
3Loss of information
If traditional manual reporting is used, then information completeness is poor, but system simplicity is maintained
Solution Approach 1:
The patent merges multiple data collection sources including electronic sensors, communication networks, and processing systems into an integrated accident identification system. This consolidation of multiple information sources improves the completeness and accuracy of accident data while managing system complexity through unified architecture and coordinated operation of integrated components.
Data Source
AI summary
A method and apparatus for identifying a traffic accident, a device and a computer storage medium are disclosed, which relates to the technical fields of intelligent traffic and big data. An implementation includes: acquiring road features, environmental features and road traffic stream features; inputting the road features, the environmental features and the road traffic stream features into a pre-trained traffic-accident identifying model to obtain an accident-information identifying result of a road which at least includes an accident identifying result. In the present application, the accident road may be automatically identified according to the road features, the environmental features and the road traffic stream features. Compared with a traditional manual reporting way, timeliness is stronger, and a coverage rate is higher.