Cloud Vehicle Hazard Detection via Segmented Data Processing
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Solution Overview
Problem
Current systems lack effective methods for detecting and identifying vehicles engaging in dangerous driving behaviors and accidents in real-time, especially in cloud-based environments, which hinders timely intervention and safety measures.
Innovation Solution
A cloud-based detection system that collects and analyzes position and motion data from multiple vehicles to identify collisions, hazardous driving behaviors, and endangered vehicles, issuing warnings and reports to relevant agencies and services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud-based detection systems collect and analyze position and motion data from multiple vehicles, then detection capability and safety monitoring are improved, but data processing complexity and computational requirements increase
Solution Approach 1:
The system segments the detection process by creating separate detection modules for different hazard types (collision detection module, hazardous driving behavior detection module, endangered vehicle identification module). Each module processes specific aspects of vehicle data independently, reducing overall processing complexity while maintaining comprehensive detection capability
Solution Approach 2:
The patent introduces a cloud-based data center as an intermediary that receives, stores, and processes position and motion data from multiple vehicles. This centralized intermediary handles the computational complexity remotely, allowing individual vehicle systems to remain simple while achieving sophisticated collective detection capabilities
2Loss of time
If real-time detection and warning systems are implemented, then response time and safety intervention are improved, but system complexity and computational load increase
Solution Approach 1:
The system performs preliminary actions by continuously collecting and pre-processing position and motion data from vehicles, maintaining ready-to-analyze data buffers in the cloud. When potential hazards are detected through simple threshold comparisons, warnings are immediately issued without requiring complex real-time computation, thus achieving fast response with minimal system complexity
Solution Approach 2:
Vehicles autonomously collect their own position and motion data using onboard sensors and transmit it to the cloud system. The system automatically detects hazards by comparing data patterns against predefined criteria and issues warnings without human intervention, reducing the need for complex centralized control while maintaining real-time monitoring capabilities
Data Source
AI summary
A system for identifying hazardous driving behaviors is presented. Position and motion data from a plurality of vehicles are uploaded to a data center. For each vehicle, the system computes a set of hazard metric for identifying hazardous driving behaviors based on the position and motion information received from the plurality of vehicles. A hazardous vehicle is identified based on the computed hazard metric for the plurality of vehicles. The system reports a set of information regarding the hazardous vehicle to an agency.