Connected Device Collision Prevention via Trajectory Analysis
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Solution Overview
Problem
Current connected devices primarily facilitate post-collision reporting rather than proactive collision prevention, lacking the capability to anticipate and communicate potential collisions to prevent them.
Innovation Solution
A collision prevention system that utilizes a communication interface to gather information from connected devices and additional sources, processes this information to estimate potential collisions, and issues alerts to connected devices to prevent incidents, incorporating features like digital map development, weather, infrastructure, and user classification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If connected devices are used for post-collision reporting, then collision information can be communicated after an accident occurs, but the system cannot anticipate or prevent collisions before they happen
Solution Approach 1:
The system performs preliminary actions by continuously monitoring connected devices' location, speed, and trajectory data to predict potential collision paths before collisions occur. The central controller analyzes this data proactively to identify vehicles on conflicting paths and issues warnings in advance, enabling drivers to take preventive action rather than merely reporting after the fact.
Solution Approach 2:
The system implements feedback by continuously receiving real-time data from connected devices, analyzing collision risk, and sending alert messages back to the relevant vehicles. This closed-loop feedback mechanism allows the system to monitor the situation dynamically and provide ongoing guidance to drivers to avoid collisions.
2Reliability
If the system monitors all connected devices to predict collisions, then collision prevention capability improves, but system complexity and data processing requirements increase
Solution Approach 1:
The system segments the monitoring task by focusing only on connected devices that are determined to be road users based on their movement patterns and location data. Rather than processing data from all connected devices uniformly, the system identifies and tracks only those devices exhibiting road user behavior characteristics, reducing unnecessary computational overhead.
Solution Approach 2:
The system applies partial action by selectively analyzing data from devices classified as road users rather than all connected devices. The classification mechanism filters the dataset to include only relevant entities (vehicles, pedestrians, cyclists in motion), avoiding the complexity of processing stationary or irrelevant devices while maintaining comprehensive collision prediction coverage for actual road users.
3Reliability
If the system issues alerts to all connected devices, then collision prevention coverage is maximized, but false alarms and unnecessary alerts increase
Solution Approach 1:
The system applies local quality by issuing alerts selectively only to the specific connected devices that are determined to be at risk of collision, rather than broadcasting to all devices. The central controller identifies the precise vehicles involved in the potential collision scenario and targets warnings only to those entities, ensuring relevant information reaches the right users without causing unnecessary alarm to others.
Data Source
AI summary
A method of performing collision prevention and a system to perform collision prevention involve a communication interface to receive information from connected devices of individuals. The system also includes a processor to obtain the information from the connected devices, estimate a potential for an upcoming collision, and issue an alert based on the potential for the upcoming collision to one or more of the connected devices.