Vehicle Fleet Hazard Zone Detection via Centralized Hotspot Analysis
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Solution Overview
Problem
Existing methods fail to effectively identify and address potential hazard zones in road traffic before accidents occur, relying on post-incident analysis which is ineffective in preventing fatalities and near-misses, and are limited by manual observation and insufficient data collection.
Innovation Solution
A method and device that utilize a fleet of vehicles connected to a central computer unit to detect incidents with environmental sensors, transmit geolocated data, and analyze patterns to identify and visualize potential hazard zones, providing contextual information and warnings to vehicles and authorities to proactively address critical situations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a fleet of vehicles continuously captures and transmits incident data to a central computer unit, then the quantity and quality of data for identifying hazard zones is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The system segments data collection and processing across multiple vehicles (distributed sensors) while using a central computer unit for aggregated analysis. Each vehicle independently captures incidents with its environmental sensors, and the central unit processes the segmented data streams to identify hotspots and hazard zones, resolving the complexity through distributed architecture.
Solution Approach 2:
The central computer unit acts as an intermediary between the fleet of vehicles and the hazard zone identification process. It receives, aggregates, and processes incident data from multiple vehicles, then generates hotspot information that is transmitted back to vehicles. This intermediary structure manages the complexity of processing large quantities of data from multiple sources.
2Measurement precision
If contextual information is added to transmitted incidents and hotspots are analyzed, then the measurement precision and reliability of hazard zone identification is improved, but the processing time and computational requirements increase
Solution Approach 1:
The system performs preliminary actions by continuously collecting and pre-processing incident data with contextual information (geolocation, time, environmental conditions) before hazard zones are identified. The central computer unit maintains a database of incidents with contextual data, so when analyzing for hotspots, the precision is improved without requiring real-time processing of all raw data, thus reducing processing time.
Solution Approach 2:
The patent replaces manual observation and analysis with automated electronic data processing. Environmental sensors in vehicles automatically capture incidents with contextual information, and the central computer unit uses automated algorithms to analyze patterns and identify hotspots, significantly improving precision while reducing the time required compared to manual methods.
3Speed
If hotspots are transmitted rapidly to vehicles near hazard zones, then the speed of warning delivery is improved, but the data transmission requirements and system complexity increase
Solution Approach 1:
The system applies local quality by transmitting hotspot warnings selectively to only those vehicles that are near identified hazard zones, rather than broadcasting to all vehicles in the fleet. The central computer unit determines which vehicles require warnings based on their current locations and the identified hotspots, improving warning delivery speed to relevant vehicles while reducing unnecessary data transmission and system complexity.
4Reliability
If the system identifies and warns about potential hazard zones before accidents occur, then the reliability of accident prevention is improved, but the risk of false positives and unnecessary warnings increases
Solution Approach 1:
The system implements feedback mechanisms where incident data is continuously collected, analyzed, and used to identify hotspots, which then generate warnings to vehicles. The system monitors the effectiveness of warnings and uses this feedback to refine hotspot identification criteria, improving reliability while reducing false positives by learning from actual outcomes and adjusting the sensitivity of hazard zone detection.
Data Source
AI summary
A method for identifying potential hazard zones in road traffic by vehicles connected to a central computer unit involves recording an incident indicative of a potential hazard zone and transmitting it to the central computer unit with its geolocation. The transmitted incident is listed as a hotspot in a digital map if there are a large number of similar incidents with the same geolocation. Contextual information is added to the transmitted incident. The hotspot is analyzed for the identification of a potential hazard zone, a current hotspot is compared with confirmed hotspots, the hotspots are visualized on a platform, with a geolocation of a hotspot-confirmed traffic critical incident being transmitted to an authority to be checked and/or as a warning message to a vehicle currently near such an analyzed hotspot.