Vehicle Weather Data Mapping for Real-Time Road Ice Hazards
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Solution Overview
Problem
Existing systems for determining road hazards, such as ice, rely on central weather data and are not suited to handle rapidly changing weather conditions, leading to inadequate prediction and safety for vehicles.
Innovation Solution
A method where vehicles collect and transmit weather data, including temperature and rain information, to a cloud server, which aggregates and analyzes this data to set hazard flags for geographic regions, enabling vehicles to adjust their operation and road treatment systems to address potential ice hazards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If central weather data is used to determine road hazards, then the system structure is simple, but the ability to handle rapidly changing weather conditions deteriorates
Solution Approach 1:
The patent segments the weather monitoring system into multiple distributed vehicle-based sensors across different geographic regions, each independently collecting and transmitting local weather data. This segmentation allows the system to capture rapidly changing local conditions while maintaining overall system simplicity through modular architecture.
Solution Approach 2:
The patent transitions from a single centralized weather data source to a multi-dimensional distributed network of vehicle sensors. By adding the spatial dimension of multiple measurement points across different locations, the system gains the ability to detect and respond to rapidly changing local weather conditions while maintaining manageable complexity through standardized data collection protocols.
2Measurement precision
If vehicles collect and transmit weather data to cloud server, then real-time hazard detection capability is improved, but data aggregation and processing complexity increases
Solution Approach 1:
Vehicles perform preliminary weather data collection and transmission in advance, sending temperature, rain, and location data to the cloud server before hazards fully develop. This preliminary action allows the server to aggregate and analyze data proactively, improving real-time hazard detection while distributing processing complexity across the network rather than concentrating it in one location.
Solution Approach 2:
The system implements feedback loops where vehicles receive hazard information from the cloud server and adjust their operations accordingly. This feedback mechanism improves measurement precision by continuously refining hazard detection based on aggregated data from multiple vehicles, while the automated feedback process helps manage processing complexity through standardized response protocols.
3Reliability
If hazard flags are set for geographic regions based on aggregated vehicle data, then location-specific safety is improved, but data storage and processing requirements increase
Solution Approach 1:
The patent applies local quality by setting hazard flags specifically for geographic regions where conditions warrant them, rather than applying uniform hazard assessments across all areas. Each region's hazard status is determined by local vehicle sensor data, improving location-specific safety while minimizing data storage requirements by only processing and storing data for regions with detected hazards.
Solution Approach 2:
The system uses parameter changes by monitoring temperature and rain conditions to dynamically adjust hazard flag states. When temperature drops below freezing or rain is detected in combination with low temperatures, the system changes the hazard parameter from normal to hazardous, enabling efficient data processing by focusing computational resources on regions where parameter changes indicate potential ice formation.
Data Source
AI summary
Systems, methods, and apparatus related to determining ice hazards on roads based on crowdsourced data from vehicles. In one approach, a server receives weather data and location data from each of several vehicles. The weather data is timestamped when received. The server determines, using the location data, a geographic region in which each vehicle is located. The weather data is stored in a database associated with the respective geographic region for the vehicle that transmitted the weather data. The server periodically scans the database to select weather data received over a selected time period. The selected data is analyzed to determine whether an ice hazard exists for one or more regions. A communication is sent to vehicles in those regions having the determined ice hazard.