STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY (20240273752). SYNCHRONIZING VEHICLE TELEMATICS DATA WITH INFRASTRUCTURE DATA PERTAINING TO A ROAD SEGMENT simplified abstract

SYNCHRONIZING VEHICLE TELEMATICS DATA WITH INFRASTRUCTURE DATA PERTAINING TO A ROAD SEGMENT

Organization Name

STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY

Inventor(s)

Alexander Cardona of Gilbert AZ (US)

Kip Wilson of Cave Creek AZ (US)

David Frank of Tempe AZ (US)

Phillip Michael Wilkowski of Gilbert AZ (US)

Nolan White of Chandler AZ (US)

SYNCHRONIZING VEHICLE TELEMATICS DATA WITH INFRASTRUCTURE DATA PERTAINING TO A ROAD SEGMENT - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240273752 titled 'SYNCHRONIZING VEHICLE TELEMATICS DATA WITH INFRASTRUCTURE DATA PERTAINING TO A ROAD SEGMENT

The patent application describes techniques for collecting, synchronizing, and displaying various types of data related to a road segment to enhance analysis of vehicle events, insurance claims, risk prediction, autonomous vehicle control, and data visualization.

• Enhanced analysis of vehicle events by synchronizing different data types collected from various sources.
• Enhanced analysis of insurance claims related to vehicle incidents at a road segment.
• Machine learning techniques for predicting risk levels for vehicle events or road segments.
• Techniques for considering region-specific driver profiles in controlling autonomous vehicles.
• Improved techniques for displaying collected data in a meaningful and contextualized manner.

Potential Applications: - Transportation and automotive industries - Insurance companies - Traffic management authorities - Autonomous vehicle technology developers

Problems Solved: - Lack of comprehensive data analysis for vehicle events and insurance claims - Difficulty in predicting risk levels accurately - Inefficient autonomous vehicle control without considering driver profiles - Ineffective data visualization methods

Benefits: - Enhanced decision-making based on comprehensive data analysis - Improved risk prediction for better safety measures - More efficient autonomous vehicle control - Enhanced user experience through improved data visualization

Commercial Applications: Title: Advanced Data Analysis and Visualization Technology for Transportation Industry This technology can be used by transportation companies, insurance firms, and autonomous vehicle developers to improve safety, efficiency, and decision-making processes.

Questions about the technology: 1. How does this technology improve the analysis of vehicle events compared to traditional methods? 2. What are the advantages of using machine learning for predicting risk levels in transportation scenarios?

Original Abstract Submitted

techniques for collecting, synchronizing, and displaying various types of data relating to a road segment enable, via one or more local or remote processors, servers, transceivers, and/or sensors, (i) enhanced and contextualized analysis of vehicle events by way of synchronizing different data types, relating to a monitored road segment, collected via various different types of data sources; (ii) enhanced and contextualized analysis of filed insurance claims pertaining to a vehicle incident at a road segment; (iii) advantageous machine learning techniques for predicting a level of risk assumed for a given vehicle event or a given road segment; (iv) techniques for accounting for region-specific driver profiles when controlling autonomous vehicles; and/or (v) improved techniques for providing a gui to display collected data in a meaningful and contextualized manner.