Telematics Device Accident Data Segmentation
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Solution Overview
Problem
Delivery services and other transportation businesses face challenges in assessing driver safety and accident liability due to the lack of effective systems for collecting and analyzing data on vehicle operations and driver behaviors, which increases accident risks and liabilities.
Innovation Solution
A system and method for evaluating driver safety and accident conditions by capturing and processing telematics data, including vehicle dynamics and contextual data, using a telematics device that stores and transmits data to a central server for analysis, allowing for the determination of accident times and conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is captured at higher frequency for accident reconstruction, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments data storage into two distinct memory types: a first memory for continuous high-frequency accident data capture and a second memory for periodic lower-frequency operational data storage. This segmentation allows the system to maintain high measurement precision for accident reconstruction while managing device complexity through differentiated storage strategies.
Solution Approach 2:
The system performs preliminary action by continuously capturing and storing high-frequency accident-related data in the first memory in advance of any accident event. This ensures that when an accident occurs, precise data is already recorded and ready for analysis, eliminating the need for complex real-time processing during the actual accident event.
2Reliability
If continuous high-frequency data is stored in memory, then reliability of accident data is improved, but loss of substance increases due to memory constraints
Solution Approach 1:
The patent divides memory resources into two segments: a first memory dedicated to storing high-frequency accident data continuously, and a second memory for storing lower-frequency operational data. This segmentation ensures that critical accident data reliability is maintained without exhausting overall memory capacity, as each memory type serves its specific purpose with appropriate storage demands.
Solution Approach 2:
The system applies local quality by assigning different storage characteristics to different memory regions: the first memory is optimized for high-frequency, short-duration accident data with continuous overwrite capability, while the second memory handles periodic operational data. This localized optimization ensures reliable accident data capture without unnecessarily consuming total memory resources.
3Measurement precision
If multiple sets of data are captured and stored, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent segments data capture into two distinct modes: continuous high-frequency capture for accident events and periodic lower-frequency capture for operational monitoring. Each mode writes to its designated memory type, simplifying data management by avoiding the complexity of managing a single unified high-frequency data stream while still achieving high measurement precision when accidents occur.
Solution Approach 2:
The system employs periodic action by capturing operational data at regular intervals in the second memory, while maintaining the capability for continuous high-frequency capture in the first memory when accidents occur. This periodic approach to operational monitoring reduces overall data management complexity compared to continuous high-frequency capture for all data types, while preserving accident reconstruction accuracy.
Data Source
AI summary
According to various embodiments, systems and methods are provided for capturing vehicle activity data and filtering such data to reconstruct accident conditions according to a predetermined level of accuracy.