Fleet Vehicle Position Data Analytics for Behavior Metrics
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Solution Overview
Problem
Efficiently managing fleet vehicle usage is cumbersome and costly due to inefficient and unauthorized use, as existing methods lack effective tracking and analysis of vehicle routes, driving behavior, and productivity.
Innovation Solution
A system that analyzes geographic position data from fleet vehicles using data collection devices and analytics servers to determine behavior metrics, such as job-related vs. non-job-related stops, driving efficiency, and worker productivity, providing insights through reports and dashboards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If geographic position data is collected and analyzed from fleet vehicles, then vehicle usage efficiency and productivity can be improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system segments the fleet management process into distinct functional modules: data collection devices in vehicles, wireless communication interfaces, servers for data reception and storage, and client devices for analysis and reporting. Each module handles specific tasks independently, reducing overall system complexity while enabling comprehensive vehicle tracking and analysis.
Solution Approach 2:
The patent introduces wireless communication interfaces and server systems as intermediaries between data collection devices and client devices. These intermediaries facilitate data transmission and processing, allowing the system to handle large volumes of geographic position data without requiring direct complex connections between all system components.
2Reliability
If comprehensive tracking of vehicle routes and driving behavior is implemented, then unauthorized use can be detected, but data processing time and computational resources increase
Solution Approach 1:
The system performs preliminary data collection and storage at multiple levels (local devices, wireless interfaces, and servers) as data is generated. Geographic position data is continuously collected and pre-processed in the background, allowing for rapid analysis and detection of unauthorized use when needed without requiring real-time processing of all historical data.
Solution Approach 2:
The system implements feedback mechanisms where client devices continuously receive and analyze geographic position data, comparing actual vehicle routes against authorized routes. This continuous feedback loop enables real-time detection of deviations indicating unauthorized use, while the system only processes relevant anomaly data intensively rather than all data continuously.
3Loss of information
If detailed behavior metrics such as job-related stops and driving efficiency are analyzed, then productivity insights can be obtained, but measurement and analysis complexity increase
Solution Approach 1:
The server system and client devices are designed to perform multiple functions: storing geographic position data, analyzing driving behavior patterns, identifying job-related stops, calculating efficiency metrics, and generating various types of reports. This multi-functional approach consolidates complex analysis capabilities into unified systems, reducing the need for separate specialized tools for each type of metric analysis.
Data Source
AI summary
A device may receive multiple position data records. Each of the multiple position data records may identify a geographic position of a vehicle at a particular time. The device may determine, based on the multiple position data records: a first set of time periods during which the vehicle is in motion, and a second set of time periods during which the vehicle is not in motion; determine, based on behavior analysis data, a first type of motion associated with the first set of time periods and a second type of stop associated with the second set of time periods to form behavior metrics; and output the behavior metrics.