Vehicle Mobility Index from Acceleration Signals for Driving Aggressiveness
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems lack a comprehensive method to determine the aggressiveness of vehicle operation based on fluctuations in speed, brakes, and cornering, which is crucial for predicting warranty claims and understanding vehicle usage patterns.
Innovation Solution
A system that utilizes sensors to collect data on longitudinal and lateral acceleration, filters it using an interquartile range, and calculates a mobility index to assess the aggressiveness of vehicle handling, incorporating machine learning and blockchain technology for data management and authorization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If systems focus only on harsh events to assess vehicle operation, then the assessment is simple, but it lacks comprehensive understanding of overall operation dynamics
Solution Approach 1:
The patent segments the continuous acceleration signal into discrete operational phases (acceleration, deceleration, steady-state) and further segments the assessment into multiple dimensions (longitudinal, lateral, vertical). This segmentation enables comprehensive analysis of all operation dynamics while maintaining systematic organization, resolving the contradiction between information completeness and system complexity.
Solution Approach 2:
The patent transitions from traditional single-dimension harsh event assessment to multi-dimensional analysis by incorporating longitudinal acceleration, lateral acceleration, and vertical acceleration simultaneously. This dimensional expansion provides comprehensive operation understanding without proportionally increasing complexity, as the same sensor data is analyzed across multiple dimensions.
2Measurement precision
If systems use detailed sensor data to determine aggressiveness, then measurement precision improves, but processing complexity increases
Solution Approach 1:
The patent changes the parameter representation by transforming raw acceleration data into operational phase classifications and mobility indices. Instead of processing continuous raw signals directly, the system converts them into discrete phases (acceleration, deceleration, steady-state) and aggregated mobility indices, maintaining measurement precision while reducing processing complexity through parameter transformation.
Solution Approach 2:
The patent introduces mobility indices as intermediary variables between raw sensor data and aggressiveness assessment. These indices serve as mediators that condense complex multi-dimensional acceleration patterns into single representative values, enabling precise aggressiveness measurement without requiring direct processing of all raw sensor details.
3Reliability
If systems analyze overall operation dynamics beyond harsh events, then prediction accuracy for maintenance needs improves, but computational requirements increase
Solution Approach 1:
The patent performs preliminary classification of operational phases and calculation of mobility indices during normal vehicle operation, before maintenance decisions are needed. By pre-processing and organizing the data into meaningful categories and aggregated metrics, the system enables accurate maintenance prediction without requiring intensive computational power at the moment of decision-making.
Data Source
AI summary
An example operation includes one or more of sensing from at least one sensor, a longitudinal acceleration and a lateral acceleration, receiving from the at least one sensor, a longitudinal acceleration signal based on the longitudinal acceleration and a lateral acceleration signal based on the lateral acceleration, filtering via at least one logic, the longitudinal acceleration signal and the lateral acceleration signal based on an interquartile range of the longitudinal acceleration signal and the lateral acceleration signal, yielding a plurality of filtered signals and determining via the at least one logic, a mobility index of a transport based on the filtered signals.