Driver Trip Performance Assessment Across Vehicle Types
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Solution Overview
Problem
Existing methods for assessing driving performance are inadequate as they rely on blunt measures like fuel consumption, which vary with vehicle type and conditions, and lack reliable data for many vehicles, making it difficult to compare drivers accurately.
Innovation Solution
A method and system that automatically assess driver performance by reading current-trip driving data sets every few seconds, mapping them to historic groups based on similarity and conformity, and calculating performance parameters using previous-trip data from multiple drivers and vehicles, without considering instantaneous energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fuel consumption is used to measure driving performance, then environmental impact can be tracked, but the measure is blunt and varies with vehicle type and conditions
Solution Approach 1:
The patent changes the measurement parameters from fuel consumption to multiple driving behavior parameters (acceleration, deceleration, speed, time) that can be precisely measured by vehicle sensors. This allows for more precise measurement of driving performance while accounting for different vehicle types and conditions through normalized evaluation criteria.
Solution Approach 2:
The patent creates a universal assessment system that works across different vehicle types (cars, trucks, buses) by using standardized driving parameters and normalized evaluation methods. The system can be applied to various vehicle categories while maintaining consistent measurement principles through the use of comparable behavioral metrics.
2Quantity of substance
If fuel consumption data is collected for all vehicles, then aggregate environmental impact can be calculated, but reliable data is not readily available for many vehicle types
Solution Approach 1:
The patent utilizes the vehicle's own existing sensors and onboard systems to collect driving data, eliminating the need for external fuel consumption monitoring equipment. The vehicle self-provides the necessary data through its standard sensor suite, ensuring both availability and reliability across all vehicle types.
Solution Approach 2:
The patent introduces a centralized server as an intermediary that collects, normalizes, and processes driving data from multiple vehicles. This intermediary system standardizes the data format and quality across different vehicle types, ensuring reliable aggregation of driving performance information.
3Measurement precision
If driving data is collected frequently to capture real-time performance, then assessment accuracy improves, but data processing complexity increases
Solution Approach 1:
The patent segments the continuous driving data into discrete evaluation intervals (e.g., per trip or per driving event). This segmentation reduces the complexity of processing continuous streams of data while maintaining sufficient accuracy for performance assessment by focusing on meaningful discrete units of driving behavior.
Solution Approach 2:
The patent extracts only the essential driving parameters needed for performance assessment (acceleration, deceleration, speed, time) from the full set of available vehicle data. This extraction approach reduces data processing complexity by focusing on the most relevant metrics while maintaining assessment accuracy.
Data Source
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AI summary
Method for automatically assessing performance of a driver (110) of a vehicle (100) for a particular trip, wherein current driving data sets, comprising basic driving data are repeatedly read from the vehicle, which method comprises the steps a) collecting previous-trip driving data sets, comprising instantaneous vehicle energy consumption, for different previous trips, different drivers and different vehicles; b) for each of said current-trip driving data sets, selecting a corresponding previous-trip data set; c) calculating the value of said second trip performance parameter based upon the respective values of a first trip performance parameter for each of said selected previous-trip driving data sets, which first trip performance parameter is calculated for the previous-trip data set in question as a relative trip performance of the previous-trip data set in question in relation to the trip during which the previous-trip data set was observed. The invention also relates to a system.