PATENT CLAIM ANALYSIS

Application Number: 15781108
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-12
Patent Classification: ["340", "439000"]

Abstract:
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) classifying said previous-trip driving data sets into collections corresponding to vehicle classes; c) classifying the current vehicle ( 100 ) into a current class; and d) calculating a performance parameter for the current trip based upon respective performance parameters for previous-trip driving data sets in said current collection; wherein the basic parameter set comprises vehicle velocity and engine rotation speed and/or motor load and energy consumption, and wherein the class-defining parameters comprise characteristic engine rotation speed per vehicle velocity and/or characteristic energy consumption per motor load. The invention also relates to a system.

Claim (Index 13):
System for automatically assessing performance of a driver of a current vehicle for a particular current trip, which system is arranged to repeatedly read updated current-trip driving data sets from the vehicle, which current-trip driving data sets each comprises data from at least a predetermined set of basic driving data parameters, wherein the system is arranged to read new such current-trip driving data sets from the vehicle at consecutive observation time points separated by at the most a predetermined observation time period, wherein the system comprises a server arranged to collect previous-trip driving data sets, observed at a plurality of different observation time points, for a plurality of different previous trips made by a plurality of different drivers and a plurality of different vehicles, which previous-trip driving data sets each comprises parameter values for at least a certain predetermined set of qualified driving data parameters in turn comprising the said basic parameter set and in particular instantaneous vehicle energy consumption, wherein the server is arranged to classify said previous-trip driving data sets into a set of collections, wherein each of said collections only comprises previous-trip driving data sets for a particular class of vehicles, wherein all previous-trip driving data sets of one and the same vehicle are classified into one and the same collection, based upon a basic class conformity measure between driving data sets for the vehicle in question and a set of class-defining parameters, wherein the server is arranged to classify the current vehicle into a particular current class based upon said basic class conformity measure, wherein in that the server is arranged to calculate an energy consumption-based trip performance parameter value for the current trip based upon respective energy consumption-based performance parameter values for previous-trip driving data sets in said current collection, wherein the said basic parameter set comprises instantaneous vehicle velocity and instantaneous engine rotation speed and/or the basic parameter set comprises instantaneous motor load and instantaneous energy consumption, and wherein the said class-defining parameters comprise, for each class of vehicles, a characteristic engine rotation speed for a particular vehicle velocity and/or a characteristic energy consumption for a particular motor load.

Metadata:
- Claim Count in Document: 4.0
- Percentile: 94.0
- Lexical Diversity: 2.12346
- Patent Class: 340.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15781109', '15781114', '15781113', '15781104', '15781101']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.7180098394669457
- 35 USC 102 Novelty (BERT): 0.5628533759082557
- Combined Prediction Score: 0.7024941931110767
- Mean Citation Score: 403.722256
- Max Citation Score: 409.8965
- Similarity Product: 395.6860254933834

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test