# US 10,501,089 B2 · Method and system for assessing the trip performance of a driver > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,501,089 B2 - Document ID: US10501089B2 - Status: Granted - Kind: B2 - Application number: 15/781,113 - Filed: 2016-12-15 - Published: 2018-10-18 - Granted: 2019-12-10 - Earliest claimed: 2015-12-15 - Assignees: Greater Than AB - Applicants: Greater Than S.A. - Inventors: Anders Lindelöf - Web page: https://patentgrep.com/patent/US10501089B2 ## CPC - B60W 40/09: Driving style or behaviour - G07C 5/008: {communicating information to a remotely located station (transmission systems for measured values G08C)} - G07C 5/02: Registering or indicating driving, working, idle, or waiting time only (apparatus forming part of taximeters G07B13/00) - G07C 5/08: Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time - B60W 2050/0065: {using a personalised data carrier, e.g. magnetic card, memory card or electronic ignition key} - B60W 2510/0638: Engine speed - B60W 2520/10: Longitudinal speed - B60W 2530/00: Input parameters relating to vehicle conditions or values, not covered by groups B60W2510/00 or B60W2520/00 - B60W 2556/10: Historical data - B60W: CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT - G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE ## 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) grouping said previous-trip driving data sets into basic historic groups and calculating a respective group performance parameter; c) further grouping said previous-trip driving data sets into extended historic groups; d) mapping each current-trip data set to said extended historic groups; and e) calculating a current-trip performance parameter based upon the group performance parameter values of the respective basic historic groups corresponding to previous-trip driving data sets comprised in the extended historic group to which a current-trip data set was matched in step d. The invention also relates to a system. ## Claims ### Claim 1 A method for automatically assessing performance of a driver of a current vehicle for a particular current trip, wherein updated current-trip driving data sets are repeatedly read from the vehicle, the current-trip data sets each comprises data from at least a predetermined set of extended driving data parameters, wherein new such current-trip data sets are read from the vehicle at consecutive observation time points separated by at the most a predetermined observation time period, wherein the method comprises the steps of: a) collecting 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, the previous-trip data sets each comprises parameter values for both said set of extended driving data parameters and a predetermined set of a qualified parameter set, the qualified parameter set comprises the parameters of a basic parameter set and instantaneous vehicle energy consumption; b) grouping said previous-trip driving data sets into basic historic groups of such sets, based upon a basic driving data set similarity measure, the basic similarity measure is arranged to take values for said basic parameter set into consideration, and calculating the value of a respective group performance parameter for each such basic historic group; c) further grouping said previous-trip driving data sets into extended historic groups of such sets, based upon an extended driving data set similarity measure, the extended similarity measure is arranged not to take all values for said basic parameter set into consideration that are taken into consideration by the basic similarity measure; d) for each of said current-trip data sets, mapping the current-trip data set in question to at the most one particular of said extended historic groups, based upon an extended group conformity measure between a driving data set and an extended historic group; and e) calculating a current-trip performance parameter based upon the group performance parameter values of respective basic historic groups corresponding to previous-trip driving data sets comprised in the extended historic group to which a current-trip data set was matched in step d. ### Claim 2 (depends on 1) The method according to claim 1, wherein the current-trip driving data sets do not comprise said basic parameter set. ### Claim 3 (depends on 1) The method according to claim 1, wherein said group performance parameter is calculated based upon a respective relative instantaneous vehicle energy consumption value for the previous-trip driving data sets comprised in the basic historic group in question, wherein the relative instantaneous energy consumption value in question is calculated in relation to a total energy consumption for the complete trip during which the previous-trip driving data set in question was observed. ### Claim 4 (depends on 3) The method according to claim 3, wherein the current-trip performance parameter is calculated based upon an average value of said relative instantaneous energy consumption values for said matched respective basic historic groups. ### Claim 5 (depends on 1) The method according to claim 1, wherein the basic parameter set comprises instantaneous vehicle velocity, wherein the method further comprises a step in which, for said basic historic groups, a characteristic vehicle velocity function is calculated regarding the value of said relative instantaneous vehicle energy consumption for different vehicle velocity parameter values, and wherein the current-trip performance parameter value is further calculated based upon a weighting of said relative instantaneous energy consumption values using said characteristic vehicle velocity function. ### Claim 6 (depends on 1) The method according to claim 1, wherein the method further comprises the steps of classifying 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; classifying the current vehicle into a particular current class of said set of classes based upon said basic class conformity measure; wherein the current-trip performance parameter value is calculated based upon only the respective relative instantaneous vehicle energy consumption values for previous-trip driving data sets in said current collection. ### Claim 7 (depends on 6) The method according to claim 6, wherein the basic parameter set comprises instantaneous vehicle velocity and instantaneous engine rotation speed, and wherein the class-defining parameters comprise, for each class of vehicles, a characteristic engine rotation speed for a particular vehicle velocity. ### Claim 8 (depends on 1) The method according to claim 1, wherein the extended parameter set comprises at least one parameter from a parameter list comprising GPS-based velocity, GPS-based acceleration, altitude, accelerometer-based acceleration and compass-based heading. ### Claim 9 (depends on 8) The method according to claim 8, wherein at least one of said current-trip driving data set values are either registered by the current vehicle, the current vehicle is connected to a central server via a wireless connection, or registered by a portable device arranged in the current vehicle, the portable device is connected using a wireless connection to the central server. ### Claim 10 (depends on 1) The method according to claim 1, wherein the current vehicle is not arranged to automatically provide driving data information via an external interface. ### Claim 11 (depends on 1) The method according to claim 1, wherein said predetermined observation time period is at the most 10 seconds, preferably at the most 5 seconds, more preferably at the most 2 seconds. ### Claim 12 (depends on 1) The method according to claim 1, wherein the current-trip performance parameter value is either communicated, via a wireless link, from a central server to a portable electronic device arranged at the current vehicle, and presented to the driver, or communicated, via a wireless link, directly from the vehicle to said central server. ### Claim 13 (depends on 12) The method according claim 12, wherein a value of the current-trip performance parameter is calculated repeatedly, preferably at least every 10 minutes, more preferably at least every 2 minutes, more preferably at least every 30 seconds, during the current trip. ### Claim 14 (depends on 1) The method according to claim 1, wherein each of said previous-trip driving data sets is observed at a respective one of said plurality of different observation time points, and wherein the said parameter values of the previous-trip driving data sets are each read either as a respective instantaneous value or a respective average value read across a certain respective time period of at the most 5 seconds of length. ### Claim 15 A system for automatically assessing performance of a driver of a current vehicle for a particular current trip, the system is arranged to repeatedly read updated current-trip driving data sets are from the vehicle, the current-trip data sets each comprises data from at least a predetermined set of extended driving data parameters, wherein the system is arranged to read new such current-trip 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, the previous-trip data sets each comprises parameter values for both said set of extended driving data parameters and a predetermined set of a qualified parameter set, the qualified parameter set comprises the parameters of a basic parameter set and instantaneous vehicle energy consumption, wherein the server is arranged to group said previous-trip driving data sets into basic historic groups of such sets, based upon a basic driving data set similarity measure, the basic similarity measure is arranged to take values for said basic parameter set into consideration, and to calculate the value of a respective group performance parameter for each such basic historic group, wherein the server is arranged to further group said previous-trip driving data sets into extended historic groups of such sets, based upon an extended driving data set similarity measure, the extended similarity measure is arranged not to take all values for said basic parameter set into consideration that are taken into consideration by the basic similarity measure, wherein the server is arranged to, for each of said current-trip data sets, map the current-trip data set in question to at the most one particular of said extended historic groups, based upon an extended group conformity measure between a driving data set and an extended historic group, and wherein the server is arranged to calculate a current-trip performance parameter based upon the group performance parameter values of respective basic historic groups corresponding to previous-trip driving data sets comprised in the extended historic group to which a current-trip data set was matched. ### Claim 16 (depends on 15) The system according to claim 15, wherein the system is arranged to observe each of said previous-trip driving data sets is at a respective one of said plurality of different observation time points, and wherein the system is arranged to read the parameter values of the previous-trip driving data sets either as a respective instantaneous value or a respective average value read across a certain respective time period of at the most 5 seconds of length.