Methods of determining user-centric traffic estimation error parameter associated with estimated road traffic conditions

Patent metadata

Field	Value
Publication number	US-2018286221-A1
Application number	US-201815861197-A
Country	US
Kind code	A1
Filing date	Jan 3, 2018
Priority date	Apr 4, 2017
Publication date	Oct 4, 2018
Grant date	—

Abstract

A method of determining a user-centric traffic estimation error parameter associated with an estimated road traffic condition that is electronically provided to a user of a device. the method comprises: at a first moment in time, acquiring an estimated travel time for a road segment, the estimated travel time having been computed for the first moment in time; responsive to the device approaching the road segment, displaying an application-generated estimated travel time for the road segment, the application-generated estimated travel time being based on a most recently acquired estimated travel time from the server; responsive to the device departing from the road segment, determining an actual travel time for the road segment; computing the user-centric traffic estimation error parameter based on the application-generated estimated travel time and the actual travel time; and transmitting the user-centric traffic estimation error parameter to the server for adjusting a traffic prediction algorithm.

First claim

What is claimed is:

1 . A method of determining a user-centric traffic estimation error parameter associated with an estimated road traffic condition that is electronically provided to a user of an electronic device using a navigational application executed on the electronic device, the method being executed on the electronic device, the method comprising:
at a first moment in time, acquiring, by the electronic device from a server, an estimated travel time for a road segment, the server executing a traffic prediction algorithm, the estimated travel time having been computed by the traffic prediction algorithm for the first moment in time, the estimated travel time being indicative of the estimated road traffic condition of the road segment during the first moment in time; responsive to the electronic device approaching the road segment, displaying, by the electronic device, an application-generated road traffic condition for the road segment, the application-generated road traffic condition being based on a most recently acquired estimated travel time from the server, the application-generated road traffic condition being representative of an expected travel time for the road segment by the user as the user enters the road segment; responsive to the electronic device departing from the road segment, determining, by the electronic device, an actual travel time for the road segment, the actual travel time being indicative of an actual road traffic condition of the road segment experienced by the user as the user travelled the road segment; determining, by the electronic device, device-side intelligence of the electronic device being indicative of the expected travel time by the user upon the electronic device approaching the road segment and of the actual travel time; and transmitting, by the electronic device, to the server for adjusting the traffic prediction algorithm based on the user-centric traffic estimation error parameter, one of:
the user-centric traffic estimation error parameter, the user-centric traffic estimation error parameter computed by the electronic device based on the device-side intelligence; and
the device-side intelligence for computing the user-centric traffic estimation error parameter.

2 . The method of claim 1 , wherein the method further comprises determining, by the electronic device, that the electronic device is approaching the road segment.

3 . The method of claim 1 , wherein the traffic prediction algorithm is configured by the server to compute updated estimated travel times according to a frequency of computation.

4 . The method of claim 3 , wherein the frequency of computation varies depending on a period of a day.

5 . The method of claim 3 , wherein the most recently acquired estimated travel time from the server is the estimated travel time having been computed by the traffic prediction algorithm for the first moment in time.

6 . The method of claim 3 , wherein the electronic device approaches the road segment at a second moment in time, the second moment in time being later in time than the first moment in time, and wherein an interval between the second moment in time and the first moment in time is superior to the frequency of computation.

7 . The method of claim 6 , wherein the most recently acquired estimated travel time is an outdated estimated travel time at the second moment in time.

8 . The method of claim 6 , wherein the electronic device departs from the road segment at a third moment in time, the third moment in time being later in time than the second moment in time, and wherein the most recently acquired estimated travel time is an outdated estimated travel time at the third moment in time.

9 . The method of claim 1 , wherein the method further comprises determining, by the electronic device, that the electronic device is departing from the road segment.

10 . A server for adjusting a traffic prediction algorithm based on a user-centric traffic estimation error parameter associated with an estimated road traffic condition, the server executing the traffic prediction algorithm, the server being communicatively coupled to an electronic device, the electronic device executing a navigational application for electronically providing to a user of the electronic device the estimated road traffic condition, the server being configured to:
acquire, from the electronic device, initial navigational parameters being indicative of a request from a user for the estimated road traffic condition, at a first moment in time:
compute an estimated travel time for a road segment for the first moment in time using the traffic prediction algorithm based on the initial navigational parameters, the estimated travel time being indicative of the estimated road traffic condition of the road segment during the first moment in time;
transmit the estimated travel time for the road segment for the first moment in time to the navigational application of the electronic device;
compute an updated estimated travel time for the road segment for another moment in time using the traffic prediction algorithm, the another moment in time being later in time than the first moment in time, the updated estimated travel time being indicative of an updated estimated road traffic condition of the road segment during the another moment in time; send the updated estimated travel time for the road segment for the another moment in time to the navigational application of the electronic device, the updated estimated travel time for the road segment for the another moment in time being non-acquired by the electronic device, the server being unaware of non-acquisition by the electronic device of the updated estimated travel time for the road segment for the another moment in time; at a third moment in time, the third moment in time being later in time than the another moment in time, acquire one of:
device-side intelligence of the electronic device from the electronic device for computing the user-centric traffic estimation error parameter, the device-side intelligence being indicative of an expected travel time by the user upon the electronic device approaching the road segment and of the actual travel time, the expected travel time being based on a most recently acquired estimated travel time by the electronic device, the expected travel time being represented by an application-generated road traffic condition for the road segment provided to the user as the user entered the road segment, the actual travel time being indicative of an actual road traffic condition for the road segment experienced by the user as the user travelled the road segment; and
the user-centric traffic estimation error parameter computed by the electronic device based on the device-side intelligence; and
adjust the road traffic prediction algorithm based on the user-centric traffic estimation error parameter.

11 . The server of claim 10 , wherein the server is further configured to determine server-side intelligence being indicative of the updated estimated travel time for the road segment for another moment in time and of the actual travel time, the updated estimated travel time being a most recently sent estimated travel time by the server, the device-side intelligence being different from the server-side intelligence.

12 . The server of claim 10 , wherein the server is further configured to:
at the third moment in time acquire the device-side intelligence of the electronic device from the electronic device for computing the user-centric traffic estimation error parameter; determine server-side intelligence being indicative of the updated estimated travel time for the roa

Assignees

• Yandex Europe Ag

Inventors

• Khokhlov Mikhail Aleksandrovich
• SINITSYN Philipp Gennadievich

Classifications

• G01C21/3492 Primary

  employing speed data or traffic data, e.g. real-time or historical (traffic control systems for road vehicles involving transmission of navigation instructions to the vehicle G08G1/0968) · CPC title

• G01C21/3415

  Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents · CPC title

• G08G1/0104 Primary

  Measuring and analyzing of parameters relative to traffic conditions · CPC title

• G01C21/20

  Instruments for performing navigational calculations (G01C21/24, G01C21/26 take precedence) · CPC title

• G01C21/3694

  Output thereof on a road map · CPC title