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US10156454B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10156454-B2
Application numberUS-201514944383-A
CountryUS
Kind codeB2
Filing dateNov 18, 2015
Priority dateNov 18, 2015
Publication dateDec 18, 2018
Grant dateDec 18, 2018

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

A computer detects the receipt of a destination and mode of transportation from a user. The computer determines potential routes to the destination using static map information and splits the routes into shorter lengths known as segments. The computer determines a commute time for each of the segments based on static map information, known as a static segment commute time, and determines whether any of the segments have been previously commuted by the user. If so, the computer replaces the static segment commute times with the segment commute times recorded during previous commutes of the segment, known as habitual segment commute times. The computer then determines the total commute time of each potential route based on the static and habitual segment commute times and records additional habitual segment statistics as the user commutes the selected route.

First claim

Opening claim text (preview).

What is claimed is: 1. A method for GPS optimization, the method comprising: determining one or more potential routes between a location of a user and a destination; splitting at least one of the one or more potential routes into one or more segments; determining one or more static segment commute times associated with at least one of the one or more segments based on static segment statistics, wherein the static segment statistics detail at least one of: (i) a mileage of the one or more segments, (ii) one or more speed limits corresponding to the one or more segments, and (iii) one or more traffic signals corresponding to the one or more segments; determining whether habitual segment statistics are applicable to a time of driving at least one of the one or more segments, wherein the habitual segment statistics include information detailing previous commutes of the one or more segments by the user including at least one of: (i) a time at segment begin, (ii) a time at segment end, (iii) an overall segment commute time, (iv) a maximum speed, (v) a minimum speed, (vi) an average speed, (vii) an amount of time at a stand-still, (viii) a day of the week, and (ix) a date, and wherein determining that habitual segment statistics are applicable to at least one of the one or more segments requires: determining that the habitual segment statistics correspond to a time of day that is within a threshold time period of a time of day at which the user is commuting the one or more potential routes; determining that the habitual segment statistics correspond to a same day of the week as a day of the week at which the user is commuting the one or more potential routes; determining that the habitual segment statistics correspond to a same holiday as a holiday at which the user commuting the one or more potential routes; and determining that the habitual segment statistics are within a threshold percentage of the static segment statistics; based on determining that habitual segment statistics are applicable to at least one of the one or more segments, determining one or more habitual segment commute times for the at least one of the one or more segments based on the habitual segment statistics of the at least one of the one or more segments; determining whether a deviation of the one or more habitual segment commute times from the one or more static segment commute times exceeds a threshold amount; based on determining that the deviation of the one or more habitual segment commute times from the one or more static segment commute times exceeds the threshold amount; replacing the one or more static segment commute times associated with the at least one of the one or more segments with the determined one or more habitual segment commute times associated with the at least one of the one or more segments; and determining an overall commute time for the at least one of the one or more potential routes based on at least one of: (i) at least one of the one or more of the static segment commute times associated with the at least one of the one or more segments and (ii) at least one of the one or more determined habitual segment commute times associated with the at least one of the one or more segments, wherein one or more steps of the above method are performed using one or more computers. 2. The method of claim 1 , further comprising: collecting current habitual segment statistics corresponding to the one or more segments as the one or more segments are commuted by the user; and updating a segment statistics database based on comparing the current habitual segment statistics with the habitual segment statistics. 3. The method of claim 1 , wherein the one or more segments are at least one of: one or more city blocks along the one or more potential routes and one or more stretches of highway between consecutive exits along the one or more potential routes. 4. The method of claim 1 , further comprising: collecting current habitual segment statistics corresponding to the one or more segments as the one or more segments are commuted by the user; and updating a segment statistics database based on applying exponential moving averages and regression techniques to the current habitual segment statistics. 5. The method of claim 1 , wherein the one or more potential routes details at least one of: a driving route, a cycling route, a walking route, a jogging route, and a public transportation route. 6. A computer program product for GPS optimization, the computer program product comprising: one or more computer-readable non-transitory storage media and program instructions stored on the one or more computer-readable storage media, the program instructions comprising: program instructions to determine one or more potential routes between a location of a user and a destination; program instructions to split at least one of the one or more potential routes into one or more segments; program instructions to determine one or more static segment commute times associated with at least one of the one or more segments based on static segment statistics, wherein the static segment statistics detail at least one of: (i) a mileage of the one or more segments, (ii) one or more speed limits corresponding to the one or more segments, and (iii) one or more traffic signals corresponding to the one or more segments; program instructions to determine whether habitual segment statistics are applicable to a time of driving at least one of the one or more segments, wherein the habitual segment statistics include information detailing previous commutes of the one or more segments by the user including at least one of: (i) a time at segment begin, (ii) a time at segment end, (iii) an overall segment commute time, (iv) a maximum speed, (v) a minimum speed, (vi) an average speed, (vii) an amount of time at a stand-still, (viii) a day of the week, and (ix) a date, and wherein the program instructions to determine that habitual segment statistics are applicable to at least one of the one or more segments requires: program instructions to determine that the habitual segment statistics correspond to a time of day that is within a threshold time period of a time of day at which the user is commuting the one or more potential routes; program instructions to determine that the habitual segment statistics correspond to a same day of the week as a day of the week at which the user is commuting the one or more potential routes; program instructions to determine that the habitual segment statistics correspond to a same holiday as a holiday at which the user commuting the one or more potential routes; and program instructions to determine that the habitual segment statistics are within a threshold percentage of the static segment statistics; based on determining that habitual segment statistics are applicable to at least one of the one or more segments, program instructions to determine one or more habitual segment commute times for the at least one of the one or more segments based on the habitual segment statistics of the at least one of the one or more segments; program instructions to determine whether a deviation of the one or more habitual segment commute times from the one or more static segment commute times exceeds a threshold amount; based on determining that the deviation of the one or more habitual segment commute times from the one or more static segment commute times exceeds the threshold amount; program instructions to replace the one or more static segment commute times associated with the at least one of the one or more segments with the determined one or more habitual segment commute times associated with the at least one of the one or more segments; and program instructions to determine an overall commute time for the at lea

Assignees

Inventors

Classifications

  • Trajectory determination or predictive tracking, e.g. Kalman filtering · CPC title

  • 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

  • Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system · CPC title

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Frequently asked questions

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What does patent US10156454B2 cover?
A computer detects the receipt of a destination and mode of transportation from a user. The computer determines potential routes to the destination using static map information and splits the routes into shorter lengths known as segments. The computer determines a commute time for each of the segments based on static map information, known as a static segment commute time, and determines whethe…
Who is the assignee on this patent?
IBM
What technology area does this patent fall under?
Primary CPC classification G01C21/3492. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Dec 18 2018 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 2 related publications on this page (citations in our corpus or others sharing the same primary CPC).