# US 11,112,257 B2 · Navigation with sun glare information > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,112,257 B2 - Document ID: US11112257B2 - Status: Granted - Kind: B2 - Application number: 15/968,902 - Filed: 2018-05-02 - Published: 2019-11-07 - Granted: 2021-09-07 - Earliest claimed: 2018-05-02 - Assignees: Microsoft Technology Licensing, LLC - Applicants: Microsoft Technology Licensing, LLC - Inventors: Sapna Jeswani; Ajoy Nandi; Vinay Bhat - Web page: https://patentgrep.com/patent/US11112257B2 ## CPC - G01C 21/3461: {Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types or segments such as motorways, toll roads or ferries} - G01C 21/3484: {Personalized, e.g. from learned user behaviour or user-defined profiles} - G01C 21/3691: {Retrieval, searching and output of information related to real-time traffic, weather, or environmental conditions (arrangements for giving variable traffic instructions G08G1/09)} - G01C: MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY (measuring liquid level G01F; radio navigation, determining distance or velocity by use of propagation effects, e.g. Doppler effects, propagation time, of radio waves, analogous arrangements using other waves G01S) ## Abstract Representative embodiments disclose mechanisms to utilize navigation routes in order to avoid or minimize sun glare along the navigation route. Some embodiments first estimate whether it is likely that sun glare will be perceived while navigating between a starting location and an ending location. If sun glare is likely, the navigation route is calculated using sun glare as part of a cost function. If sun glare is not likely, the navigation route is calculated without regard to sun glare. Real-time sun glare feedback can be received from one user device and used in sun glare calculations for another user device. In some embodiments a trained machine learning model can be utilized as part of the sun glare calculation. Other embodiments include digital assistants that use sun glare information to recommend actions and/or take actions on behalf of a user. ## Claims ### Claim 1 A computer implemented method, comprising: determining a starting location and an ending location; determining a first time range during which travel will occur from the starting location to the ending location; determining a first sun position during at least a portion of the first time range; generating a basic glare index from the first sun position and a predetermined relationship between sun positions and corresponding glare indices; determining whether sun glare is likely while traveling from the starting location to the ending location based on the basic glare index; responsive to determining that sun glare is likely: generating a predicted glare index by modifying the basic glare index in accordance with environmental adjustments, the environmental adjustments accounting for both: (1) near obstructions of the sun at the first sun position that are caused by, or within, a vehicle traveling from the starting location to the ending location and (2) far obstructions of the sun at the first sun position that are external to the vehicle; and determining a first travel route to minimize a first cost function along the first travel route from the starting location to the ending location, the first cost function being based on the predicted glare index; and responsive to determining that sun glare is not likely: determining a second travel route to minimize a second cost function along the second travel route from the starting location to the ending location, the second cost function excluding sun glare. ### Claim 2 (depends on 1) The method of claim 1, wherein the predetermined relationship between sun positions and corresponding glare indices is a curve in two or more dimensions correlating the sun positions to the corresponding glare indices. ### Claim 3 (depends on 1) The method of claim 1, wherein the predetermined relationship between sun positions and corresponding glare indices is specific to a first sensor installed on the vehicle. ### Claim 4 (depends on 1) The method of claim 1, wherein the predetermined relationship between sun positions and corresponding glare indices is wavelength specific. ### Claim 5 (depends on 1) The method of claim 1, wherein the predetermined relationship between sun positions and corresponding glare indices is generated by a trained machine learning model that was trained based on pre-existing pairs of sun positions and corresponding glare indices. ### Claim 6 (depends on 1) The method of claim 1, wherein the far obstructions of the sun comprise weather obstructions, the weather obstructions being one of: observed weather obstructions, predicted weather obstructions or historical weather obstructions. ### Claim 7 (depends on 1) The method of claim 1, wherein the far obstructions of the sun comprise atmospheric obstructions, the atmospheric obstructions being one of: observed atmospheric obstructions, predicted atmospheric obstructions or historical atmospheric obstructions. ### Claim 8 (depends on 1) The method of claim 1, wherein the near obstructions comprise at least one of: a roof of the vehicle or a sun visor of the vehicle. ### Claim 9 (depends on 1) The method of claim 1, wherein the environmental adjustments accounting for the far obstructions are based on modeled shadowing effects of one or more shadows associated with the far obstructions. ### Claim 10 (depends on 1) The method of claim 1, wherein the environmental adjustments are generated by a trained machine learning model that was trained based on pre-existing pairs of environmental adjustments and corresponding predict glare indices. ### Claim 11 (depends on 1) The method of claim 1, wherein the determining that sun glare is likely is based on the basic glare index exceeding a predetermined threshold. ### Claim 12 (depends on 1) The method of claim 1, further comprising generating a user glare index by modifying the predicted glare index in accordance with user adjustments that account for subjective user factors. ### Claim 13 (depends on 12) The method of claim 12, wherein the subjective user factors quantify how bothersome sun glare is to an individual user. ### Claim 14 (depends on 12) The method of claim 12, wherein the first cost function is directly based on the user glare index and, thereby, indirectly based on the predicted glare index. ### Claim 15 (depends on 12) The method of claim 12, further comprising: detecting the sun glare during the travel from the starting location to the ending location; querying a user traveling from the starting location to the ending location for feedback, the querying being triggered by the detecting the sun glare; and modifying the user adjustments in accordance with user feedback received in response to the querying. ### Claim 16 (depends on 15) The method of claim 15, wherein the detecting the sun glare comprises detecting sensor degradation exceeding a sensor degradation threshold. ### Claim 17 (depends on 15) The method of claim 15, wherein the detecting the sun glare comprises detecting that a sun glare sensor is sensing sun glare above a sun glare threshold. ### Claim 18 (depends on 15) The method of claim 15, wherein the detecting the sun glare comprises detecting sun glare impacts on the user's operation of the vehicle during the travel from the starting location to the ending location. ### Claim 19 A computer storage medium comprising executable instructions that, when executed by a processor of a machine, cause the machine to perform acts comprising: determining a starting location and an ending location; determining a first time range during which travel will occur from the starting location to the ending location; determining a first sun position during at least a portion of the first time range; generating a basic glare index from the first sun position and a predetermined relationship between sun positions and corresponding glare indices; determining whether sun glare is likely while traveling from the starting location to the ending location based on the basic glare index; responsive to determining that sun glare is likely: generating a predicted glare index by modifying the basic glare index in accordance with environmental adjustments, the environmental adjustments accounting for both: (1) near obstructions of the sun at the first sun position that are caused by, or within, a vehicle traveling from the starting location to the ending location and (2) far obstructions of the sun at the first sun position that are external to the vehicle; and determining a first travel route to minimize a first cost function along the first travel route from the starting location to the ending location, the first cost function comprising the predicted glare index; and responsive to determining that sun glare is not likely: determining a second travel route to minimize a second cost function along the second travel route from the starting location to the ending location, the second cost function excluding sun glare. ### Claim 20 A computing device comprising: one or more processing units; and one or more computer storage media comprising executable instructions that, when executed by at least some of the one or more processing units, cause the computing device to: determine a starting location and an ending location; determine a first time range during which travel will occur from the starting location to the ending location; determine a first sun position during at least a portion of the first time range; generate a basic glare index from the first sun position and a predetermined relationship between sun positions and corresponding glare indices; determine whether sun glare is likely while traveling from the starting location to the ending location based on the basic glare index; responsive to determining that sun glare is likely: generate a predicted glare index by modifying the basic glare index in accordance with environmental adjustments, the environmental adjustments accounting for both: (1) near obstructions of the sun at the first sun position that are caused by, or within, a vehicle traveling from the starting location to the ending location and (2) far obstructions of the sun at the first sun position that are external to the vehicle; and determine a first travel route to minimize a first cost function along the first travel route from the starting location to the ending location, the first cost function comprising the predicted glare index; and responsive to determining that sun glare is not likely: determine a second travel route to minimize a second cost function along the second travel route from the starting location to the ending location, the second cost function excluding sun glare.