Navigation with sun glare information

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.

What is claimed is: 
     
         1 . A computer implemented method, comprising:
 determining a starting location and an ending location;   determining whether sun glare is likely while traveling from the starting location to the ending location;   responsive to determining that sun glare is likely:   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 predicted sun glare;   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.   
     
     
         2 . The method of  claim 1  wherein the first cost function comprises sun glare and travel time. 
     
     
         3 . The method of  claim 1  wherein the first cost function comprises sun glare and estimated traffic. 
     
     
         4 . The method of  claim 1  wherein the second cost function comprises travel time. 
     
     
         5 . The method of  claim 1  wherein the second cost function comprises estimated traffic. 
     
     
         6 . The method of  claim 1  wherein predicted sun glare is calculated by operations comprising:
 estimating start time and end time for travel along the first travel route; 
 determining a plurality of base sun glare-location pairs corresponding to estimated locations along the first travel route based on the azimuth and elevation of the sun at a time corresponding to the estimated locations; and 
 utilizing the base sun glare as the predicted sun glare for the corresponding location. 
 
     
     
         7 . The method of  claim 6  wherein the base sun glare is adjusted based on environmental factors prior to being utilized as the predicted sun glare for the corresponding location. 
     
     
         8 . The method of  claim 6  wherein the base sun glare is adjusted using a trained machine learning model prior to being utilized as the predicted sun glare for the corresponding location. 
     
     
         9 . The method of  claim 1  further comprising:
 sending sun glare information to a navigation server. 
 
     
     
         10 . A system comprising:
 a processor and device-storage media having executable instructions which, when executed by the processor, cause the system to perform operations comprising:   determining a travel route to minimize a cost function along the travel route from a starting location to an ending location, the cost function comprising predicted sun glare;   receiving perceived sun glare from a user device navigating along the travel route;   providing the perceived sun glare to a second user device.   
     
     
         11 . The system of  claim 10  wherein the second user device is also navigating along the travel route. 
     
     
         12 . The system of  claim 10  wherein predicted sun glare is calculated by operations comprising:
 estimating start time and end time for travel along the first travel route; 
 determining a plurality of base sun glare-location pairs corresponding to estimated locations along the first travel route based on the azimuth and elevation of the sun at a time corresponding to the estimated locations; and 
 utilizing the base sun glare as the predicted sun glare for the corresponding location. 
 
     
     
         13 . The system of  claim 12  wherein the base sun glare is adjusted based on environmental factors prior to being utilized as the predicted sun glare for the corresponding location. 
     
     
         14 . The system of  claim 13  wherein environmental factors comprises at least one of:
 a shadow factor; 
 a weather factor. 
 
     
     
         15 . The system of  claim 12  wherein the base sun glare is adjusted using a trained machine learning model prior to being utilized as the predicted sun glare for the corresponding location. 
     
     
         16 . The system of  claim 10  further comprising receiving sun glare information from a user device navigating along a different travel route. 
     
     
         17 . The system of  claim 10  further comprising receiving weather information. 
     
     
         18 . The system of  claim 10  wherein the predicted sun glare is created in part using a trained machine learning model. 
     
     
         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 whether sun glare is likely while traveling from the starting location to the ending location;   responsive to determining that sun glare is likely:   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 predicted sun glare;   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.   
     
     
         20 . The storage medium of  claim 19  wherein determining whether sun glare is likely comprises:
 estimating a start time and an end time for travel from the starting location to the ending location; 
 determining whether the elevation of the sun between the start time and the end time falls below a threshold; 
 determining that sun glare is likely when the elevation falls below the threshold.