DRIVING DIRECTION BASED ON WEATHER FORECASTING SYSTEM AND METHOD

• US 20150198452A1
• Filed: 10/20/2014
• Published: 07/16/2015
• Est. Priority Date: 08/20/2013
• Status: Abandoned Application

• Current Assignee: Haoran Guan, Prachi Agarwal, Raghav Gupta
• Original Assignee: Haoran Guan, Prachi Agarwal, Raghav Gupta
• Inventors: Gupta, Raghav, Guan, Haoran, Agarwal, Prachi
• Application Number:
  US14/519,011
• Publication Number:
  US 20150198452A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01C 21/3461 Preferred or disfavoured areas, e.g. dangerous zones, toll or emission zones, intersections, manoeuvre types, segments such as motorways, toll roads, ferries
• CPC Class Codes: 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

Abstract

Navigation based on a weather forecasting system and method. A weather-based system and method for navigating or routing from an initial destination to a final destination. Routing may involve driving, air travel or the like. The system receives via a mobile computing device, a starting and destination location information and uses recent sequence of periodic real-time weather data for the starting, destination and in-between areas information to determine expected weather movement for the near future for respective areas. Based, in part, on the expected weather movement for the near future, the system determines optimal routing directions from the start to final destination.

Claims

1. A weather-based method for navigating from one location to another, the method employing a mobile computing device in communication with a server having a processor via a network, the mobile computing device comprising a computer readable memory having a processor, the method comprising:

by the one or more processors, receiving on the mobile computing device, a starting location on a map or an address of the starting location for a trip;

by the one or more processors, using the starting location to collect and store, in memory, recent and current weather data for the starting location, wherein the recent weather data includes data for a recent time interval prior to a starting time of the trip, wherein said past time interval is predetermined;

by the one or more processors, receiving on the mobile device, a destination location on a map or an address of the destination location for the trip;

by the one or more processors, using the destination location to collect and store, in memory, recent and current weather data for the destination location, wherein the recent weather data is for a recent time interval prior to the starting time of the trip to ensure future output data is substantially real time, wherein said recent time interval for the destination location is predetermined;

by the one or more processors, determining an in-between area that extends directly between the starting location and the destination location but only if said in-between area includes transportation routes that are usable for the trip from the starting location to the destination location;

by the one or more processors, using the in-between area to collect and store, in memory, recent and current weather data for the in-between area, wherein the recent weather data is for a recent time interval prior to the starting time of the trip;

wherein said recent time interval for the in-between area is predetermined;

by the one or more processors, determining an expected movement of weather for the starting location based in part on the recent and current weather data for the starting location;

by the one or more processors, determining an expected movement of weather for the in-between area based in part on the recent and current weather data for the in-between area;

by the one or more processors, determining an expected movement of weather for the destination location based in part on the recent and current weather for the destination location; and

by the one or more processors, determining an optimal route from the starting location through or around the in-between area to the destination location based in part on the expected movement of weather for the starting location, the in-between area and the destination location.

2. The method claim 1 wherein determining an optimal route is

by the one or more processors, determining a severity of the expected weather movement;

and

by the one or more processors, if the expected weather movement is severe, generating travel directions that route the trip around the expected weather movement.

3. The method of claim 1 wherein said determining an expected weather movement for each of the starting location, destination location and in-between area is

by the one or more processors, using the predetermined and recent time intervals of recent weather data to create a periodic sequence of weather data (e.g., periods of five minutes);

by the one or more processors, and in real time, extrapolating the periodic sequence of weather data into the future for a future time interval extending generally 60 minutes into the future from a current time; and

by the one or more processors, applying the extrapolated sequence to the most recent location of weather to yield an expected weather movement.

4. The method of claim 1 wherein said determining an expected weather movement for each of the starting location, destination location and in-between area is

by the one or more processors, applying a weather model to the recent weather data to obtain the expected weather movement.

5. The method of claim 1 further comprising

by the one or more processors, after initiation of the trip, re-determining an optimal route at temporal segments of the trip.

6. A computer program product including a computer readable storage medium and including computer executable code which when executed by a processor is adapted to:

receive a mobile computing device, a starting location on a map or an address of a starting location for a trip;

use the starting location to collect and store, in memory, recent and current weather data for the starting location, wherein the recent weather data includes data for a recent time interval prior to a starting time of the trip, wherein said past time interval is predetermined;

receive on the mobile device, a destination location on a map or an address of the destination location for the trip;

use the destination location to collect and store, in memory, recent and current weather data for the destination location, wherein the recent weather data is for a recent time interval prior to the starting time of the trip to ensure future output data is substantially real time, wherein said recent time interval for the destination location is predetermined;

determine an in-between area that extends directly between the starting location and the destination location but only if said in-between area includes transportation routes that are usable for the trip from the starting location to the destination location;

use the in-between area to collect and store, in memory, recent and current weather data for the in-between area, wherein the recent weather data is for a recent time time interval from the starting time of the trip;

wherein said recent time interval for the in-between area is predetermined;

determine an expected movement of weather for the starting location based in part on the recent and current weather data for the starting location;

determine an expected movement of weather for the in-between area based in part on the recent and current weather data for the in-between area;

determine an expected movement of weather for the destination location based in part on the recent and current weather for the destination location; and

determine an optimal route from the starting location through or around the in-between area to the destination location based in part on the expected movement of weather for the starting location, the in-between area and the destination location.

7. The computer program product of claim 6 wherein determining an optimal route is by

determining a severity of the expected weather movement;

and

if the expected weather movement is severe, generating travel directions that route the trip around the expected weather movement.

8. The computer program product of claim 6 wherein said determining an expected weather movement for each of the starting location, destination location and in-between area is by

using the predetermined and recent time intervals of recent weather data to create a periodic sequence of weather data (e.g., periods of five minutes);

and in real time, extrapolating the periodic sequence of weather data into the future for a future time interval extending generally 60 minutes into the future from a current time; and

applying the extrapolated sequence to the most recent location of weather to yield an expected weather movement.

9. The computer program product of claim 6 wherein said determining an expected weather movement for each of the starting location, destination location and in-between area is by

applying a weather model to the recent weather data to obtain the expected weather movement.

10. The computer program product of claim 6 further comprising

after initiation of the trip, re-determining an optimal route at temporal segments of the trip.