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The Addition of Weather and Event Factors to Improve Travel Arrival Estimation Disclosure Number: IPCOM000243679D
Publication Date: 2015-Oct-09
Document File: 3 page(s) / 192K

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The Prior Art Database


Disclosed is a method to give routing time in near future from site A to B would be better estimated by adding estimators for factors of weather and news/event. User can have more options on the user interface to turn weather and event factors on or off. If one or both is turn on, the weather or/and events estimator could be activated.

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The Addition of Weather and Event Factors to Improve Travel Arrival Estimation

Today, users can use their GPS devices or navigation applications to receive an estimated time of arrival for current or future routes by optionally selecting the time and day of travel. Current route times on tools such as Google Maps consider the speed limits and the traffic conditions which may result in a delayed arrival. However, these tools do not consider some other important factors. The disclosed method shows how to add these factors to improve traveling time (driving/biking/walking/public transportation) estimates.

FIG-1. Current Solution on Suggested Route from Location A to Location B

The example below, focuses on future travel time estimates rather than on current travel times although it could be applied equally to both. The new added factors include:

1. Weather factors: The severe weather would effect route time on any given day and time. The weather factors that effect travel route times are thunderstorms, heavy fog, snow, hail, etc. Weather data to be used in determining the driving estimation can be acquired from the national or local weather service. The severe weather may cause roads to be closed, which in turn could completely change the routing.

2. News and events: Events, especially large scale events could affect driving times tremendously. News and events include government events, sports events, strikes, and local organizational events. Some streets may be blocked off because of events at particular places (for example, presidential motorcade). These events could result in re-routed traffic because of blocked streets. Unexpected events like accidents, fires and terrorist incidents could also effect traffic conditions.

Users can get better driving time estimation if the above factors were added to the historical


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travel data. Currently tools like Google Maps can show estimated travel times up to a week in

advance. Unfortunately, the estimated traveling time ranges can change because of various factors. The ranges are so distant that sometimes the estimated arrival times can be way off. Users have no clue when the actual travel conditions are congested. If weather and events are added, the user could get a more realistic picture of what to expect. Implementation of the method would be as follows:

A: Using time estimation functions: Route time estimation is a function of road segment of some distance from A to B (d), date and time (t), and weather factor (w) and event factor (e). Two functions are defined to estimate the impacts both on weather and events: Weather Estimator and Event Estimator. Event estimator for route time at time t for a distance d with an expected event e will be represented as RT(e,d,t). Likewise, a weather estimator for route time for a distance d at time t with expected weather w would be represented as RT(w,d,t). [Note that in both functions d is representing a specific road segment (from A...