Browse Prior Art Database

Method for Fuel Station Selection Using Predictive Analysis and User Preferences

IP.com Disclosure Number: IPCOM000237869D
Publication Date: 2014-Jul-17
Document File: 3 page(s) / 123K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a system that determines the optimal place for a vehicle to refuel on a journey based on predictive factors, past usage factors, and user preferences.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 52% of the total text.

Page 01 of 3

Method for Fuel Station Selection Using Predictive Analysis and User Preferences

Many factors during a driver's journey determine the best place to stop to refuel a vehicle. The most obvious is the range of the fuel in the vehicle and fuel cost. Other factors can include the best time of day to stop, the location of amenities near the gas station, and gas station brand preferences. Predicting when a vehicle will need to be refueled is not obvious; factors such as current and anticipated traffic and weather conditions can affect the fuel economy of a vehicle. With so many factors, it is difficult for a driver to predict at the start of the journey the best location for refueling.

Solutions already exist to provide the driver with fueling locations based on some of the above input. For example, a global positioning system (GPS) can show the location of nearby gas stations, and applications on smart phones provide crowd-sourced pricing information. However, none of these solutions combines all the factors to identify a single recommended fuel stop based on all predictive inputs and user preferences.

The solution is a system that combines three factors to determine the exact duration of a journey and the best place to refuel. The factors are:


 Predictive factors (e.g., anticipated traffic conditions along the route)


 Past usage factors (e.g., the driver's average speed)


 User preferences (e.g., gas station brands, nearby amenities, restaurants, time-of-day, etc.)

The novel approach uses predictive analytics to determine the exact journey time at any given point on a route. An algorithm combines the result of these analytics with user preferences.

The system combines these factors to produce a list of suitable gas stations for refueling .

To implement the system in a preferred embodiment:

1. A user inputs a journey into the system (in this example "A" represents the departure location and "B" represents the destination).

2. The system uses predictive, past usage, and user preference factors (as stated above) to estimate arrival time along arrival time along different points of the route

3. Based on these factors, the system calculates the journey time. In this example, the journey begins at 1:30pm, arriving at the de...