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Surface Vehicle Travel Pattern Optimization Through Data Analytics and Reporting

IP.com Disclosure Number: IPCOM000215408D
Publication Date: 2012-Feb-26
Document File: 6 page(s) / 99K

Publishing Venue

The IP.com Prior Art Database

Abstract

A method and system for utilizing traffic and meeting schedule data to optimize planned surface vehicle driving traffic patterns is disclosed.

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Surface Vehicle Travel Pattern Optimization Through Data Analytics and Reporting

Disclosed is a method and system for utilizing traffic and meeting schedule data to optimize planned surface vehicle driving traffic patterns. Traffic density data and calendar schedules are integrated for use in defining travel patterns, including roadways, times of days and days of week, to avoid high density traffic.

The disclosed method provides drivers of surface vehicles (cars, trucks..., etc.) with processes for establishing travel patterns that meet their objectives while minimizing time within high density traffic conditions. This differs from providing route information based primarily on distances between the start and end points. Traffic condition data from various media may be used. Additional data such as ongoing traffic densities over a period of time are used in optimizing planned traffic patterns. Alternative dates and times for routes for which traffic density conditions would be more favorable are identified. The driver is provided with recommended routes, dates and times for travel consistent with requirements as defined by the driver. The recommended travel patterns enable the driver to optimize their long term appointment(s) and planning route(s) based on the provided information.

People who travel by vehicles on surface roads apply various data to their decision making for the dates and routes chosen in support of their travel needs. This data often includes routes as determined from maps and potentially also from electronic route advisors. Additionally, the dates and time for their travel are often based on calendars and perhaps some personal experience with traffic density considerations.

Data analytics, delivered through a computer system, is used to provide additional information to the drivers. The driver may use this additional information to optimize routes and to plan schedules. Specifically, the data relates to the potential routes available to the driver and the expected traffic density for each route throughout the 24 hour period for each day of the week. Accordingly, the data is tabulated and compared to the planned or existing route and schedules as provided by the driver. The source of this planned and existing route data can include sensor acquired data from the vehicle as it travels, GPS readings, and manual input. By comparing the expected traffic density for the potential routes and schedule to the actual or planned routes, the driver can be advised of recommended alternative travel patterns. These recommended patterns can include alternate times, alternate days of the week and alternate routes as compared to any existing driver patterns. Thus, a driver who only knows, for example, that traffic is very dense on Tuesday at 2:00 for a specific route through personal experience can now be informed that the traffic is less dense for the same route on an alternate time and or day. With this information, the driver...