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Undergraduate Research Project Management System

FreeSim Mobile

Status Complete
Seeking Researchers No
Start Date 11/01/2010
End Date 12/01/2010
Funding Source Discovery Grant
Funding Amount
Community Partner
Related Course
Last Updated 03/01/2011 11:34PM
Keywords freesim, traffic, iphone

People

Faculty
  Jeffrey Miller

Student Researchers
  Timothy Menard

Abstract

We present a preliminary application for the iPhone that uses the built-in GPS receiver along with the web capabilities utilizing a V2I architecture to send a continuous flow of data to a central server where FreeSim, a real-time traffic simulator, applies the proportional model algorithm to determine the time to traverse a roadway in order to report in real-time the current flow of traffic. At the University of Alaska, Anchorage, we currently have vehicle tracking devices installed in 80 probe vehicles that traverse the Anchorage area. The high cost associated with vehicle tracking devices makes it difficult to penetrate a large vehicular network on limited funds, so we must look towards other available technologies, such as the constantly-expanding cellular network. In this paper we look at the iPhone 3G capability of reporting accurate and reliable locations by describing our sample application and comparing its reported GPS accuracy to the existing vehicle probes we have. We will then present a study of its performance of calculating an accurate traffic flow where a chosen section of roadway was driven. Drivers equipped with an iPhone3G cellular phone and a vehicle tracking device manually timed how long it took to travel along the test road section. The vehicle tracking devices report speed and location every 10 seconds whereas the iPhone is capable of reporting the location every second, though we were receiving it every eight seconds. From this data, we calculated the amount of time to traverse the test roadway section using the proportional model algorithm and compared it to the actual amount of time it took to traverse the test roadway section. We found that the vehicle tracking device had an average error factor of 4.43% from the actual time to traverse the roadway section (as determined by the stopwatch), whereas the iPhone was found to have an error factor of 4.18%. The outcome of the case study is used to determine that the iPhone is relatively as accurate as a vehicle tracking device, though it is important to note that the iPhone is more limited than a device attached to a vehicle in the data it can obtain to only reporting its location.

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