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A demonstration of MNTG - A web-based road network traffic generator | IEEE Conference Publication | IEEE Xplore

A demonstration of MNTG - A web-based road network traffic generator


Abstract:

This demo presents Minnesota Traffic Generator (MNTG); an extensible web-based road network traffic generator. MNTG enables its users to generate traffic data at any arbi...Show More

Abstract:

This demo presents Minnesota Traffic Generator (MNTG); an extensible web-based road network traffic generator. MNTG enables its users to generate traffic data at any arbitrary road networks with different traffic generators. Unlike existing traffic generators that require a lot of time/effort to install, configure, and run, MNTG is a web service with a user-friendly interface where users can specify an arbitrary spatial region, select a traffic generator, and submit their traffic generation request. Once the traffic data is generated by MNTG, users can then download and/or visualize the generated data. MNTG can be extended to support: (1) various traffic generators. It is already shipped with the two most common traffic generators, Brinkhoff and BerlinMOD, but other generators can be easily added. (2) various road network sources. It is shipped with U.S. Tiger files and OpenStreetMap, but other sources can be also added. A beta version of MNTG is launched at: http://mntg.cs.umn.edu.
Date of Conference: 31 March 2014 - 04 April 2014
Date Added to IEEE Xplore: 19 May 2014
Electronic ISBN:978-1-4799-2555-1

ISSN Information:

Conference Location: Chicago, IL, USA

I. Introduction

Having access to road network traffic data is a major need to validate and evaluate indexing and query processing techniques in moving objects databases, spatio-temporal databases, and data streams. Unfortunately, such data is not easily available, and is usually of much smaller scale than needed. The process of extracting real traffic data requires installing and configuring many GPS-enabled devices and continuously monitoring the locations of such devices, which is a cumbersome task. For instance, GeoLife project [13] took more than four years to collect 17,621 trajectories dataset with the involvement of 182 volunteers in Beijing. As a result, researchers have been using existing traffic generators as a means of getting synthetic datasets that exhibit similar behavior to real data. The most two common traffic generators are Brinkhoff [1] and BerlinMOD [3], which have been widely adopted by large numbers of papers in the database literature, e.g., see [2], [5], [6], [8], [10], [12].

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References

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