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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01z316q1769
Title: Assessing Real-Time Transportation Demand: Building an Interactive, Three-Dimensional Visualization of Traffic Flows in New Jersey
Authors: Harpalani, Natasha
Advisors: Kornhauser, Alain
Department: Operations Research and Financial Engineering
Class Year: 2014
Abstract: Vast quantities of transportation data exist and help planners and various industry professionals develop areas, ensure safety, and increase the mobility of humans. While transportation data is necessary to begin to understand patterns, trends, and locations of traffic, it does not always provide a clear picture of the context of traffic. Transportation trends are often dependent on the urban environment, landscape, and time of day. In order to make accurate conclusions based on real world context, it is important to be able to visualize a complex transportation dataset. This thesis aims to build a visualization tool that produces a real-time, geospatial visualization of a complex dataset containing trip demand for the state of New Jersey during an average day. A visualization of this complex dataset will provide users insight into the context of trip demand in New Jersey and will thus aid users in making assessments and decisions regarding transportation networks. This tool has a simple and intuitive user interface that allows a user to choose a specific county and time of day during which to view trip demand for New Jersey residents and workers. This study begins the process of building a visualizer. As more work progresses beyond this study, the hope is that a visualization platform in the form of a web application will arise in the future, allowing users to input a large dataset containing transportation information for any area, and view trip demand in a three-dimensional, and interactive virtual globe.
Extent: 111
URI: http://arks.princeton.edu/ark:/88435/dsp01z316q1769
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2023

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