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GeoSparkSim: A Scalable Microscopic Road Network Traffic Simulator Based on Apache Spark

Abstract Researchers and practitioners have widely studied road network traffic data in different areas such as urban planning, traffic prediction and spatial-temporal databases. For instance, researchers use such data to evaluate the impact of road network changes. Unfortunately, collecting large-scale high-quality urban traffic data requires tremendous efforts because participating vehicles must install Global Positioning System(GPS) receivers and administrators must continuously monitor these devices. There have been some urban traffic simulators trying to generate such data with different features. However, they suffer from two critical issues (1) Scalability: most of them only offer single-machine solution which is not adequate to produce large... (more)
Created Date 2019
Contributor Fu, Zishan (Author) / Sarwat, Mohamed (Advisor) / Pedrielli, Giulia (Committee member) / Sefair, Jorge (Committee member) / Arizona State University (Publisher)
Subject Computer science / Computer engineering / Urban planning / Apache Spark / Microscopic Simulator / Road Network / Scalability / Traffic / Workload Balancing
Type Masters Thesis
Extent 107 pages
Language English
Note Masters Thesis Computer Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis