Data Analytics Engineering Capstone Projects and Presentations

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    Traffic Management Modeling for Manassas Virginia
    (2019-12) Chalmala, Goutham; Lepe, Michael; Esguerra, Marissa; Murray, James
    Vehicle traffic management has become a major issue in the United States and, especially, in the Northern Virginia area. This study assesses the traffic factors and develops models for the enhancement and optimization of traffic flow in Manassas, Virginia. The primary objective focuses on enhancing traffic flow through a portion of Prince William County. The secondary objective is to reduce the median traffic transit time for vehicles that go through the area. With these two measures, the team has been provided critical foundational data provided by their sponsor, ASSETT, Inc., which includes a traffic analysis provided at intersections in the area. The data is also supplemented with VDOT traffic data from their public website. To assess capacity of the road network, simulated data was also input for random trips in the network. The team used their knowledge of data science and data engineering, along with tools for traffic analysis, such as Simulation of Urban Mobility (SUMO), OpenStreetmaps, NetEdit, and TraCI. The team developed a series of models which varied the traffic volume patterns (routes), traffic quantities, and traffic light timing and sequencing. The results were analyzed and reported on a 24-hour period by traffic-in, traffic-out, total flow, and median transit times. To aid in the realism of the simulation, other factors, such as pedestrian traffic, emergency vehicle transit, and traffic degradation from disabled vehicles, were added in the later phases of analysis. The results of these simulations provided a series of vehicle profiles by time of day and on an aggregate as well as at key intersections. These analyses will aid ASSETT, Inc. in their understanding of traffic patterns in the Northern Virginia area and provide them with an in-depth analysis of traffic flow optimization and enhancement opportunities.