Is this project an undergraduate, graduate, or faculty project?
Graduate
individual
What campus are you from?
Daytona Beach
Authors' Class Standing
Rogelio Gracia Otalvaro, PhD Graduate Student
Lead Presenter's Name
Rogelio Gracia Otalvaro
Faculty Mentor Name
Bryan C. Watson
Abstract
To address the mounting challenges posed by traffic congestion and air pollution within urban city centres, authorities are implementing measures concerning private mobility restrictions and regulations. Public transportation and car-sharing have both increased in popularity at the same time, changing the way people move around. The main objective of this study is to determine if the exists a ratio between private to public transportation that would reduce traffic congestion, transit times, and how to calculate it.
Utilizing an agent-based model, we simulate the traffic dynamics of a hypothetical city to evaluate the effects of different proportions of transportation modes on the city's traffic and pollution scenarios. The base model of the city has a 4 nodal layout, where agents are created at any of the nodes with another destination node assigned and a form of transport selected. Each simulation tests a different private to public car ratio and measures how many people arrive to their destinations, and how long does it take them to reflect efficiency of each private to public transport ratio.
The results of this study could set a benchmark for politicians and traffic regulators to aim at, as it could help promote public transportation by proving they could significantly mitigate traffic congestion and pollution.
Did this research project receive funding support from the Office of Undergraduate Research.
No
Metropolitan Transit Simulation: Assessing the Symbiosis of Public and Private Mobility
To address the mounting challenges posed by traffic congestion and air pollution within urban city centres, authorities are implementing measures concerning private mobility restrictions and regulations. Public transportation and car-sharing have both increased in popularity at the same time, changing the way people move around. The main objective of this study is to determine if the exists a ratio between private to public transportation that would reduce traffic congestion, transit times, and how to calculate it.
Utilizing an agent-based model, we simulate the traffic dynamics of a hypothetical city to evaluate the effects of different proportions of transportation modes on the city's traffic and pollution scenarios. The base model of the city has a 4 nodal layout, where agents are created at any of the nodes with another destination node assigned and a form of transport selected. Each simulation tests a different private to public car ratio and measures how many people arrive to their destinations, and how long does it take them to reflect efficiency of each private to public transport ratio.
The results of this study could set a benchmark for politicians and traffic regulators to aim at, as it could help promote public transportation by proving they could significantly mitigate traffic congestion and pollution.