A GIS-Based Decision System for Intermodal Security and Safety
or Dr. David Shen, 305-348-1869, email@example.com
Miami downtown area is a critical link in the entire transportation network due to its strategic location and concentration of activities. In the downtown area, there is a concentration of federal, state, county, and city government offices. It has a financial center with a concentration of national and international banks and financial institution located on Brickle Avenue. There are diplomat missions. It is also a popular tourist destination and an art and cultural center, with hotels, marinas, stores and shopping malls, parks, arenas, museums, schools and universities, and a new performing art center in the area. Over 100,000 people live, work, and carry out other types of activities in Miami downtown. Most importantly, it is at a location where Interstate I-95, federal road US-1, two expressways (SR 836 and SR 395), Metrorail, Metromover, and numerous bus routes converge. It is the gateway to both the Port of Miami and Miami Beach and is an intermodal center that connects the east, west, north, and south parts of the county with each other and with the Miami International Airport.
In an emergency situation, not only a massive evacuation may be necessary to allow workers, students, visitors, and tourists to leave the downtown and the Port of Miami (mainly port employees, cruise company employees, and cruise passengers), but the transportation infrastructure must also be protected and traffic flow maintained. Without careful planning, evacuation cannot be carried out successfully and confusion and a lack of traffic control and direction will lead to virtually a shutdown of the transportation network and exposure of the public to safety hazards. To avoid such chaos, plans must be made in advance and real-time traffic conditions need to be monitored to allow evacuation and traffic control plans to be modified under an emergency situation.
The goal of this research is to create a simulation model that allows the estimation and visualization of traffic conditions, which will allow the development of emergency plans. This research will develop a network model for simulation and forecasting traffic information for the control network and predict the short-term traffic condition. The result will be presented in real-time on GIS maps and with 3D visualization.