ITS World Congress

The Intelligent Transport System (ITS) industry has been growing exponentially from innovations from corridor management, smart mobility to big data management, ensuring safe and sustainable service and better accessibility for all users. One of the key elements in this is the automation of processes involved in traffic management for more efficient and streamlined approach for traffic operators and planners, a breakthrough which the Regional Integrated Corridor Management System (R-ICMS) project for District 5 (D5) of Florida Department of Transportation (FDOT) has achieved. This project is aimed at managing traffic in the region with a large-scale network during planned or unplanned events occurring on Interstate 4 (I-4) in Orlando metro area, the major corridor in the region. The key element in the D5 R-ICMS is a response plan evaluation module that is triggered either on-demand for planned events or automatically when an anomaly is detected in the network, using a mesoscopic transport model. 

The model is centered along I-4, running from Seminole County down to Osceola County, and including the surrounding tollways and arterials in the region, deployed to a Predictive Engine (PRE) running simulations in real time, and a Decision Support System (DSS) for R-ICMS. Each response plan includes diversion routes and control plan changes that are imported into the model for every evaluation, using inputs from the combination of real-time traffic data, traffic patterns generated from historical traffic data, and network statistics from rolling simulations. For every response plan, the diversion routes and control plan changes are selected by the traffic planners and each element is imported dynamically by the PRE prior to every simulation. The model is linked to a data server where information for the diversion routes and control plan changes are imported. For the diversion routes, the model takes information from a GIS server and dynamically builds a diversion route in the network as called for by the R-ICMS evaluation. For the signals, the model takes information from the TMDD server to build the control plan along the diversion route based on the parameters provided by the operator. Additionally, the model is updated every day to ensure the most current diversion routes and control plans are present in the model. Each response plan scenario, including do-nothing, is scored based on traffic network parameters. The results from each evaluation are sent to the DSS and the response plan with the highest score is activated in real time. 

The project highlights the integration of real-time traffic data importation and setting up different scenarios for each response plan that is dynamically changing according to the needs of the whole network and has proven to be an effective tool in managing traffic in a large-scale network that reaches an urban and suburban population. 

Presentation Agenda 

The key elements in this presentation will focus on the Decision Support System (DSS) component of D5 R-ICMS, while only briefly mentioning the other components of R-ICMS. Below is an outline of the proposed presentation agenda: 

1. High level description of R-ICMS, focusing on Aimsun Live integration and its role in R-ICMS. 
2. Traffic pattern generation using historical data highlighting the methods used in the analysis. 
3. Data integration method between Aimsun Live and R-ICMS. 
4. Description of how Aimsun Live launches continuous and on-demand simulations. 
5. Response plan analysis with high level mention of scoring, and how response plan is implemented.