Lead Presenter Biography

Parag Gupta, a data science enthusiast, and seasoned travel demand modeler with 7 years of experience. With a passion for leveraging data to drive strategic decision-making, Parag Gupta has developed expertise in creating and implementing predictive models to forecast travel demand for various modes of transportation. Over the years, Parag Gupta has honed their skills in statistical analysis, data visualization, and data communication. He has successfully used these tools to identify trends and patterns in travel data. In their most recent role, Parag Gupta was instrumental in developing SERPM 9 External Travel Demand model, Congestion Dashboard, Desktop Application for RSLAM (Richmond Simplified Land Use Allocation Model) and various post processing tools for TDM which has improved decision-making and enhanced the overall user experience. With a strong work ethic, Parag Gupta is committed to continuously improving their skills and staying up to date with the latest industry advancements.

Co-Authors

Presentation Description

Congestion is the number one problem that American cities face. No other problems touch as many lives on a daily basis as congestion does. Traffic congestion causes increase in emissions, severe air pollution and contributes to global warming. In an effort to promote positive investments towards climate and foster sustainable development sensitive to natural resources Lee County Metropolitan Planning Organization (MPO) Congestion Dashboard was developed.
LEE MPO Congestion Dashboard is a modern web-based user interface tool developed in R programming language, that is an open-source software environment for statistical computing and graphics. It takes advantage of the state-of-the-art Shiny package that makes it easy to build interactive web-apps straight from R. These applications can be hosted as standalone on webpage or embed in R to use them as desktop applications.
Data utilized in the dashboard is sourced from NAVSTREETS Street Data by HERE technologies, obtained from Florida Department of Transportation (FDOT). This data contains high spatial resolution of roadways (down to local streets), descriptive attributes like facility types, number of lanes, speed limits etc., along with their geometry. Final spatial dataset is filtered for LEE-MPO and neighboring counties. This dataset is analyzed by joining the processed pattern speed table (for weekdays and weekends) to get final congested speed. Congestion ratios, calculated by dividing posted speed limit by congested speed, are interactively displayed at 15-minute intervals for peak-periods. For weekdays peak period ranges from 0600-0900 hours (AM Peak Period) and 1500-1800 hours (PM Peak Period). For weekends, peak periods range from 0900-1200 hours (AM Peak Period) and 1200-1500 hours (PM Peak Period).
Users can interact with the dashboard by selecting a desired time interval. Over eighty thousand observations are processed to analyze the congestion speed for the selected time periods. Various descriptive statistics like maximum AM/PM congestion ratio, total roadway links congested, and total roadway features congested are also displayed for the time-period selected.
Users can navigate, zoom, and pan to their locations of choice while simultaneously viewing the congestion for AM and PM periods. This helps in comparing and contrasting the roadways to see the effect of congestion in different time periods. The visualization takes advantage of modern-JavaScript library Leaflet for displaying interactive maps and WebGL API to render 2D and 3D graphics. This also helps in giving a frictionless experience by significantly reducing the time-lags needed in rendering eighty thousand links on the interactive map tile layer. Other tabs of the dashboard show the total percentage growth in the population, and the employment of the region by visualizing a Choropleth map of TAZs (Travel Analysis Zones). And a network map that displays the volume to capacity ratios (level of service) from the official travel demand model for the horizon year, 2045. Overall, user experience designed is simple, colorful, and easy to navigate. The tool designed displays relative strength in conveying information and can be modified to user’s needs quickly. It has the potential to generate strategic visons with evidence that is needed by transportation planners in the twenty-first century. 

Presentation File