With the Transit-HUB app, Nashville residents, commuters and visitors can plan trips using public transit, compare trip options, watch real-time bus locations, receive smart trip notifications and get step-by-step navigation.



To know more about the application and the T-HUB Decision Support system, watch the video.

Acknowledgement: Research on Transit-Hub is sponsored under a research grant from National Science Foundation.

Any opinions, findings, and conclusions or recommendations expressed on this page are that of the T-Hub team and do not necessarily reflect the views of NSF.

Key features of the app include a real-time bus tracker, navigation, service alert notifications, calendar-based personal transit schedule management / notification and a comparison view to evaluate different trip options. By making public transit more predictable, the app encourages customers to use public transit more often. The comparative route view compares public transit options against the cost of using a car. A summary view provides the cumulative time customers have spent using public transit, and that information can be shared with friends.

This system is powered by real-time vehicle locator data provided by the Nashville MTA and cloud-based smart analytic services developed by the SCOPE and MAGNUM labs at Vanderbilt’s Institute for Software Integrated Systems under a research project sponsored by the National Science Foundation (NSF).

Trip Management and Real-Time Navigation


  • Supports recurring trips and Supports calendar integration
  • Estimated trip time considering the current or typical delay
  • Provide comparitive view
    • Fuel savings
    • Calories burned
    • Impact points
  • Compare details between suggested transit routes and driving car
  • Select the routes to enter details view
  • Tap "Go" button to depart now and enter navigation mode
  • Tap "Add" button to add the route to Trips
  • Active assist for the next planned trip
  • Follow the step-by-step navigation to your destination
  • Track your bus's location on the map
  • See how much time is left to get on the bus
  • Tap the check marker for next step
  • Configurable notifications for the next bus.
  • Replan scheduled trip.
  • Set recurring trips.
  • Hold to enter/resume real-time navigation mode
  • See service alerts that affect your trips.
  • Share your trips with friends (coming soon)

Route-based Real-Time Query Mode


  • Designed for people who are familiar with the routes and just want to know where the buses are and how long is the estimated waiting time.
  • Select route and direction.
  • Track real-time bus locations on the route.
  • Select a stop on the map and get the estimated arrival time for current and future bus on that route.
  • Compare arrival time between buses.
  • Time On Bus: User's total time on the bus
  • Time Walking: User's total time walking
  • Calories Burned: Calculated from total walking distances
  • Cost of Gas Saved: Total gas saving from taking the buses compared to driving cars

T-HUB Decision Support System

The hub supports real-time notifications and alerts to help riders track their routes and potential delays, as well as facilitate information flow (dynamic route demand) from potential riders to transit service providers. A critical aspect of this work is an integrated analytics and simulation engine, which allows riders to plan future trips, evaluating multiple trip options simultaneously. It enables city officials to assess and improve the efficacy of transit options based on models generated from ridership data. This work integrates several data streams generated from sensors including automated vehicle locators, personal smart phones and beacons.

ANALYTICS ENGINE

  • Analytics engine helps identify patterns leading to delays and can help revise the transit schedules.
  • The source of data includes the Automated Vehicle Locator information from the buses and the static transit schedule from Nashville MTA.
  • Data is grouped into clusters using sihouette analysis and K-Means algorithm, based on the delay and time of the day.
  • Historical data is used to create aggregate models for anomalous operation identification and future prediction.
  • Future capabilities include crowdsouring data and a monte carlo simulation for analyzing data aggregates across multiple routes.

Meet Our Team!

Dr. Abhishek Dubey, PI

Dr. Abhishek Dubey is a Research Scientist at the Institute for Software Integrated Systems in Vanderbilt University. He is the principal investigator for the transit hub project.

Dr. Jules White

Dr. Jules White is an Assistant Professor of Computer Science and Engineering at Vanderbilt University, Nashville, TN.

Dr. Sandeep Neema

Dr. Sandeep Neema is a Research Associate Professor of Computer Science and Engineering at Vanderbilt University, Nashville, TN.

Dr. Aniruddha Gokhale

Dr. Aniruddha Gokhale is an Associate Professor of Computer Science and Engineering at Vanderbilt University, Nashville, TN.

Fangzhou Sun, Lead Developer

Fangzhou Sun is a Graduate Research Assistant at Institute for Software-Integrated Systems and a PhD. candidate at Vanderbilt Univeristy.

Shashank Shekhar

Shashank Shekhar is a Graduate Research Assistant at Institute for Software-Integrated Systems and a PhD. candidate at Vanderbilt Univeristy.

Himanshu Neema

Himanshu Neema has a M.S. in Computer Science from Vanderbilt University. He is a Senior Staff Engineer at Institute for Software-Integrated Systems.

Dr. Janos Sztipanovits, advisor

Dr. Janos Sztipanovits is the E. Bronson Ingram Distinguished Professor of Engineering at Vanderbilt University. He is founding director of the Institute for Software Integrated Systems.

Our Collaborators

Metropolitan Transit Authority, Nashville

Siemens, Corporate Technology

Got a question?

Send an email to Abhishek Dubey: dabhishe at isis dot vanderbilt dot edu

Visit http://www.isis.vanderbilt.edu/ for more information about our research group.

Project Status

Idea Complete
Development Complete
In Beta Test
Deployed
Commercialized

Acknowledgement: Research on Transit-Hub is sponsored under a research grant from National Science Foundation. Any opinions, findings, and conclusions or recommendations expressed on this page are that of the T-Hub team and do not necessarily reflect the views of NSF.


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