Integrating Demand Responsive Applications Across Fixed Transit and Transportation Networking Company Operations Can Address 60 Percent of Trips to Improve Traveler Cost, Time, and Equity Measures.

A Simulation Study Assessed Benefits of Incorporating Demand Responsive Travel Options into Fixed Transit Systems to Maximize Coverage in Low Population Density Areas.

Date Posted

Connecting Demand Response Transit with Fixed Service Transit

Summary Information

One advantage of Demand Responsive Transit (DRT) is its ability to address the transportation needs of rural populations, particularly in geographically dispersed areas, due to their capability to combine flexible or customizable service with cost-efficiency. Fixed Route Transit (FRT) is adept at catering to the travel demands of urban populations. The coverage of FRT in the low population density areas can be expanded by connecting FRT and DRT. This study aimed to improve the existing FRT system in Morristown, Tennessee by connecting FRT with the DRT system. Morristown’s FRT serviced three different routes and 29 stops (as of 2019-2020) and the city also maintained a functioning DRT service. This study also assessed possible collaboration with Transportation Networking Companies (TNC). Various scenarios featuring multiple modes and legs were modeled using an agent-based simulation, incorporating TNCs alongside FRT and DRT. The study calculated the best performing scenario in terms of the total system cost for every Origin-Destination (OD) pair.


The methodology entailed collecting passenger data, creating a sketch planning tool for connecting FRT with DRT and TNC, and determining the operational and economical aspects of coordination. The DRT data were collected from July 2019 to June 2020. Demand data were collected from the transit agency and cost and travel matrices were created for every OD pair, 381 in total, with route assignment for each trip performed for eight different scenarios that represented various combinations of the FRT, DRT, and TNC systems to complete a trip (i.e., Integrated Scenario). Every trip was assumed to have up to three legs and use three modes. A total of eight scenarios were created and two key scenarios are described below:

  • Base Scenario: DRT-DRT: Passengers take a DRT from the nearest node and completes the trip using the same service, disregarding the FRT stops.
  • DRT-FRT: The coordinated scenarios of DRT with FRT, where passengers take a DRT to reach the nearby FRT stop and completes the trip in an FRT, or passengers reach the nearby FRT stop to the destination and continue using DRT services to reach the destination, or both (i.e., DRT-FRT-DRT).

The obtained data was utilized to replicate present field conditions using an agent-based simulation model. The simulation model assumed a homogeneous fleet, with vehicles having the same inputs (capacity, speed, route choice, etc.). The FRT vehicles used fixed predefined routes, and DRT vehicles were modeled as a fleet of vehicles operated by a central dispatching unit that assigned travel requests to vehicles, which provided door-to-door services to passengers.


  • The results revealed that a large amount of the DRT and TNC functions as a feeder to the FRT services in a fully integrated system.
  • With DRT-DRT being the base case, 40 percent of the time they remained as the best option in alternative scenarios. But 60 percent of trips that used DRT-DRT in the base scenario preferred the integrated system based on improvements to cost, time, and equity in alternative scenarios.
  • Out of the DRT-FRT scenario, 56 percent use the DRT-FRT-DRT three-legged option and the FRT-DRT two-legged option with FRT being in the first leg of the trip for 12 percent of the time and DRT serving the first leg for 33 percent.
Results Type
Deployment Locations