Microtransit refers to an on-demand, dynamically routed, mobile-app-powered shuttle service with rider walking exchange. Microtransit is an emerging transit service that seems to improve riders’ experience by operating small-sized shuttles that can offer flexible routes and on-demand scheduling services. It is essentially a “smart bus service,” similar to the service of transportation network companies such as Uber and Lyft in which riders are required to book a trip using a smartphone app and get picked up in minutes at a corner by exchanging a short walk distance (walking exchange) or just waiting at the original address (door-to-door). The user may be matched with other passengers heading in the same direction to share their trips, defined as “ridesharing.” An increasing number of places are deploying microtransit to serve their residents and visitors, such as L.A. Metro in Los Angeles, California and King County Metro in Seattle, Washington. Most microtransit services integrate into existing public transit systems, such as city buses, to enhance transit service where running fixed-route buses is rather challenging.

This project is aimed at developing a simulation-based decision-making toolkit to help transit agencies evaluate microtransit service performance, optimize its operation, and make evidence-based decisions on resource distribution. Existing simulation models do not adequately represent on-demand microtransit with ride walking exchange, which makes it difficult to optimize the system and make decision with some assurance. The proposed open source microtransit simulation toolkit will be flexible and can be easily modified to apply to any place or community in any scenario. 

The proposed microtransit simulation toolkit will be based on the Simulation of Urban Mobility (SUMO) package. The flexibility and compatibility of the toolkit as a platform will enable its integration with rider walking exchange and vehicle operations, such as pick up and drop off (PUDO) strategy, or as “plugin-and-play” functional modules. A greedy heuristic shuttle routing approach will be developed for efficiently solving large scale shuttle-rider matching and routing problem, which is a major road blocker for simulating real world microtransit systems. Partnering with the city of Wilson, North Carolina, the proposed microtransit simulation toolkit will be calibrated and validated with real-world traffic and microtransit operation data. In addition, a simulation-based recursive framework will be proposed to quantitively describe the interplay between microtransit’s ride demand and behavior, supply (e.g., system operation and design) and service (e.g., waiting time) and provide a complete and systematic solution for optimizing microtransit systems. Finally, a webpage interface will be designed to take the system design inputs and display simulation and optimization results through a graphical user interface (GUI) on a website. The toolkit can be easily applied by transit agencies interested in testing different operation scenarios for their microtransit systems. 

The benefits of deploying on-demand microtransit are expected to be significant in the light of socio-economy and mobility while enhancing transportation equity, mobility convenience, job access, and reducing traffic congestion, energy consumption, and greenhouse gas emissions.