A Generalized Collaboration Model for Rideshare and Transit Service Providers

1 Research Work

- A Generalized Collaboration Model for Rideshare and Transit Service Providers to Facilitate First- and Last-Mile Services 

Submitted by: Vishal Kushwaha

Advisors: Prof. Rajesh Sundaresan and Prof. Abdul R. Pinjari

Summary of the research undertaken: The rideshare service providers (RSPs), e.g., Ola, Uber etc., are gaining popularity among travelers because of their special service structure. Their service features include on-demand rides, door-to-door connectivity, personalized rides etc. However, due to this increasing popularity, the city transportation planners are concerned that the congestion levels on the roads may increase. On the other hand, the public transit (e.g., bus, metro etc.) agencies are observing a decline in ridership due to the emergence of other travel modes such as RSPs. Also, the transit stops may be located far away from travelers’ homes or activity locations which discourages public transit use. Due to these issues, efforts are being made to make the RSPs and public transit agencies collaborate. In such collaboration frameworks, the RSPs will provide connectivity between transit stops and travelers’ home and activity locations. The transit agencies will provide connectivity on the long-haul part of the journey. However, the literature lacks modeling methods to facilitate such collaborations.

In this regard, we proposed a tri-level game theory, discrete mode choice theory, and route choice theory based model to determine optimal travel prices for such a travel mode. The model has the bus agency at the top, the RSPs in the middle, and the travelers at the bottom. The bus agency and the RSPs play a Stackelberg game to determine the optimal price of the collaborative service. Depending on the price set by the collaborating agencies, the travelers make the mode and the route choice. The model is applied to a part of the Bangalore traffic network. The simulation results show an increase in profits and market shares of the RSPs and the bus agency. The collaborative travel mode turns out to be an attractive option for the travelers in terms of travel price and travel time. A system-wide reduction in travel times and carbon dioxide emissions is also observed.
In this regard, we proposed a tri-level game theory, discrete mode choice theory, and route choice theory based model to determine optimal travel prices for such a travel mode. The model has the bus agency at the top, the RSPs in the middle, and the travelers at the bottom. The bus agency and the RSPs play a Stackelberg game to determine the optimal price of the collaborative service. Depending on the price set by the collaborating agencies, the travelers make the mode and the route choice. The model is applied to a part of the Bangalore traffic network. The simulation results show an increase in profits and market shares of the RSPs and the bus agency. The collaborative travel mode turns out to be an attractive option for the travelers in terms of travel price and travel time. A system-wide reduction in travel times and carbon dioxide emissions is also observed.
In this regard, we proposed a tri-level game theory, discrete mode choice theory, and route choice theory based model to determine optimal travel prices for such a travel mode. The model has the bus agency at the top, the RSPs in the middle, and the travelers at the bottom. The bus agency and the RSPs play a Stackelberg game to determine the optimal price of the collaborative service. Depending on the price set by the collaborating agencies, the travelers make the mode and the route choice. The model is applied to a part of the Bangalore traffic network. The simulation results show an increase in profits and market shares of the RSPs and the bus agency. The collaborative travel mode turns out to be an attractive option for the travelers in terms of travel price and travel time. A system-wide reduction in travel times and carbon dioxide emissions is also observed.
In this regard, we proposed a tri-level game theory, discrete mode choice theory, and route choice theory based model to determine optimal travel prices for such a travel mode. The model has the bus agency at the top, the RSPs in the middle, and the travelers at the bottom. The bus agency and the RSPs play a Stackelberg game to determine the optimal price of the collaborative service. Depending on the price set by the collaborating agencies, the travelers make the mode and the route choice. The model is applied to a part of the Bangalore traffic network. The simulation results show an increase in profits and market shares of the RSPs and the bus agency. The collaborative travel mode turns out to be an attractive option for the travelers in terms of travel price and travel time. A system-wide reduction in travel times and carbon dioxide emissions is also observed.