Simulation and optimization approaches for designing and operating one-way carsharing services in a multimodal transportation network

Abstract

Carsharing services have been studied as a self-standing mode of transportation. However, due to rapid urbanization acceleration and region extension, commuters often combine the fixed route/fixed schedules and carsharing service in one journey. To this end, we study one-way, station-based carsharing in the multimodal transportation system. This work aims two-fold: first, we aim to study the potential of carsharing systems as a feeder to the public transit network. And secondly, we aim to study the impact of carsharing operator’s decisions on the commuters’ demand. To fulfill the first purpose, we propose an integrated route choice and shared vehicle assignment model simulated in an agent-based model based on a case study from the state of Qatar. We further extend the integrated model to include the carpooling option, in which multiple passengers sharing the same route can share the same vehicle. Extensive simulation analyses show that the integration can considerably enhance urban mobility and increase public transportation accessibility through enhanced first and last miles linkages. To study the carsharing supply interaction with the commuters’ demand, we propose a compact mathematical formulation that optimizes the supplier’s profit and the commuters’ convenience. In particular, we study the impact of carsharing operators’ tactical and operational decisions regarding staff size, fleet size, daily relocation, and staff balancing strategies on the commuters’ overall convenience, route, and mode choice. Then, we derive a two-phase approach from the compact formulation to solve realistic instances of the problem in a reasonable computational time. Through extensive experimental results based on realistic instances from the city of Doha-Qatar, we provide managerial insights to the carsharing operators on how the tactical and operational decisions can impact their profit and the commuters’ travel convenience.

Date of Award	2023
Original language	American English
Awarding Institution	HBKU College of Science and Engineering