Optimizing stakeholders' objectives in a real-time multimodal mobility hub system

Ridesharing could offer a solution to urban mobility challenges by delivering affordability and convenience while reducing congestion and environmental impact. This paper presents a system for multimodal mobility hubs with parking facilities, integrating personal vehicles with carpooling options and shuttle services into a cohesive network designed to accommodate real-time inbound and outbound ride requests. To address diverse interests and priorities within urban transportation, a column generation approach is employed to optimize the objectives of key stakeholders. An extensive computational study is performed using real-world public transit and ridesharing datasets from Qu´ebec City. The emission, user, and system objectives favor shared transportation options, while the operator objective shows a more substantial reliance on solo vehicles. Additionally, the results indicate that a transition to fully electric vehicles powered by a renewable energy mix can reduce average emissions by 78.1% compared to a scenario with gasoline-fueled vehicles. Rigorous evaluation across diverse scenarios demonstrates the proposed system’s efficacy in addressing the complexities of large-scale transportation systems.

Uncontrolled Keywords

• Real-time ridesharing
• column generation
• multimodal transportation
• mobility hub