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https://nap.nationalacademies.org/catalog/27432/critical-issues-in-transportation-for-2024-and-beyond

Multi-Modal Optimization

The objective of this project is to develop the multi-modal optimization model, which will operate at a planning level and generate an optimal design for a multi-modal on-demand transit system given the input demand and constraints. Optimization models provide a means of providing the best possible outcome as measured by an objective, subject to a set of constraints. The starting point for this model was developed for a NSF-funded project - Socially Aware Mobility (SAM) project – that seeks to design coordinated microtransit systems in large, congested cities. These systems combine on-demand transit that serve low-density regions with high-occupancy vehicles (buses or trains) traveling along high-density corridors. These systems combine on-demand transit (cars or vans) that serves low-density regions with high-occupancy vehicles (buses or trains) traveling along high-density corridors. The scheduling and dispatching of vehicles is coordinated holistically and optimized to achieve socially desirable outcomes such as mitigating congestion, decreasing cost, improving accessibility, and providing the service efficiently. The models are being simultaneously developed in a collaboration with staff from SFCTA and MTC in San Francisco, and with WFRC and UTA in Salt Lake City. These external collaborators join weekly meetings to inform of local situations, supply data, and learn of the project’s progress and purposes.