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1897. Dynamic capacity planning for demand-responsive multimodal transit
Invited abstract in session WC-54: Demand-responsive public transport 2, stream Public Transport Optimization.
Wednesday, 12:30-14:00Room: S01 (building: 101)
Authors (first author is the speaker)
| 1. | Bernardo Martin-Iradi
|
| Institute for Transport Planning and Systems, ETH Zurich | |
| 2. | Francesco Corman
|
| ETH Zurich |
Abstract
Demand-responsive multimodal transit offers opportunities to complement existing public transport systems and provide a better service level to passengers while simultaneously making better use of the resources. This study optimizes the capacity of such a system by strategically sizing the required fleet and allocating it to the operating services. We formulate a two-stage stochastic optimization model that plans the transit system and the required fleet in the first stage and optimizes the demand-responsive operations in the second stage. We develop a decomposition-based method that exploits the network-based formulation of the second stage, allowing us to solve practical instances. Results from a case study in Zurich show that jointly designing and operating public transport and on-demand systems can benefit transport operators and passengers. By allocating the system capacity more efficiently, operators reduce operational costs while maintaining or improving the travel experience for passengers.
Keywords
- Public Local Transportation Systems
- Stochastic Optimization
- Large Scale Optimization
Status: accepted
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