Design of a Demand Responsive Transport service using Distributed Constraint Optimization for airport access

Conference Paper (2023)
Author(s)

I.A. Parmaksizoglou (TU Delft - Air Transport & Operations)

A. Bombelli (TU Delft - Air Transport & Operations)

A Sharpanskykh (TU Delft - Air Transport & Operations)

Research Group
Air Transport & Operations
Copyright
© 2023 I.A. Parmaksizoglou, A. Bombelli, Alexei Sharpanskykh
DOI related publication
https://doi.org/10.1109/MT-ITS56129.2023.10241535
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 I.A. Parmaksizoglou, A. Bombelli, Alexei Sharpanskykh
Research Group
Air Transport & Operations
ISBN (electronic)
978-1-6654-5530-5
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Accessibility is one of the key performance indicators in the evaluation of a multimodal transport system and, as a result, transport planning has become increasingly more oriented towards it. Demand Responsive Transport (DRT) services have been proposed as a measure for increasing accessibility of a Public Transit (PT) network by servicing users in inaccessible areas. Through multimodal planning and coordination, a DRT service can be integrated within the extended PT network and supply the network optimally. In the context of PT users headed toward airports, an integrated DRT service is proposed for those with extended first-mile connections. This service makes use of taxis to transport users to transit points of a dedicated train line supplying a major European airport. Ride-sharing is considered, while optimal order of service and transit points for modal change are determined. To capture the decentralized nature of matching taxis to users, a multi-agent-based algorithm based on Distributed Constraint optimization Problems (DCOPs) is developed. Real-time information about routes and fixed schedules of the PT network are extracted via a dedicated routing Application Programming Interface (API). Experiments validate the applicability of the proposed solution by reporting a decrease in users’ first-mile travel time that is approximately analogous to the modal share the service captures.

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