Quick Sub-optimal Augmentation of Large Scale Multi-modal Transport Networks

Autor: Mathieu Petit, Nour-Eddin El Faouzi, Angelo Furno, Elise Henry
Přispěvatelé: Laboratoire d'Ingénierie Circulation Transport (LICIT UMR TE ), École Nationale des Travaux Publics de l'État (ENTPE)-Université de Lyon-Université Gustave Eiffel, RP1-S19100 , PROMENADE, Platform for Resilient Multi-modal Mobility via Multi-layer Networks & Real-time Big-Data Processing
Rok vydání: 2021
Předmět:
Zdroj: Studies in Computational Intelligence ISBN: 9783030653507
COMPLEX NETWORKS (2)
COMPLEX NETWORKS 2020, The Ninth International Conference on Complex Networks and their Applications
COMPLEX NETWORKS 2020, The Ninth International Conference on Complex Networks and their Applications, Dec 2020, Madrid, Spain. pp218-230, ⟨10.1007/978-3-030-65351-4_18⟩
DOI: 10.1007/978-3-030-65351-4_18
Popis: COMPLEX NETWORKS 2020, The Ninth International Conference on Complex Networks and their Applications, Madrid, ESPAGNE, 01-/12/2020 - 03/12/2020; With the recent and continuous growth of large metropolis, the development, management and improvement of their urban multi-modal transport networks become a compelling need. Although the creation of a new transport mode often appears as a solution, it is usually impossible to construct at once a full networked public transport. Therefore, there is a need for efficient solutions aimed at prioritizing the order of construction of the multiple lines or transport modes. Hence, the proposed work aims at developing a simple and quick-to-compute methodology aimed at prioritizing the order of construction of the lines of a newly designed transport mode by maximizing the network performance gain, as described by complex networks metrics. In a resilience context, the proposed methodology could also be helpful to support the rapid and quick response to disruptions by setting up or reinforcing an adapted emergency transport line (e.g., bus service) over a set of predefined itineraries.
Databáze: OpenAIRE