METAFERW

Modeling and controlling traffic congestion and propagation in large-scale urban multimodal networks

Coordinatore	ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE    more Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.
Nazionalità Coordinatore	Switzerland [CH]
Totale costo	1˙242˙162 €
EC contributo	1˙242˙162 €
Programma	FP7-IDEAS-ERC Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	ERC-2013-StG
Funding Scheme	ERC-SG
Anno di inizio	2014
Periodo (anno-mese-giorno)	2014-02-01   -   2019-01-31

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE  Organization address address: BATIMENT CE 3316 STATION 1 city: LAUSANNE postcode: 1015 contact info Titolo: Dr. Nome: Caroline Cognome: Vandevyver Email: send email Telefono: +41 21 693 35 73 Fax: +41 21 6935583	CH (LAUSANNE)	hostInstitution	1˙242˙162.00
2	ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE  Organization address address: BATIMENT CE 3316 STATION 1 city: LAUSANNE postcode: 1015 contact info Titolo: Mr. Nome: Nikolaos Cognome: Geroliminis Email: send email Telefono: 41216932481 Fax: 4126932479	CH (LAUSANNE)	hostInstitution	1˙242˙162.00

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 Obiettivo del progetto (Objective)

'As cities grow rapidly and more people through different modes compete for limited urban road infrastructure to travel, it is important to manage traffic space to improve accessibility for travelers. This project tackles the problem of modeling and optimization in large-scale congested traffic networks with an aggregated realistic representation of dynamics and route choice and multiple modes of transport. This is a highly motivating problem both because of the socio-economic influence of congestion and the challenges embedded in the optimization framework and the modeling aspects. Currently most optimization methods for transport networks (i) are suited for toy networks with simplified dynamics that are far from real-sized networks, (ii) apply decentralized control, which is not appropriate for heterogeneously loaded networks, (iii) investigate engineering solutions through micro-simulation models and scenario analysis that make the problem intractable in real time, (iv) are not considering interactions and conflicts between transport modes (car, bus, delivery vehicle). This problem is even more challenging if one considers that transportation networks have a hierarchical structure with freeways and urban roads with mixed or separated traffic (e.g. bus-only lanes), that have dissimilar traffic flow dynamics. Lack of coordination among the jurisdictions during traffic operations or limited means of traffic data monitoring and communication can impede such mixed traffic network ideal goal. Traditionally, choices of people in transportation networks are based on equilibrium conditions with small variations.The huge amount of datasets (including thousands of GPS data from taxis, cars and buses and road detector data from heavily populated cities worldwide) can provide a unique way to understand how really people make choices, how these choices affect the development and spreading of congestion in networks and integrate them in the macroscopic dynamics and optimization'