Urban public transport optimization by bus ways: a neural network-based methodology

Migliore M; Catalano M

Risultato della ricerca: Chapter

8 Citazioni (Scopus)

Abstract

This paper describes an approach for planning the introduction of bus lanes into the urban road network, that has been applied to the urban area of Palermo. The proposed modelling tool adopts a multi-agent objective function expressing the trade-off between the interests of diverse stakeholders: the generalized transport cost for car drivers and the travel time for public transport users. The reaction of car traffic to a certain planning scenario has been simulated by the DUE assignment technique and the positive impact of the modal shift on the objective function has been tackled by attaching a suitable weight to the time saving for bus passengers. The rise in the bus travel speed, owing to the bus lane solution, has been predicted for a set of urban roads by a neural network, so as to take into account many quantitative and qualitative road attributes. The optimal location pattern of bus ways has been searched by a greedy heuristic that through a step-by-step strategy builds the problem solution by keeping, at each stage, the best alternative.
Lingua originaleEnglish
Titolo della pubblicazione ospiteUrban Transport XIII: Urban Transport and the Environment in the 21st Century
Pagine347-356
Stato di pubblicazionePublished - 2007

Fingerprint

Neural networks
Railroad cars
Planning
Travel time
Costs

All Science Journal Classification (ASJC) codes

  • Architecture
  • Computer Science Applications
  • Safety Research
  • Transportation
  • Arts and Humanities (miscellaneous)
  • Safety, Risk, Reliability and Quality
  • Automotive Engineering
  • Building and Construction
  • Civil and Structural Engineering

Cita questo

Migliore M; Catalano M (2007). Urban public transport optimization by bus ways: a neural network-based methodology. In Urban Transport XIII: Urban Transport and the Environment in the 21st Century (pagg. 347-356)

Urban public transport optimization by bus ways: a neural network-based methodology. / Migliore M; Catalano M.

Urban Transport XIII: Urban Transport and the Environment in the 21st Century. 2007. pag. 347-356.

Risultato della ricerca: Chapter

Migliore M; Catalano M 2007, Urban public transport optimization by bus ways: a neural network-based methodology. in Urban Transport XIII: Urban Transport and the Environment in the 21st Century. pagg. 347-356.
Migliore M; Catalano M. Urban public transport optimization by bus ways: a neural network-based methodology. In Urban Transport XIII: Urban Transport and the Environment in the 21st Century. 2007. pag. 347-356
Migliore M; Catalano M. / Urban public transport optimization by bus ways: a neural network-based methodology. Urban Transport XIII: Urban Transport and the Environment in the 21st Century. 2007. pagg. 347-356
@inbook{2c17594dc76a4caa8a2f5488e55e9f3c,
title = "Urban public transport optimization by bus ways: a neural network-based methodology",
abstract = "This paper describes an approach for planning the introduction of bus lanes into the urban road network, that has been applied to the urban area of Palermo. The proposed modelling tool adopts a multi-agent objective function expressing the trade-off between the interests of diverse stakeholders: the generalized transport cost for car drivers and the travel time for public transport users. The reaction of car traffic to a certain planning scenario has been simulated by the DUE assignment technique and the positive impact of the modal shift on the objective function has been tackled by attaching a suitable weight to the time saving for bus passengers. The rise in the bus travel speed, owing to the bus lane solution, has been predicted for a set of urban roads by a neural network, so as to take into account many quantitative and qualitative road attributes. The optimal location pattern of bus ways has been searched by a greedy heuristic that through a step-by-step strategy builds the problem solution by keeping, at each stage, the best alternative.",
author = "{Migliore M; Catalano M} and Marco Migliore and Mario Catalano",
year = "2007",
language = "English",
isbn = "978-1-84564-087-3",
pages = "347--356",
booktitle = "Urban Transport XIII: Urban Transport and the Environment in the 21st Century",

}

TY - CHAP

T1 - Urban public transport optimization by bus ways: a neural network-based methodology

AU - Migliore M; Catalano M

AU - Migliore, Marco

AU - Catalano, Mario

PY - 2007

Y1 - 2007

N2 - This paper describes an approach for planning the introduction of bus lanes into the urban road network, that has been applied to the urban area of Palermo. The proposed modelling tool adopts a multi-agent objective function expressing the trade-off between the interests of diverse stakeholders: the generalized transport cost for car drivers and the travel time for public transport users. The reaction of car traffic to a certain planning scenario has been simulated by the DUE assignment technique and the positive impact of the modal shift on the objective function has been tackled by attaching a suitable weight to the time saving for bus passengers. The rise in the bus travel speed, owing to the bus lane solution, has been predicted for a set of urban roads by a neural network, so as to take into account many quantitative and qualitative road attributes. The optimal location pattern of bus ways has been searched by a greedy heuristic that through a step-by-step strategy builds the problem solution by keeping, at each stage, the best alternative.

AB - This paper describes an approach for planning the introduction of bus lanes into the urban road network, that has been applied to the urban area of Palermo. The proposed modelling tool adopts a multi-agent objective function expressing the trade-off between the interests of diverse stakeholders: the generalized transport cost for car drivers and the travel time for public transport users. The reaction of car traffic to a certain planning scenario has been simulated by the DUE assignment technique and the positive impact of the modal shift on the objective function has been tackled by attaching a suitable weight to the time saving for bus passengers. The rise in the bus travel speed, owing to the bus lane solution, has been predicted for a set of urban roads by a neural network, so as to take into account many quantitative and qualitative road attributes. The optimal location pattern of bus ways has been searched by a greedy heuristic that through a step-by-step strategy builds the problem solution by keeping, at each stage, the best alternative.

UR - http://hdl.handle.net/10447/7471

M3 - Chapter

SN - 978-1-84564-087-3

SP - 347

EP - 356

BT - Urban Transport XIII: Urban Transport and the Environment in the 21st Century

ER -