A stochastic process approach for frequency-based transit assignment with strict capacity constraints
type: Item
instance of: scholarly article
title: A stochastic process approach for frequency-based transit assignment with strict capacity constraints
zbMATH Open document ID: 1169.60026
author: Fitsum Teklu
published in: Networks and Spatial Economics
publication date: 2009-06-16T00:00:00Z
review text: The present paper deals with Stochastic process (SP) models considered to the day-to-day dynamics of the transit demand-supply system, explicitly modelling passengers' information acquisition and decision processes. A Monte Carlo simulation based SP model that includes strict capacity constraints is treated. It uses micro-simulation to constrain passenger flows to capacities and obtain realistic cost estimates. Applications of the model and its comparison with the \textit{J. De Cea} and \textit{E. Fernandez} [Transp. Sci. 27, No. 2, 133--147 (1993; Zbl 0788.90030)] model are presented using a small network.
reviewed by: János Sztrik
Mathematics Subject Classification ID: 60K30
zbMATH DE Number: 5565180
zbMATH Keywords: transit assignment
zbMATH Keywords: stochastic process
zbMATH Keywords: strict capacity
zbMATH Keywords: day-to-day dynamics
describes a project that uses: pyuvdata
MaRDI profile type: Publication
full work available at URL: s11067-007-9046-3
OpenAlex ID: W2009895118
cites work: Dynamic Processes and Equilibrium in Transportation Networks: Towards a Unifying Theory
cites work: Common-Lines and Passenger Assignment in Congested Transit Networks
cites work: Large Population Approximations of a General Stochastic Traffic Assignment Model
cites work: Transit Assignment for Congested Public Transport Systems: An Equilibrium Model
cites work: Capacitated transit assignment with loading priorities.
cites work: Capacity constrained transit assignment with common lines
cites work: Equilibrium traffic assignment for large scale transit networks
cites work: Transit Equilibrium Assignment: A Model and Solution Algorithms
DOI: 10.1007/S11067-007-9046-3
description: scientific article; zbMATH DE number 5565180