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A new schedule-based transit assignment model with travel strategies and supply uncertainties

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A new schedule-based transit assignment model with travel strategies and supply uncertainties. / Hamdouch, Younes; Szeto, W. Y.; Jiang, Y.
In: Transportation Research Part B: Methodological, Vol. 67, 09.2014, p. 35-67.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Hamdouch, Y, Szeto, WY & Jiang, Y 2014, 'A new schedule-based transit assignment model with travel strategies and supply uncertainties', Transportation Research Part B: Methodological, vol. 67, pp. 35-67. https://doi.org/10.1016/j.trb.2014.05.002

APA

Hamdouch, Y., Szeto, W. Y., & Jiang, Y. (2014). A new schedule-based transit assignment model with travel strategies and supply uncertainties. Transportation Research Part B: Methodological, 67, 35-67. https://doi.org/10.1016/j.trb.2014.05.002

Vancouver

Hamdouch Y, Szeto WY, Jiang Y. A new schedule-based transit assignment model with travel strategies and supply uncertainties. Transportation Research Part B: Methodological. 2014 Sept;67:35-67. Epub 2014 Jun 4. doi: 10.1016/j.trb.2014.05.002

Author

Hamdouch, Younes ; Szeto, W. Y. ; Jiang, Y. / A new schedule-based transit assignment model with travel strategies and supply uncertainties. In: Transportation Research Part B: Methodological. 2014 ; Vol. 67. pp. 35-67.

Bibtex

@article{915a17118cdf4f2d95f632e12ef85674,
title = "A new schedule-based transit assignment model with travel strategies and supply uncertainties",
abstract = "This paper proposes a new scheduled-based transit assignment model. Unlike other schedule-based models in the literature, we consider supply uncertainties and assume that users adopt strategies to travel from their origins to their destinations. We present an analytical formulation to ensure that on-board passengers continuing to the next stop have priority and waiting passengers are loaded on a first-come-first-serve basis. We propose an analytical model that captures the stochastic nature of the transit schedules and in-vehicle travel times due to road conditions, incidents, or adverse weather. We adopt a mean variance approach that can consider the covariance of travel time between links in a space time graph but still lead to a robust transit network loading procedure when optimal strategies are adopted. The proposed model is formulated as a user equilibrium problem and solved by an MSA-type algorithm. Numerical results are reported to show the effects of supply uncertainties on the travel strategies and departure times of passengers. (C) 2014 Elsevier Ltd. All rights reserved.",
keywords = "User equilibrium, Schedule-based transit assignment, Strategy, Supply uncertainty, EQUILIBRIUM ASSIGNMENT, CAPACITY CONSTRAINTS, TRAFFIC ASSIGNMENT, TRANSPORT NETWORK, TIME VARIABILITY, USER EQUILIBRIUM, MARKET REGIMES, BUS ROUTE, FREQUENCY, DESIGN",
author = "Younes Hamdouch and Szeto, {W. Y.} and Y. Jiang",
year = "2014",
month = sep,
doi = "10.1016/j.trb.2014.05.002",
language = "English",
volume = "67",
pages = "35--67",
journal = "Transportation Research Part B: Methodological",
issn = "0191-2615",
publisher = "PERGAMON-ELSEVIER SCIENCE LTD",

}

RIS

TY - JOUR

T1 - A new schedule-based transit assignment model with travel strategies and supply uncertainties

AU - Hamdouch, Younes

AU - Szeto, W. Y.

AU - Jiang, Y.

PY - 2014/9

Y1 - 2014/9

N2 - This paper proposes a new scheduled-based transit assignment model. Unlike other schedule-based models in the literature, we consider supply uncertainties and assume that users adopt strategies to travel from their origins to their destinations. We present an analytical formulation to ensure that on-board passengers continuing to the next stop have priority and waiting passengers are loaded on a first-come-first-serve basis. We propose an analytical model that captures the stochastic nature of the transit schedules and in-vehicle travel times due to road conditions, incidents, or adverse weather. We adopt a mean variance approach that can consider the covariance of travel time between links in a space time graph but still lead to a robust transit network loading procedure when optimal strategies are adopted. The proposed model is formulated as a user equilibrium problem and solved by an MSA-type algorithm. Numerical results are reported to show the effects of supply uncertainties on the travel strategies and departure times of passengers. (C) 2014 Elsevier Ltd. All rights reserved.

AB - This paper proposes a new scheduled-based transit assignment model. Unlike other schedule-based models in the literature, we consider supply uncertainties and assume that users adopt strategies to travel from their origins to their destinations. We present an analytical formulation to ensure that on-board passengers continuing to the next stop have priority and waiting passengers are loaded on a first-come-first-serve basis. We propose an analytical model that captures the stochastic nature of the transit schedules and in-vehicle travel times due to road conditions, incidents, or adverse weather. We adopt a mean variance approach that can consider the covariance of travel time between links in a space time graph but still lead to a robust transit network loading procedure when optimal strategies are adopted. The proposed model is formulated as a user equilibrium problem and solved by an MSA-type algorithm. Numerical results are reported to show the effects of supply uncertainties on the travel strategies and departure times of passengers. (C) 2014 Elsevier Ltd. All rights reserved.

KW - User equilibrium

KW - Schedule-based transit assignment

KW - Strategy

KW - Supply uncertainty

KW - EQUILIBRIUM ASSIGNMENT

KW - CAPACITY CONSTRAINTS

KW - TRAFFIC ASSIGNMENT

KW - TRANSPORT NETWORK

KW - TIME VARIABILITY

KW - USER EQUILIBRIUM

KW - MARKET REGIMES

KW - BUS ROUTE

KW - FREQUENCY

KW - DESIGN

U2 - 10.1016/j.trb.2014.05.002

DO - 10.1016/j.trb.2014.05.002

M3 - Journal article

VL - 67

SP - 35

EP - 67

JO - Transportation Research Part B: Methodological

JF - Transportation Research Part B: Methodological

SN - 0191-2615

ER -