published journal article

A Link Queue Model of Network Traffic Flow

Transportation Science

Publication Date

March 1, 2021

Author(s)

Abstract

Fundamental to many transportation network studies, traffic flow models can be used to describe traffic dynamics determined by drivers’ car-following, lane-changing, merging, and diverging behaviors. In this study, we develop a deterministic queueing model of network traffic flow, in which traffic on each link is considered as a queue. In the link queue model (LQM), the demand and supply of a link queue are defined in the queue size (number of vehicles), and its in- and out-flows are computed from junction flux functions corresponding to macroscopic merging and diverging rules. The new model is a system of ordinary differential equations that is mathematically tractable and computationally efficient and can capture queue spillbacks and interactions among links. We further demonstrate that the LQM is fundamentally different from the cell transmission model (CTM) and link transmission model (LTM) for a road segment, a signalized ring road, and a diverge-merge network, with respect to the shock and rarefaction waves, network fundamental diagram, and stability property. In a sense, the new model is a space-continuous approximation of the kinematic wave model and can be a useful addition to the multiscale modeling framework of network traffic flow. The model has been applied to formulate and solve network traffic control and observation problems.

Suggested Citation
Wen-Long Jin (2021) “A Link Queue Model of Network Traffic Flow”, Transportation Science, 55(2), pp. 436–455. Available at: 10.1287/trsc.2020.1012.

conference paper

Set Cover-based Formulation and Decomposition Solution Approach for the Crowdsourced Package Delivery Problem

100th Transportation Research Board (TRB) Annual Meeting

Publication Date

January 1, 2021
Suggested Citation
Dingtong Yang, Michael F. Hyland and R. Jayakrishnan (2021) “Set Cover-based Formulation and Decomposition Solution Approach for the Crowdsourced Package Delivery Problem”. 100th Transportation Research Board (TRB) Annual Meeting, Washington, DC.

conference paper

A machine learning approach for localization in cellular environments

2018 IEEE/ION position, location and navigation symposium (PLANS)

Publication Date

April 1, 2018

Author(s)

Ali Abdallah, Samer S. Saab, Zaher Kassas
Suggested Citation
Ali A. Abdallah, Samer S. Saab and Zaher M. Kassas (2018) “A machine learning approach for localization in cellular environments”, in 2018 IEEE/ION position, location and navigation symposium (PLANS). IEEE, pp. 1223–1227. Available at: 10.1109/plans.2018.8373508.

published journal article

Multi-criteria sustainability assessment in transport planning for recreational travel

International Journal of Sustainable Transportation

Suggested Citation
Joseph Y.J. Chow, Sarah V. Hernandez, Ankoor Bhagat and Michael G. McNally (2013) “Multi-criteria sustainability assessment in transport planning for recreational travel”, International Journal of Sustainable Transportation, 8(2), pp. 151–175. Available at: 10.1080/15568318.2011.654177.

book/book chapter

Methodological developments in activity-travel behavior analysis

Publication Date

January 1, 2012

Author(s)

Suggested Citation
David Brownstone (2012) “Methodological developments in activity-travel behavior analysis”, in C.R.B. R. M. Pendayala (ed.) Travel behavior research in an evolving world. International Association for Travel Behavior Research, pp. 249–260.

published journal article

In memoriam frank a. Haight 1919-2006

TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT

Publication Date

January 1, 2006

Author(s)

Thomas Golob, Molly I. Haight
Suggested Citation
Thomas F. Golob and Molly I. Haight (2006) “In memoriam frank a. Haight 1919-2006”, TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 11(5), pp. 386–388. Available at: 10.1016/j.trd.2006.06.007.

published journal article

Enhancing the universality and transferability of freeway incident detection using a Bayesian-based neural network

Transportation Research Part C: Emerging Technologies

Publication Date

October 1, 1999
Suggested Citation
Baher Abdulhai and Stephen G. Ritchie (1999) “Enhancing the universality and transferability of freeway incident detection using a Bayesian-based neural network”, Transportation Research Part C: Emerging Technologies, 7(5), pp. 261–280. Available at: 10.1016/s0968-090x(99)00022-4.

published journal article

Flexing service schedules: Assessing the potential for demand-adaptive hybrid transit via a stated preference approach

Transportation Research Part C: Emerging Technologies

Publication Date

March 1, 2017

Author(s)

Charlotte Frei, Michael Hyland, Hani Mahmassani
Suggested Citation
Charlotte Frei, Michael Hyland and Hani S. Mahmassani (2017) “Flexing service schedules: Assessing the potential for demand-adaptive hybrid transit via a stated preference approach”, Transportation Research Part C: Emerging Technologies, 76, pp. 71–89. Available at: 10.1016/j.trc.2016.12.017.

published journal article

Vehicular ad hoc networks: Storms on the horizon

Access

Publication Date

October 1, 2013

Author(s)

Abstract

Vehicular ad hoc networks (VANETs) offer a promising way to prevent accidents, facilitate eco-friendly driving, and provide more accurate real-time traffic information. This article describes the three different communication pathways incorporated by VANETs and briefly outlines potential applications. While there are still communication problems to solve within these complex systems, concerns about privacy, liability, and security are the chief obstacles that prevent progress towards large-scale implementation.

Suggested Citation
Amelia Regan (2013) “Vehicular ad hoc networks: Storms on the horizon”, Access, (43), pp. pp. 35–37. Available at: https://escholarship.org/uc/item/48h1r6wd.

conference paper

Development of methods and tools for managing traffic congestion in freeway corridors

2006 IEEE intelligent transportation systems conference

Publication Date

September 1, 2006

Abstract

In this paper we present some of our research findings derived from a series of research activities funded by the California PATH program to commemorate the occasion of the establishment of the PATH program 20 years ago. The major theme woven by these research efforts is the development of more effective traffic management tools that help tame unbridled traffic congestion in California, and the major contributions include a better understanding of traveler behavior, improved methods for obtaining origin-destination demand matrices, and increased modeling and control capabilities

Suggested Citation
W. Recker, H.M. Zhang, Lianyu Chu, A. Chen and M. McNally (2006) “Development of methods and tools for managing traffic congestion in freeway corridors”, in 2006 IEEE intelligent transportation systems conference, pp. 30–37. Available at: 10.1109/ITSC.2006.1706714.