First order multi-lane traffic flow model – an incentive based macroscopic model to represent lane change dynamics

Hari Nagalur Subraveti, Victor Knoop, Bart van Arem

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)
41 Downloads (Pure)

Abstract

Unbalanced lane usage on motorways might lead to the reduction in capacity
of the motorway. Lane-level traffic management present new opportunities
to balance the lane-flow distribution and help reduce congestion.
In order to come up with efficient traffic management strategies on a
lane-level, there is a need for accurate lane-specific traffic state estimation
models. This paper presents a first-order lane-level traffic flow model. The
proposed model differs from the existing models in the following areas: (i)
incentive-based motivation for lane changes and consideration of downstream
conditions (ii) transfer of lateral flows among cells. The model is
tested against real-world data. It is observed that the model is able to capture
the lane-level dynamics in terms of the lane flow distribution. The
model results are compared to a linear regression model and results show
that the developed model performs better than the regression model on
the test sections.
Original languageEnglish
Pages (from-to)1758-1779
Number of pages22
JournalTransportmetrica B: Transport Dynamics
Volume7
Issue number1
DOIs
Publication statusPublished - 2019

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • cell transmission model
  • incentives
  • lane flow distribution
  • Lane-level
  • macroscopic traffic flow model

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