Tracking the evolution of congestion in dynamic urban road networks

Tarique Anwar, Chengfei Liu, Hai L. Vu, Md. Saiful Islam

Research output: Chapter in Book/Report/Conference proceedingConference PaperOtherpeer-review

7 Citations (Scopus)

Abstract

The congestion scenario on a road network is often represented by a set of differently congested partitions having homogeneous level of congestion inside. Due to the changing traffic, these partitions evolve with time. In this paper, we propose a two-layer method to incrementally update the differently congested partitions from those at the previous time point in an efficient manner, and thus track their evolution. The physical layer performs low-level computations to incrementally update a set of small-sized road network building blocks, and the logical layer provides an interface to query the physical layer about the congested partitions. At each time point, the unstable road segments are identified and moved to their most suitable building blocks. Our experimental results on different datasets show that the proposed method is much efficient than the existing re-partitioning methods without significant sacrifice in accuracy
Original languageEnglish
Title of host publicationProceedings of the 25th ACM International on Conference on Information and Knowledge Management
EditorsSnehasis Mukhopadhyay, ChengXiang Zhai
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages2323-2328
Number of pages6
ISBN (Print)9781450340731
DOIs
Publication statusPublished - 24 Oct 2016
Externally publishedYes
EventACM International Conference on Information and Knowledge Management 2010 - Toronto, Canada
Duration: 26 Oct 201030 Oct 2010
Conference number: 19th
https://dl.acm.org/doi/proceedings/10.1145/1871437

Conference

ConferenceACM International Conference on Information and Knowledge Management 2010
Abbreviated titleCIKM 2010
CountryCanada
CityToronto
Period26/10/1030/10/10
Internet address

Keywords

  • Road network motif
  • Incremental partitioning
  • Tracking congestion evolution
  • Urban road networks

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