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Novel Trip Agglomeration Methods for Efficient Extraction of Urban Mobility Patterns

Author

Listed:
  • Praveen Kumar

    (Indian Institute of Technology Kanpur)

  • Partha Chakroborty

    (Indian Institute of Technology Kanpur)

  • Hemant Gehlot

    (Indian Institute of Technology Kanpur)

Abstract

Mobility patterns in an urban area can be defined as the trip making behavior of an urban population. Traditionally, the origin-destination matrix representation of travel demand, where trip ends are agglomerated toward zone centroids that are decided a priori, has historically been used to identify trip making behavior. In this paper, different agglomeration methods are explored to extract the trip making behavior and their performances are analyzed. First, a variant of the zone-based agglomeration method is proposed, in which zones are optimally located rather than having their locations determined beforehand. Then a trip-based agglomeration method is proposed, where each trip is represented as an ordered pair of origin and destination in the form of a line segment and agglomeration of these line segments is performed. The proposed line-based agglomeration method serves a two-fold purpose, (a) the proposed trip-based agglomeration method helps in identifying the corridors carrying the majority of the flow in a single step, as opposed to trip-end based agglomeration methods where several post-processing steps may be required to identify the corridors, and (b) this method performs better than the existing trip-end based agglomeration methods in terms of the number of corridors that are required to cover the given trips. Efficient algorithms are also developed to solve the proposed trip-based agglomeration method, their performance on real-world trip datasets is tested and finally, the properties of the proposed algorithms are explored.

Suggested Citation

  • Praveen Kumar & Partha Chakroborty & Hemant Gehlot, 2024. "Novel Trip Agglomeration Methods for Efficient Extraction of Urban Mobility Patterns," Networks and Spatial Economics, Springer, vol. 24(4), pages 897-926, December.
    • Handle: RePEc:kap:netspa:v:24:y:2024:i:4:d:10.1007_s11067-024-09641-3
    DOI: 10.1007/s11067-024-09641-3
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    References listed on IDEAS

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