On a clustering-based approach for traffic sub-area division

Jiahui Zhu, Xinzheng Niu, Chase Q. Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Traffic sub-area division is an important problem in traffic management and control. This paper proposes a clustering-based approach to this problem that takes into account both temporal and spatial information of vehicle trajectories. Considering different orders of magnitude in time and space, we employ a z-score scheme for uniformity and design an improved density peak clustering method based on a new density definition and similarity measure to extract hot regions. We design a distribution-based partitioning method that employs k-means algorithm to split hot regions into a set of traffic sub-areas. For performance evaluation, we develop a traffic sub-area division criterium based on the SDbw indicator and the classical Davies-Bouldin index in the literature. Experimental results illustrate that the proposed approach improves traffic sub-area division quality over existing methods.

Original languageEnglish (US)
Title of host publicationAdvances and Trends in Artificial Intelligence. From Theory to Practice - 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Proceedings
EditorsFranz Wotawa, Ingo Pill, Roxane Koitz-Hristov, Gerhard Friedrich, Moonis Ali
PublisherSpringer Verlag
Pages516-529
Number of pages14
ISBN (Print)9783030229986
DOIs
StatePublished - 2019
Event32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019 - Graz, Austria
Duration: Jul 9 2019Jul 11 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11606 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019
CountryAustria
CityGraz
Period7/9/197/11/19

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Keywords

  • Clustering
  • Density
  • Hot region
  • Traffic sub-area
  • Vehicle trajectory

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