GeoVisual analytics for understanding the distribution of speeding patterns on arterial roads: assessing the traffic safety of vulnerable road users

Irma Kveladze*, Niels Agerholm

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

1 Citation (Scopus)

Abstract

Arterial roads have operational significance and play a substantial role in the mobility of modern society. They make up the majority of road network in urban and rural areas and allow high-speed movement despite traffic-controlling elements. In densely populated areas where the presence of Vulnerable Road Users (VRUs) is high, high-speed movement is problematic, and speed calming measures are needed to improve traffic safety, since many VRUs do crossroads, regardless of the road network regulations. These aspects have been researched in the traffic domain in a small scale, and not much has been investigated from a visualisation perspective. To provide comprehensive insights on the movement characteristics of arterial roads, we propose a GeoVisual Analytics (GVA) approach. GVA techniques are suitable solutions to display and extract knowledge from large amounts of Floating Car Data (FCD) collected through on-board devices of vehicles. By cross-sector collaboration between cartographic and traffic experts, five arterial road segments in Aalborg City were selected to answer where and when in particular VRUs do cross streets by ignoring traffic rules. Based on clusters of large unexplainable deviations from driving speed in FCD, the results uncovered meaningful patterns from complex traffic movements. They also allowed for the provision of some recommendations that are critical for traffic safety in urban areas.

Original languageEnglish
JournalJournal of Location Based Services
Volume14
Issue number3
Pages (from-to)201-230
Number of pages30
ISSN1748-9725
DOIs
Publication statusPublished - 2 Jul 2020

Bibliographical note

Publisher Copyright:
© 2020 Informa UK Limited, trading as Taylor & Francis Group.

Keywords

  • arterial roads
  • floating car data
  • Geo visual analytics
  • traffic safety

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