Analysis of road performance and traffic demand variations by the seasons

Jinyoung Kim, Fumitaka Kurauchi, Nobuhiro Uno

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

1 Citation (Scopus)

Abstract

This paper investigates variations of road performance and traffic demand by the seasons on urban expressway. Authors have been analysing the influence of several external factors such as time of a day, day of a week, weather and commercial custom onto fluctuations of road performance and traffic demand in the former study (1). And it was concluded that all the factors except commercial custom have a big influence onto the performance and demand. The season is considered as a new external factor in this study. Travel time obtained by automatic license plate detector is used for grasping the road performance and its variation. The path flows estimated by a dynamic path flow estimation model are used as a traffic demand. For clarifying the reason of the road performance degradation, the relationship between the performance and the demand is analysed utilising cluster analysis. It is found that the season is one of the most important external factors on the variations of performance and demand.

Original languageEnglish
Title of host publication15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008
Pages959-970
Number of pages12
Publication statusPublished - 2008 Dec 1
Event15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008 - New York, NY, United States
Duration: 2008 Nov 162008 Nov 20

Publication series

Name15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008
Volume2

Other

Other15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008
Country/TerritoryUnited States
CityNew York, NY
Period08/11/1608/11/20

Keywords

  • Dynamic path flow estimation
  • Road performance variation
  • Traffic demand variation

ASJC Scopus subject areas

  • Mechanical Engineering
  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Transportation
  • Automotive Engineering
  • Computer Networks and Communications
  • Artificial Intelligence
  • Computer Science Applications

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