STATISTICAL ANALYSIS OF DAY-TO-DAY VARIATIONS IN REAL-TIME TRAFFIC FLOW DATA

In the absence of intelligent vehicle-highway system technologies, commuters tend to select their routes through a congested network primarily on the basis of expected average link travel times. For this average to be representative of the current day, it is essential that the traffic conditions be relatively similar each day. However, if the traffic conditions vary considerably from one day to the next, the historical information will be insufficient for commuters to find the optimum routes through the network, and the provision of real-time traffic information could provide major benefits. Furthermore, simulation is becoming an important tool in evaluating different traffic control strategies. As a result it has become more and more important not only that the average typical traffic conditions be established but also that the upper and lower bounds of these average conditions be estimated. Consequently, two related issues are examined: the spatial and temporal magnitude of the variability in traffic conditions during typical nonincident conditions, and the magnitude of this variability during incident conditions. It was shown that in the absence of incidents, the temporal and spatial variations in traffic conditions were very similar for weekdays but varied considerably relative to the typical conditions during weekends. Major incidents, however, were found to alter drastically the average recurring conditions, thus creating a window of opportunity for achieving travel benefits by using dynamic data in real time.

• Record URL:
  http://onlinepubs.trb.org/Onlinepubs/trr/1995/1510/1510-004.pdf
• Record URL:
  https://scholar.google.com/scholar_lookup?title=STATISTICAL+ANALYSIS+OF+DAY-TO-DAY+VARIATIONS+IN+REAL-TIME+TRAFFIC+FLOW+DATA&author=H.+Rakha&author=M.+Van+Aerde&publication_year=1995
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• Supplemental Notes:
  • This paper appears in Transportation Research Record No. 1510, Traffic Flow Theory and Characteristics with Applications for Intelligent Transportation System Technologies. Distribution, posting, or copying of this PDF is strictly prohibited without written permission of the Transportation Research Board of the National Academy of Sciences. Unless otherwise indicated, all materials in this PDF are copyrighted by the National Academy of Sciences. Copyright © National Academy of Sciences. All rights reserved
• Authors:
  • Rakha, H
  • Van Aerde, M
• Publication Date: 1995

Language

• English

Media Info

• Features: Figures; References; Tables;
• Pagination: p. 26-34
• Monograph Title: Traffic flow theory and characteristics with applications for intelligent transportation system technologies
• Serial:
  • Transportation Research Record
  • Issue Number: 1510
  • Publisher: Transportation Research Board
  • ISSN: 0361-1981

Subject/Index Terms

• TRT Terms: Real time control; Real time data processing; Statistical analysis; Traffic flow; Traffic incidents; Variables; Weekdays; Weekends
• Uncontrolled Terms: Data; Incidents
• Old TRIS Terms: Variations
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I71: Traffic Theory;

Filing Info

• Accession Number: 00715622
• Record Type: Publication
• ISBN: 0309062039
• Files: TRIS, TRB
• Created Date: Jan 19 1996 12:00AM