Urban travel time reliability at different traffic conditions

Fangfang Zheng, Jie Li, H.J. van Zuylen, Xiaobo Liu, Hongtai Yang

Research output: Contribution to journalArticleScientificpeer-review

15 Citations (Scopus)
29 Downloads (Pure)

Abstract

The decision making of travelers for route choice and departure time choice depends on the expected travel time and its reliability. A common understanding of reliability is that it is related to several statistical properties of the travel time distribution, especially to the standard deviation of the travel time and also to the skewness. For an important corridor in Changsha (P.R. China) the travel time reliability has been evaluated and a linear model is proposed for the relationship between travel time, standard deviation, skewness, and some other traffic characteristics. Statistical analysis is done for both simulation data from a delay distribution model and for real life data from automated number plate recognition (ANPR) cameras. ANPR data give unbiased travel time data, which is more representative than probe vehicles. The relationship between the mean travel time and its standard deviation is verified with an analytical model for travel time distributions as well as with the ANPR travel times. Average travel time and the standard deviation are linearly correlated for single links as well as corridors. Other influence factors are related to skewness and travel time standard deviations, such as vehicle density and degree of saturation. Skewness appears to be less well to explain from traffic characteristics than the standard deviation is.

Original languageEnglish
Pages (from-to)106-120
Number of pages15
JournalJournal of Intelligent Transportation Systems: technology, planning, and operations
Volume22 (1028)
Issue number2
DOIs
Publication statusPublished - 23 Dec 2017

Keywords

  • automated number plate recognition
  • skewness
  • travel time reliability
  • travel time standard deviation
  • urban traffic

Fingerprint

Dive into the research topics of 'Urban travel time reliability at different traffic conditions'. Together they form a unique fingerprint.

Cite this