Publication detail

STOCHASTIC TRAFFIC DEMAND PROFILE: INTERDAY VARIATION FOR GIVEN TIME AND DAY OF WEEK

MIKOLÁŠEK, I.

Original Title

STOCHASTIC TRAFFIC DEMAND PROFILE: INTERDAY VARIATION FOR GIVEN TIME AND DAY OF WEEK

Type

journal article in Web of Science

Language

English

Original Abstract

Traffic demand prediction is one of the major elements of traffic planning and modelling. Traffic surveys routinely estimate the profile of traffic demand on a certain road section, showing the expected evolution of the demand over a day or week. However, the actual demand fluctuates around this value on day-to-day basis and thus can exceed otherwise sufficient capacity and consequently cause congestion due to the capacity drop. This type of traffic demand variability has not yet been properly studied although it can play significant role in traffic modelling and engineering. The relevance of this variability is further increasing with the growing popularity of stochastic traffic models. This paper presents results of a statistical analysis of the demand variability in five-minute aggregation intervals. Normal, lognormal and gamma distributions all show reasonably well fit to the data for individual intervals and often do not differ on statistically significant level. Based on the count of the best fits, the lognormal distribution seems to be most suitable, while the gamma distribution is the most universal and with generally acceptable fit. There appears to be a pattern where certain distributions have better fit in different times of the day and week. The regularity and magnitude of demand probably both play a role in this, as well as the aggregation interval. Two simple models for modelling the variability are proposed for practical applications when there is not enough data to perform similar analysis.

Keywords

Random traffic demand; Probability distribution; Traffic model; Goodness-of-fit

Authors

MIKOLÁŠEK, I.

Released

31. 12. 2022

Publisher

CZECH TECHNICAL UNIV PRAGUE, FAC CIVIL ENGINEERING

Location

PRAGUE 6

ISBN

1805-2576

Periodical

The Civil Engineering Journal

Year of study

31

Number

4

State

Czech Republic

Pages from

636

Pages to

646

Pages count

11

URL

https://www.vut.cz/uk/podpora-publikovani/identifikatory/orcid/registrace

BibTex

@article{BUT182405,
  author="Igor {Mikolášek}",
  title="STOCHASTIC TRAFFIC DEMAND PROFILE: INTERDAY VARIATION FOR GIVEN TIME AND DAY OF WEEK",
  journal="The Civil Engineering Journal",
  year="2022",
  volume="31",
  number="4",
  pages="636--646",
  doi="10.14311/CEJ.2022.04.0048",
  issn="1805-2576",
  url="https://www.vut.cz/uk/podpora-publikovani/identifikatory/orcid/registrace"
}