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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F22%3APU147355" target="_blank" >RIV/00216305:26110/22:PU147355 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.vut.cz/uk/podpora-publikovani/identifikatory/orcid/registrace" target="_blank" >https://www.vut.cz/uk/podpora-publikovani/identifikatory/orcid/registrace</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.14311/CEJ.2022.04.0048" target="_blank" >10.14311/CEJ.2022.04.0048</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20100 - Civil engineering

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

The Civil Engineering Journal

ISSN

1805-2576

e-ISSN

—

Svazek periodika

31

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

11

Strana od-do

636-646

Kód UT WoS článku

000907791700010

EID výsledku v databázi Scopus

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