Statistical model of traffic flow at an unsignalized intersection and its use for capacity estimation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F24%3A00379559" target="_blank" >RIV/68407700:21340/24:00379559 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Statistical model of traffic flow at an unsignalized intersection and its use for capacity estimation

Popis výsledku v původním jazyce

We present a probabilistic model of traffic flow at an uncontrolled intersection of the T-type and its possible use for evaluation of intersection capacity. The statistical method used is based on the generally accepted practice formulated by Werner Siegloch (1973), in which an estimation of capacity is influenced by the so-called gap acceptance rule, when the driver of a minor road vehicle accepts/rejects a gap (time clearance) between two successive main-road vehicles for his/her inclusion maneuver. In this contribution, such a stochastic scheme is reformatted strictly into a language of random variables. This makes it possible to validate/reject older approaches by which various authors have estimated the probabilities for gap acceptance and other related statistical characteristics, including a capacity itself. The performed analysis convincingly shows that some traditional regression techniques used in practical applications of the Siegloch’s method can fatally fail. Instead, the authors propose a verified methodology based on the application of modern regression methods. The contribution of the new methodology lies in a fundamental refinement of capacity estimates, which is finally demonstrated by applying it to recent empirical data sets.

Název v anglickém jazyce

Statistical model of traffic flow at an unsignalized intersection and its use for capacity estimation

Popis výsledku anglicky

We present a probabilistic model of traffic flow at an uncontrolled intersection of the T-type and its possible use for evaluation of intersection capacity. The statistical method used is based on the generally accepted practice formulated by Werner Siegloch (1973), in which an estimation of capacity is influenced by the so-called gap acceptance rule, when the driver of a minor road vehicle accepts/rejects a gap (time clearance) between two successive main-road vehicles for his/her inclusion maneuver. In this contribution, such a stochastic scheme is reformatted strictly into a language of random variables. This makes it possible to validate/reject older approaches by which various authors have estimated the probabilities for gap acceptance and other related statistical characteristics, including a capacity itself. The performed analysis convincingly shows that some traditional regression techniques used in practical applications of the Siegloch’s method can fatally fail. Instead, the authors propose a verified methodology based on the application of modern regression methods. The contribution of the new methodology lies in a fundamental refinement of capacity estimates, which is finally demonstrated by applying it to recent empirical data sets.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

10103 - Statistics and probability

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

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