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Promet - Traffic&Transportation journal

Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

PUBLISHED
31.08.2015
LICENSE
Copyright (c) 2024 Çağlar Koşun, Hüseyin Murat Çelik, Serhan Özdemir

An Analysis of Vehicular Traffic Flow Using Langevin Equation

Authors:

Çağlar Koşun
IZMIR INSTITUTE OF TECHNOLOGY

Hüseyin Murat Çelik
ISTANBUL TECHNICAL UNIVERSITY

Serhan Özdemir
IZMIR INSTITUTE OF TECHNOLOGY

Keywords:Langevin equation, traffic dynamics, Brownian motion, traffic regimes, traffic flow, stochastic forces, drift, diffusion,

Abstract

Traffic flow data are stochastic in nature, and an abundance of literature exists thereof. One way to express stochastic data is the Langevin equation. Langevin equation consists of two parts. The first part is known as the deterministic drift term, the other as the stochastic diffusion term. Langevin equation does not only help derive the deterministic and random terms of the selected portion of the city of Istanbul traffic empirically, but also sheds light on the underlying dynamics of the flow. Drift diagrams have shown that slow lane tends to get congested faster when vehicle speeds attain a value of 25 km/h, and it is 20 km/h for the fast lane. Three or four distinct regimes may be discriminated again from the drift diagrams; congested, intermediate, and free-flow regimes. At places, even the intermediate regime may be divided in two, often with readiness to congestion. This has revealed the fact that for the selected portion of the highway, there are two main states of flow, namely, congestion and free-flow, with an intermediate state where the noise-driven traffic flow forces the flow into either of the distinct regimes.

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How to Cite
Koşun, Ç. (et al.) 2015. An Analysis of Vehicular Traffic Flow Using Langevin Equation. Traffic&Transportation Journal. 27, 4 (Aug. 2015), 317-324. DOI: https://doi.org/10.7307/ptt.v27i4.1613.

SPECIAL ISSUE IS OUT

Guest Editor: Eleonora Papadimitriou, PhD

Editors: Marko Matulin, PhD, Dario Babić, PhD, Marko Ševrović, PhD


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