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We introduce microscopic and macroscopic stochastic traffic models including traffic accidents. The microscopic model is based on a Follow-the-Leader approach whereas the macroscopic model is described by a scalar conservation law with…

Probability · Mathematics 2021-11-19 Simone Göttlich , Thomas Schillinger

A discrete model of traffic on a multilane road is considered. The traffic is presented as particles movement with a deterministic component and a stochastic one. Formulas for the traffic characteristics have been found. The model can…

Physics and Society · Physics 2007-05-23 A. P. Buslaev , V. M. Prikhodko , A. G. Tatashev , M. V. Yashina

The present paper proposes a stochastic model of the traffic flow. This model has a discrete set of states and the continuous time. The model is a generalization of the discrete stochastis model that has been considered in a previous paper…

Other Condensed Matter · Physics 2007-05-23 A. P. Buslaev , A. G. Tatashev , M. V. Yashina

In this paper, we investigate a nonlocal traffic flow model based on a scalar conservation law, where a stochastic velocity function is assumed. In addition to the modeling, theoretical properties of the stochastic nonlocal model are…

Numerical Analysis · Mathematics 2024-07-04 Timo Böhme , Simone Göttlich , Andreas Neuenkirch

A new vehicular traffic flow model based on a stochastic jump process in vehicle acceleration and braking is introduced. It is based on a master equation for the single car probability density in space, velocity and acceleration with an…

Other Condensed Matter · Physics 2009-11-10 K. Thomas Waldeer

We introduce a counting process to model the random occurrence in time of car traffic accidents, taking into account some aspects of the self-excitation typical of this phenomenon. By combining methods from probability and differential…

Physics and Society · Physics 2025-05-19 Simone Göttlich , Thomas Schillinger , Andrea Tosin

This paper is concerned with a fluidodynamic model for traffic flow. More precisely, we consider a single conservation law, deduced from conservation of the number of cars, defined on a road network that is a collection of roads with…

Analysis of PDEs · Mathematics 2007-05-23 G. M. Coclite , B. Piccoli

Macroscopic traffic flow is stochastic, but the physics-informed deep learning methods currently used in transportation literature embed deterministic PDEs and produce point-valued outputs; the stochasticity of the governing dynamics plays…

Systems and Control · Electrical Eng. & Systems 2026-03-11 Wuping Xin

The aim of this work is to introduce a two-dimensional macroscopic traffic model for multiple populations of vehicles. Starting from the paper [20], where a two-dimensional model for a single class of vehicles is proposed, we extend the…

Numerical Analysis · Mathematics 2020-11-04 Caterina Balzotti , Simone Göttlich

We investigate piecewise deterministic Markov processes (PDMP), where the deterministic dynamics follows a scalar conservation law and random jumps in the system are characterized by changes in the flux function. We show under which…

Probability · Mathematics 2019-01-30 Stephan Knapp

This paper presents a mesoscopic traffic flow model that explicitly describes the spatio-temporal evolution of the probability distributions of vehicle trajectories. The dynamics are represented by a sequence of factor graphs, which enable…

Machine Learning · Statistics 2019-09-25 Saif Eddin Jabari , Deepthi Mary Dilip , DianChao Lin , Bilal Thonnam Thodi

The goal of the paper is a rigorous derivation of a macroscopic traffic flow model with a bifurcation or a local perturbation from a microscopic one. The microscopic model is a simple follow-the-leader with random parameters. The random…

Analysis of PDEs · Mathematics 2021-11-16 P Cardaliaguet , N Forcadel

This paper studies a stochastic model that describes the evolution of vehicle densities in a road network. It is consistent with the class of (deterministic) kinematic wave models, which describe traffic flows on the basis of conservation…

Probability · Mathematics 2021-02-11 Michel Mandjes , Jaap Storm

We develop a discrete Boltzmann-type model that uses dynamics in phase space to describe the behavior of traffic flows. Firstly, we model the traffic flow at mesoscopic scale using dynamics in phase space, which is considered as an…

Cellular Automata and Lattice Gases · Physics 2023-11-27 Zhizhen Zhang , Changhong Lu

We derive a conservation law on a network made of two incoming branches and a single outgoing one from a discrete traffic flow model. The continuous model is obtained from the discrete one by letting the number of vehicles tend to infinity…

Analysis of PDEs · Mathematics 2024-09-04 P Cardaliaguet

We consider here probabilistic models of transportation flows. The main goal of this introduction is rather not to present various techniques for problem solving but to present some intuition to invent adequate and natural models having…

Probability · Mathematics 2011-10-24 V. A. Malyshev , A. A. Zamyatin

In this work, we propose an alternative stochastic model for the fundamental diagram of traffic flow with minimal number of parameters. Our approach is based on a mesoscopic viewpoint of the traffic system in terms of the dynamics of…

Physics and Society · Physics 2016-02-23 Adriano Francisco Siqueira , Carlos Jose Todero Peixoto , Chen Wu , Wei-Liang Qian

Traffic flow is a very prominent example of a driven non-equilibrium system. A characteristic phenomenon of traffic dynamics is the spontaneous and abrupt drop of the average velocity on a stretch of road leading to congestion. Such a…

Physics and Society · Physics 2012-10-29 Florian Knorr , Michael Schreckenberg

Traffic control is at the core of research in transportation engineering because it is one of the best practices for reducing traffic congestion. It has been shown in recent years that the traffic control problem involving…

Optimization and Control · Mathematics 2021-05-10 Hao Liu , Christian Claudel , Randy Machemehl

We have studied the distribution of traffic flow $q$ for the Nagel-Schreckenberg model by computer simulations. We applied a large-deviation approach, which allowed us to obtain the distribution $P(q)$ over more than one hundred decades in…

Data Analysis, Statistics and Probability · Physics 2019-12-11 Wiebke Staffeldt , Alexander K. Hartmann
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