Modeling

Three-Stream Model for Arterial Traffic

Bails, Constant
Hofleitner, Aude
Xuan, Yiguang
Bayen, Alexandre M.
2012

In this article, a new analytical traffic flow model is proposed for traffic dynamics at signalized intersections. During each cycle, both the arrival and the departure traffic are approximated by three distinct traffic streams with uniform density. Because of the similar representation of the arrival and the departure traffic, results from a single intersection can easily be extended to a series of intersections. With this model, the number of parameters of the model is tractable, leading to analytical solutions of the problem. It also is proved that the total delay of one-way...

Large-Scale Estimation of Arterial Traffic and Structural Analysis of Traffic Patterns from Probe Vehicles

Hofleitner, Aude
Herring, Ryan
Bayen, Alexandre
Han, Yufei
2012

Estimating and analyzing traffic conditions on large arterial networks is an inherently difficult task. The first goal of this article is to demonstrate how arterial traffic conditions can be estimated using sparsely sampled GPS probe vehicle data provided by a small percentage of vehicles. Traffic signals, stop signs, and other flow inhibitors make estimating arterial traffic conditions significantly more difficult than estimating highway traffic conditions. To address these challenges, a statistical modeling framework is proposed that leverages a large historical database and...

State Estimation in Large-Scale Open Channel Networks Using Particle Filters

Rafiee, Mohammad
Barrau, Axel
Bayen, Alexandre
2012

We consider the problem of estimating flow state in real time in large-scale open channel networks. After constructing a state space model of the flow based on the Saint-Venant equations, we implement the optimal sequential importance resampling (SIR) filter to perform state estimation using some additional flow measurements. The estimation method is implemented using a model of a network of 19 subchannels and one reservoir, Clifton Court Forebay, in Sacramento-San Joaquin Delta in California and the numerical results are presented.

Phase Transition Model of Non-Stationary Traffic Flow: Definition, Properties and Solution Method

Blandin, Sébastien
Argote, Juan
Bayen, Alexandre M.
2013

We consider the problem of modeling traffic phenomena at a macroscopic level. Increasing availability of streaming probe data allowing the observation of non-stationary traffic motivates the development of models capable of leveraging this information. We propose a phase transition model of non-stationary traffic in conservation form, capable of propagating joint measurements from fixed and mobile sensors, to model complex traffic phenomena such as hysteresis and phantom jams, and to account for forward propagation of information in congested traffic. The model is shown to reduce to the...

Special Issue on Mathematics of Traffic Flow Modeling, Estimation and Control

Bayen, Alexandre M.
Frankowska, Hélène
Lebacque, Jean-Patrick
Piccoli, Benedetto
2013

This Special Issue gathers contributions, most of which were presented atthe Workshop ``Mathematics of Traffic Flow Modeling, Estimation and Control', organized at the Institute for Pure and Applied Mathematicsof the University of California Los Angeles on December 7--9 2011.For more information please click the “Full Text” above.

Calibration Framework based on Bluetooth Sensors for Traffic State Estimation Using a Velocity based Cell Transmission Model

Allström, Andreas
Bayen, Alexandre M.
Fransson, Magnus
Gundlegård, David
Patire, Anthony D.
2014

The velocity based cell transmission model (CTM-v) is a discrete time dynamical model that mimics the evolution of the traffic velocity field on highways. In this paper the CTM-v model is used together with an ensemble Kalman filter (EnKF) for the purpose of velocity sensor data assimilation. We present a calibration framework for the CTM-v and EnKF. The framework consists of two separate phases. The first phase is the calibration of the parameters of the fundamental diagram and the second phase is the calibration of demand and filter parameters. Results from the calibrated model are...

Traffic Modeling and Management: Trends and Perspectives

Bayen, Alexandre M.
Colombo, Rinaldo M.
Goatin, Paola
Piccoli, Benedetto
2014

The present issue of Discrete and Continuous Dynamical Systems -- Series S is devoted to Traffic Modeling and Management. This subject dramatically developed in recent years. On one hand, the successes of the analytical theory of conservationlaws have provided new tools to traffic researchers while, on the otherhand, the requirements coming from the applications have growndramatically. Remarkably, two of the papers that opened the way tothis decades long development date the same year. In 1995 ``The Unique Limit of the Glimm Scheme'' by A. Bressan (Archive forRational Mechanics and...

Information Patterns in the Modeling and Design of Mobility Management Services

Keimer, Alexander
Laurent-Brouty, Nicolas
Farokhi, Farhad
Signargout, Hippolyte
Cvetkovic, Vladimir
Bayen, Alexandre M.
Johansson, Karl H.
2018

The development of sustainable transportation infrastructure for people and goods, using new technology and business models, can prove beneficial or detrimental for mobility, depending on its design and use. The focus of this paper is on the increasing impact new mobility services have on traffic patterns and transportation efficiency in general. Over the last decade, the rise of the mobile internet and the usage of mobile devices have enabled ubiquitous traffic information. With the increased adoption of specific smartphone applications, the number of users of routing applications has...

A Methodology for Evaluating the Performance of Model-Based Traffic Prediction Systems

Gomes, Gabriel
Gan, Qijian
Bayen, Alexandre M.
2018

Model-based traffic prediction systems (mbTPS) are a central component of the decision support and ICM (integrated corridor management) systems currently used in several large urban traffic management centers. These models are intended to generate real-time predictions of the system’s response to candidate operational interventions. They must therefore be kept calibrated and trustworthy. The methodologies currently available for tracking the validity of a mbTPS have been adapted from approaches originally designed for off-line operational planning models. These approaches are insensitive...

Deep Truck : A Deep Neural Network Model for Longitudinal Dynamics of Heavy Duty Trucks

Albeaik, Saleh
Chou, Fang-Chieh
Lu, Xiao-Yun
Bayen, Alexandre M.
2019

This article demonstrates the use of deep neural networks (NN) and deep reinforcement learning (deep-RL) for modeling and control of longitudinal heavy duty truck dynamics. Instead of explicit use of analytical model derived information or parameters about the truck, the deep NN model is fitted to data using a brief set of historical data collected from an arbitrary driving cycle. The deep model is used in this article to design a cruise controller for the truck using model-free deep-RL. The deep model and the control loop performances are demonstrated both using state-of-the-art...