Modeling

Multi-stage Models for Dynamic Ride-Sharing in Taxi Services and Congestion Analysis

Quadrifoglio, Luca
Zhang, Cheng
Sun, Min-Ci
Maria Laura Delle Monache
Yeo, Yuneil
2024

This research introduces practical optimization model for implementing ride-sharing in taxi services and studies the effects of ride-sharing on the congestion status through the case study of Chicago. Ride-sharing combines trips into one ride-shared trip with the objective of maximizing the total mileage saving. This research proposes a multi-stage model to optimize rider matches, aiming to reduce the total travel distance and enhance the matching of multiple riders. To validate the effectiveness of the model, real taxi data from Chicago is used, demonstrating significant improvements in...

On the Analytical Properties of a Nonlinear Microscopic Dynamical Model for Connected and Automated Vehicles

Matin, Hossein Nick Zinat
Yeo, Yuneil
Gong, Xiaoqian
Maria Laura Delle Monache
2024

In this letter, we propose an integrated dynamical model of Connected and Automated Vehicles (CAVs) which incorporates CAV technologies and a microscopic car-following model to improve safety, efficiency, and convenience. We rigorously investigate the analytical properties such as well-posedness, maximum principle, perturbation, and stability of the proposed model in some proper functional spaces. Furthermore, we prove that the model is collision-free and derive an explicit lower bound on the distance as a safety measure.

Macroscopic Modelling and Control of Heavy-Duty Electric Road Systems

Čičić, Mladen
Maria Laura Delle Monache
2024

Electric road systems (ERS), where power is delivered to the vehicles as they drive, are an intriguing option for road freight sector electrification. In order to analyse various aspects of their operation, such as their economical feasibility, or their influence on the power system, appropriate modelling approaches are needed. While microscopic, agent-based models have successfully been used for this purpose, their complexity makes them unsuitable for control design and implementation. In this work, we propose a macroscopic model, capturing the interaction between the ERS and Heavy-Duty...

Generic Multi-class Cell Transmission Model for Traffic Control

Čičić, Mladen
Siri, Enrico
Maria Laura Delle Monache
2024

Recent years have witnessed renewed interest in multi-class traffic models, inspired in no small part by the impending arrival of Connected and Autonomous Vehicles, whose behaviour is likely to differ from that of Human-Driven Vehicles. Although numerous multi-class traffic models have been proposed, consistent overarching theory is lacking. In this paper, we propose a generic first-order multi-class traffic modelling framework, intended to be sufficiently versatile to represent most of the traffic phenomena relevant to freeway control applications. Based on this framework, we are able to...

A Tutorial on Neural Network-Based Solvers for Hyperbolic Conservation Laws: Supervised vs. Unsupervised Learning, and Applications to Traffic Modeling

Canesse, Alexi
Fu, Zhe
Lichtle, Nathan
Matin, Hossein Nick Zinat
Liu, Zhe
Maria Laura Delle Monache
Alexandre Bayen
2025

Neural networks (NNs) are powerful tools for solving complex partial differential equations (PDEs) with high accuracy. However, many NN-based solvers are designed as general-purpose models or lack theoretical grounding, limiting their ability to capture essential solution properties such as regularity, conservation, and entropy conditions. This issue is especially critical for hyperbolic conservation laws, which govern wave propagation and shock formation, and are among the most challenging PDEs to solve accurately. This tutorial examines both supervised and unsupervised NN-based solvers...

A Nonlocal Degenerate Macroscopic Model of Traffic Dynamics with Saturated Diffusion: Modeling and Calibration Theory

Do, Dawson
Matin, Hossein Nick Zinat
Miti, Masuma Mollika
Maria Laura Delle Monache
2025

In this work, we introduce a novel first-order nonlocal partial differential equation with saturated diffusion to describe the macroscopic behavior of traffic dynamics. We show how the proposed model is better in comparison with existing models in explaining the underlying driver behavior in real traffic data. In doing so, we introduce a methodology for adjusting the parameters of the proposed PDE with respect to the distribution of real datasets. In particular, we conceptually and analytically elaborate on how such calibration connects the solution of the PDE to the probability transition...

Modeling, Monitoring, and Controlling Road Traffic Using Vehicles to Sense and Act

Maria Laura Delle Monache
McQuade, Sean T.
Matin, Hossein Nick Zinat
Gloudemans, Derek A.
Wang, Yanbing
Gunter, George L.
Alexandre Bayen
Lee, Jonathan W.
Piccoli, Benedetto
Seibold, Benjamin
Sprinkle, Jonathan M.
Work, Daniel B.
2025

This review offers a comprehensive overview of current traffic modeling, estimation, and control methods, along with resulting field experiments. It highlights key developments and future directions in leveraging technological advancements to improve traffic management and safety. The focus is on macroscopic, microscopic, and micro-macro models, as well as state-of-the-art control techniques and estimation methods for deploying vehicles in traffic field experiments.

A Methodology for the Integration of Vehicle Failure Diagnostics

Raja Sengupta
Lindsey, Antonia E.
1998

The paper presents a model-based method for the design of diagnostics for a large-scale system. The method is demonstrated by application to the diagnostic design for the longitudinal control system of a fully automated vehicle capable of platooned operation. It is assumed that the system is modelled by continuous and discrete event models (DEM's). We comment on the abstraction of continuous models into discrete event models and show how DEM's may be constructed in a modular manner for a given set of sensors, observers and controllers defined in the continuous domain. The method is modular...

Estimating ATIS Benefits for the Smart Corridor

Raja Sengupta
Hongola, Bruce
1998

This report studies the effects of Advanced Traveler Information Systems (ATIS) on traffic congestion in the Smart Corridor of the Santa Monica Freeway. Simulation modeling is used to estimate the potential travel time savings to divert traffic from the Smart Corridor to arterial roads when incidents occur. The study attempts to establish relationships between traffic management variables, such as incident detection time, incident duration, capacity reduction, percentage of traffic diversion, and duration of traffic diversion.

Numerical Simulation and Spectral Analysis of Pressure Fluctuations in Vehicle Aerodynamic Noise Generation

Duncan, Bradley D.
Raja Sengupta
Mallick, Swapan
Shock, Rick
Sims-Williams, D. B.
2002

A new approach is proposed and demonstrated for investigation of the spatial structure of fluctuations in unsteady aerodynamics results obtained using CFD. This approach is used in this study to isolate unsteadiness in the flow field due to coherent structures at relatively high frequency from the dominant organized motion, as well as from the computational noise, in unsteady data obtained from CFD simulations. These simulations are performed using the commercial CFD software, PowerFLOW, which employs a Lattice Boltzmann method and a very large-eddy simulation (VLES) model for small-scale...