Publications associées à Route assignment

A data fusion approach for ride-sourcing demand estimation: A discrete choice model with sampling and endogeneity corrections

Ride-sourcing services offered by companies like Uber and Didi have grown rapidly in the last decade. Understanding the demand for these services is essential for planning and managing modern transportation systems. Existing studies develop statistical mod ...

2023

Ride-sharing with inflexible drivers in the Paris metropolitan area

Patrick Stefan Adriaan Stokkink

In ride-sharing, commuters with similar itineraries share a vehicle for their trip. Despite its clear benefits in terms of reduced congestion, ride-sharing is not yet widely accepted. We propose a specific ride-sharing variant, where drivers are completely ...

SPRINGER2022

Large-scale traffic signal control and multimodal network design

Dimitrios Tsitsokas

Traffic congestion constitutes one of the most frequent, yet challenging, problems to address in the urban space. Caused by the concentration of population, whose mobility needs surpass the serving capacity of urban networks, congestion cannot be resolved ...

EPFL2022

Optimization and equilibrium problems with discrete choice models

Stefano Bortolomiol

Many transportation markets are characterized by oligopolistic competition. In these markets customers, suppliers and regulators make decisions that are influenced by the preferences and the decisions of all other agents. In particular, capturing and under ...

EPFL2022

Dedicated bus lane network design under demand diversion and dynamic traffic congestion: An aggregated network and continuous approximation model approach

Nikolaos Geroliminis, Mehmet Yildirimoglu

This paper proposes an integrated methodological framework to design a spatially heterogeneous bus route network and time-dependent service headways to serve travel demand that varies over time and space. Travelers choose to use either the transit mode or ...

PERGAMON-ELSEVIER SCIENCE LTD2021

A Simulation-Based Heuristic to Find Approximate Equilibria with Disaggregate Demand Models

Michel Bierlaire, Virginie Janine Camille Lurkin, Stefano Bortolomiol

Oligopolistic competition occurs in various transportation markets. In this paper, we introduce a framework to find approximate equilibrium solutions of oligopolistic markets in which demand is modeled at the disaggregate level using discrete choice models ...

INFORMS2021

Stabilization of city-scale road traffic networks via macroscopic fundamental diagram-based model predictive perimeter control

Nikolaos Geroliminis, Isik Ilber Sirmatel

Traffic control for large-scale urban road networks remains a challenging problem. Aggregated dynamical models of city-scale traffic, based on the macroscopic fundamental diagram (MFD), enable development of model-based perimeter control methods. Involving ...

2021

Estimation of regional trip length distributions for the calibration of the aggregated network traffic models

Nikolaos Geroliminis, Sérgio Filipe Assunção Batista

The calibration of trip lengths is an important challenge for multi-regional MFD-based applications, as it can influence the dynamics of regional densities (and speeds). Existing research has not paid significant attention in the topic, giving opportunitie ...

2019

Moving Horizon Estimation for Model Predictive Perimeter Control of Multi-region MFD Networks

Nikolaos Geroliminis, Isik Ilber Sirmatel

Management of road traffic in urban settings remains a challenging problem. Perimeter control schemes proposed to alleviate congestion in large-scale urban networks usually assume noise-free measurements of the traffic state, which is problematic since mea ...

2019

A demand-based optimization approach to find market equilibria in oligopolies

Stefano Bortolomiol

Oligopolistic competition occurs often in transportation as well as in other markets due to reasons such as barriers to entry, limited capacity of the infrastructure and external regulations. In transport oligopolies, suppliers are profit maximizers and ta ...

2019