Emma Frejinger

Emma Frejinger
Université de Montréal | UdeM · Department of Computer Science and Operations Research

PhD Mathematics

About

38
Publications
5,585
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1,286
Citations

Publications

Publications (38)
Article
Traffic flow predictions are central to a wealth of problems in transportation. Path choice models can be used for this purpose, and in state-of-the-art models—so-called recursive path choice (RPC) models—the choice of a path is formulated as a sequential arc choice process using undiscounted Markov decision process (MDP) with an absorbing state. T...
Article
We propose a Recursive Logit (STD-RL) model for routing policy choice in a stochastic time-dependent (STD) network, where a routing policy is a mapping from states to actions on which link to take next, and a state is defined by node, time and information. A routing policy encapsulates travelers’ adaptation to revealed traffic conditions when makin...
Article
Full-text available
The problem at the heart of this tutorial consists in modeling the path choice behavior of network users. This problem has been extensively studied in transportation science, where it is known as the route choice problem. In this literature, individuals’ choice of paths are typically predicted using discrete choice models. This article is a tutoria...
Preprint
We study the routing policy choice problems in a stochastic time-dependent (STD) network. A routing policy is defined as a decision rule applied at the end of each link that maps the realized traffic condition to the decision on the link to take next. Two types of routing policy choice models are formulated with perfect online information (POI): re...
Article
Full-text available
Travel information has the potential to influence travellers choices, in order to steer travellers to less congested routes and alleviate congestion. This paper investigates, on the one hand, how travel information affects route choice behaviour, and on the other hand, the impact of the travel time representation on the interpretation of parameter...
Article
This paper focuses on the comparison of the random regret minimization (RRM) and mother logit models for analyzing the choice between alternatives having deterministic attributes. The mother logit model allows utilities of a given alternative to depend on attributes of other alternatives. It was designed to relax the independence from irrelevant al...
Article
We propose a way to estimate a family of static Multivariate Extreme Value (MEV) models with large choice sets in short computational time. The resulting model is also straightforward and fast to use for prediction. Following Daly and Bierlaire (2006), the correlation structure is defined by a rooted, directed graph where each node without successo...
Article
Full-text available
Fosgerau et al. (2013) recently proposed the recursive logit (RL) model for route choice problems, that can be consistently estimated and easily used for prediction without any sampling of choice sets. Its estimation however requires solving many large-scale systems of linear equations, which can be computationally costly for real data sets. We des...
Article
We propose a route choice model that relaxes the independence from irrelevant alternatives property of the logit model by allowing scale parameters to be link specific. Similar to the recursive logit (RL) model proposed by Fosgerau et al. (2013), the choice of path is modeled as a sequence of link choices and the model does not require any sampling...
Technical Report
The multinomial logit (MNL) model is in general used for analyzing route choices in real networks in spite of the fact that path utilities are believed to be correlated. For this reason different attributes, such as path size, have been proposed to deterministically correct the utilities for correlation and they are often used in practice. Yet, sta...
Article
Full-text available
This research focuses on the formulation of a dynamic discrete-continuous choice model to explain and predict individuals choices regarding car ownership, choice of fuel type and choice of annual driving distance. Its main contribution is to integrate dynamic choice modeling for multiple-car households and discrete-continuous choice modeling. This...
Article
Full-text available
This paper considers the path choice problem, formulating and discussing an econometric random utility model for the choice of path in a network with no restriction on the choice set. Starting from a dynamic specification of link choices we show that it is equivalent to a static model of the multinomial logit form but with infinitely many alternati...
Article
Full-text available
Car ownership and usage can vary importantly across years due to various factors, such as the introduction of new governmental policies, changes in the available technologies or variations of the market features. In order to explain and predict these changes, appropriate demand models are needed. Cars are durable goods and households account for th...
Article
Full-text available
We formulate a dynamic discrete-continuous choice model (DDCCM) of car ownership, usage and fuel type. The framework embeds a discrete-continuous choice model (DCCM) into a dynamic programming (DP) framework to account for the forward-looking behavior of households in the context of car acquisition. More specifically, we model the of transaction ty...
Article
Full-text available
In this paper we present themethodological framework of a dynamic discrete-continuous choice model (DDCCM) of car ownership, usage and fuel type. The approach consists of embedding a discrete-continuous choice model into a dynamic programming (DP) framework. This work proposes the following novel features. First, decisions are modeled at a househol...
Article
Full-text available
In this research we specify a dynamic discrete-continuous choice model (DDCCM) of car ownership and usage. This model embeds a discrete-continuous choice model into a dynamic programming (DP) framework. The DDCCM allows to jointly model the transaction type, the annual driving distance, the fuel type, the car ownership status and the car state (i.e...
Conference Paper
The past decades have seen an increased interest in the role of information as a tool to alleviate congestion. However, because the relationship between travelers' behavior and information provision is not clear yet, the need for more experiments has been claimed in literature. From May 9th, 2011 to July 12th, 2011 a revealed route choice experimen...
Article
Full-text available
Real-time traffic information is increasingly available to support route choice decisions by reducing the travel time uncertainty. However it is likely that a traveler cannot assess all available information on all alternative routes due to time constraints and limited cognitive capacity. This paper presents a model that is consistent with a genera...
Article
This paper deals with route choice models capturing travelers’ strategic behavior when adapting to revealed traffic conditions en route in a stochastic network. The strategic adaptive behavior is conceptualized as a routing policy, defined as a decision rule that maps from all possible revealed traffic conditions to the choices of next link out of...
Article
This paper presents a new paradigm for choice set generation in the context of route choice model estimation. We assume that the choice sets contain all paths connecting each origin–destination pair. Although this is behaviorally questionable, we make this assumption in order to avoid bias in the econometric model. These sets are in general impossi...
Article
Adaptive route choice models are studied that explicitly capture travelers' route choice adjustments according to information on realized network conditions in stochastic time-dependent networks. Two types of adaptive route choice models are explored: an adaptive path model in which a sequence of path choice models are applied at intermediate decis...
Article
Route choice models are difficult to design and to estimate for various reasons. In this paper we focus on issues related to data. Indeed, real data in its original format are not related to the network used by the modeler and do therefore not correspond to path definitions. Typical examples are data collected with the Global Positioning System (GP...
Article
Full-text available
This thesis focuses on the route choice behavior of car drivers (uni-modal networks). More precisely, we are interested in identifying which route a given traveler would take to go from one location to another. For the analysis of this problem we use discrete choice models and disaggregate revealed preferences data. Route choice models play an impo...
Article
When using random utility models for a route choice problem, choice set generation and correlation among alternatives are two issues that make the modelling complex. In this paper, we propose a modelling approach where the path overlap is captured with a subnetwork. A subnetwork is a simplification of the road network only containing easy identifia...
Article
We study adaptive route choice models that explicitly capture travelers' route choice adjustments according to information on realized network conditions in stochastic time-dependent networks. Two types of adaptive route choice models are explored: an adaptive path model where a sequence of path choice models are applied at intermediate decision no...
Article
In this paper we present a new point of view on choice set generation for route choice models. When modeling route choice behavior using random utility models choice sets of paths need to be defined. Existing approaches generate paths and assume th at actual choice sets are found. On the contrary, we assume that actual choice sets are the sets of a...

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Project (1)
Project
Route choice models without consideration sets, but simply using whole networks