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Buses operating in mixed traffic experience problems with delay and travel time variability in peak periods. Numerous transit priority measures are found in the literature but most rely on separating buses from other vehicles. Complete separation such as d ...
Driving is a very challenging task to automatize despite how naturally and efficiently it may come to experienced human drivers. The complexity stems from the need to (i) understand the surrounding context and forecast how it is likely to evolve, (ii) plan ...
This research presents the implementation of two different transit signal priority strategies and assesses their impact on the whole network through a bi-modal three-dimensional Macroscopic Fundamental Diagram. The first TSP strategy is the green extension ...
The objective of this thesis is to develop a general methodology to incorporate a disaggregate demand representation in supply-oriented optimization problems that allows to capture the interplay between the behavior of individuals and the decisions to be o ...
The study of how people schedule their daily activities is of interest in the context of transport demand forecasting using activity based-models, where activity schedules are generated in order to estimate the trip demand they produce. Machine learning ha ...
Making decisions is part and parcel of being human. Among a set of actions, we want to choose the one that has the highest reward. But the uncertainty of the outcome prevents us from always making the right decision. Making decisions under uncertainty can ...
Although the idea of vehicle sharing systems (VSSs) emerges back in 1940s, sustaining such a system became simpler with the improvements in technology in the past decade. In addition to that, people have become more concerned about environmental effects an ...
Although the idea of vehicle sharing systems (VSSs) emerged back in 1940s, sustaining such a system became simpler with the improvements in technology in the past decade. In addition to that, people have become more concerned about environmental effects an ...
In discrete choice modeling (DCM), model misspecifications may lead to limited predictability and biased parameter estimates. In this paper, we propose a new approach for estimating choice models in which we divide the systematic part of the utility specif ...
Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...
