Searched for: subject%3A%22Prediction%22
(1 - 7 of 7)
document
Yap, M.D. (author), Cats, O. (author)
Public transport disruptions can result in major impacts for passengers and operator. Our study objective is to predict disruption exposure at different stations, incorporating their location-specific characteristics. Based on a 13-month incident database for the Washington metro network, we successfully develop a supervised learning model to...
conference paper 2019
document
Gavriilidou, A. (author), Cats, O. (author)
Real-time holding control strategies are implemented, among other reasons, in order to protect transfers. In the context of high-frequency services, there is a need to reconcile between striving for single-line regularity and synchronizing inter-line arrivals. Their operationalization depends on the predictions regarding passenger flows...
journal article 2018
document
Ghaemi, N. (author), Zilko, A.A. (author), Yan, F. (author), Cats, O. (author), Kurowicka, D. (author), Goverde, R.M.P. (author)
Disruptions such as rolling stock breakdown, signal failures, and accidents are recurrent events during daily railway operation. Such events disrupt the deployment of resources and cause delay to passengers. Obtaining a reliable disruption length estimation can potentially reduce the negative impact caused by the disruption. Different factors...
journal article 2018
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Cats, O. (author), Loutos, G (author)
Online predictions of bus arrival times have the potential to reduce the uncertainty associated with bus operations. By better anticipating future conditions, online predictions can reduce perceived and actual passenger travel times as well as facilitate more proactive decision making by service providers. Even though considerable research...
journal article 2016
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Morriea-Matias, Luis (author), Cats, O. (author), Gama, Joao (author), Mendes-Moreira, Joao (author), Freire de Sousa, Jorge (author)
Recent advances in telecommunications created new opportunities for monitoring public transport operations in real-time. This paper presents an automatic control framework to mitigate the Bus Bunching phenomenon in real-time. The framework depicts a powerful combination of distinct Machine Learning principles and methods to extract valuable...
journal article 2016
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Fadaei, Masoud (author), Cats, O. (author), Bhaskar, Ashish (author)
The uncertainty associated with public transport services can be partially counteracted by developing real-time models to predict downstream service conditions. In this study, a hybrid approach for predicting bus trajectories by integrating multiple predictors is proposed. The prediction model combines schedule, instantaneous and historical...
journal article 2016
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Oshyani, M.F. (author), Cats, O. (author)
Bus travel times are subject to inherent and recurrent uncertainties. A real-time prediction scheme regarding how the transit system evolves will potentially facilitate more adaptive operations as well as more adaptive passengers’ decisions. This scheme should be tractable, sufficiently fast and reliable to be used in real time applications. For...
conference paper 2014
Searched for: subject%3A%22Prediction%22
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