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Estimating Travel Time Distributions by Bayesian Network Inference
IEEE Transactions on Intelligent Transportation Systems, 2020Travel time estimation is an important aspect of intelligent transportation systems (ITS). In urban environments, travel times can exhibit much variability due to various stochastic factors. For this reason, we focus on estimating travel time distributions, in contrast to the more commonly studied estimation of mean expected travel times.
Anatolii Prokhorchuk +2 more
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Empirical travel time estimation in a distribution network
Water Management, 2002In the calibration procedure adopted for most hydraulic network models, parameters are adjusted to ensure that measured and computed pressures are approximately equal. Little emphasis is placed on confirmation of a correct flowrate distribution. Such procedures can therefore promote erroneous flowrate solutions.
P. J. Skipworth, J. Machell, A. J. Saul
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Screening of Groundwater Contaminants by Travel‐Time Distributions
Journal of Environmental Engineering, 1989Analytical procedures are proposed for estimating probability distributions of travel times for chemical waste loads to groundwater. Travel distance of the chemical is treated as a renewal process, and travel time is given by the number of annual chemical displacements or renewals required for passage through the soil unsaturated zone. The methods were
Douglas A. Haith, Ethan M. Laden
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Estimating travel time distributions using copula graphical lasso
2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), 2017Travel time information is crucial for Intelligent Transportation Systems (ITS). Taxis equipped with GPS tracking systems are one possible source for extracting travel time information. In this study, we present a framework for estimating travel time distributions on a city-scale network based on GPS trajectories of taxis.
Anatolii Prokhorchuk +3 more
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Synthesizing route travel time distributions considering spatial dependencies
2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), 2016Estimation of route-level travel time distributions (or travel rates) from segment-level data is of great interest today. This paper shows how the random variable properties of comonotonicity and independence can be used in combination to develop such distributions for a wide range of operating conditions. Efficacy of the technique is illustrated using
Isaac K Isukapati, George F List
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Grouping of travel time distributions
Transportation Research, 1970John W. Dickey, Samuel P. Hunter
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2023
Tesis (Master of Science in Engineering)--Pontificia Universidad Católica de Chile, 2013 ; Los modelos lluvia-escorrentía son herramientas valiosas para simular la respuesta hidrológica de una cuenca. En años recientes, modelos distribuidos de aguas lluvias han sido desarrollados tales como los modelos de Tiempos de Viaje Distribuidos Espacialmente (o ...
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Tesis (Master of Science in Engineering)--Pontificia Universidad Católica de Chile, 2013 ; Los modelos lluvia-escorrentía son herramientas valiosas para simular la respuesta hidrológica de una cuenca. En años recientes, modelos distribuidos de aguas lluvias han sido desarrollados tales como los modelos de Tiempos de Viaje Distribuidos Espacialmente (o ...
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TRAVEL TIME DISTRIBUTION FOR NETWORK FLOWS UNDER LOCAL ROUTING
International Journal of Modern Physics C, 2011When transporting data packets on communication networks, the local routing protocols are often preferred because of the large-scale and complicated property of many realistic network structures such as Internet. Based on a local routing protocol with a navigation parameter proposed in a previous paper [W. X. Wang et al., Phys. Rev. E73, 026111 (2006)]
CHAO-YANG WANG +3 more
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Analysis of Travel Time Distribution for Varying Length of Time Interval
2020This study intends to determine the most appropriate distribution for modeling travel time variability. It also aims to explore the effects of the time of day and the length of the analysis time interval on the type of the best-fit probability distribution function.
Ganjkhanloo, Alireza +3 more
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How Random Incidents Affect Travel-Time Distributions
IEEE Transactions on Intelligent Transportation Systems, 2022Melike Baykal-Gursoy +3 more
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