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, 2017 This paper discusses the methods of travel time prediction based on the usage of machine learning and historical data. The developed prediction models are described as well as the data sources which were used as the input of the prediction models. Finally, the comparison of the models‘ performance is shown, providing proof the developed models have ...
Mudroch, Andrej
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A Personalised Online Travel Time Prediction Model
2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013Congestion slows road traffic. This has become a prominent urban road traffic problem. For commuters about to travel, or on route, accurate travel forecasts enable them to choose the right routes in a timely manner to avoid travel delays. In this paper, a personalised online travel time prediction model is proposed. The novelty of the work is threefold.
Zhenchen Wang, Stefan Poslad
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Assessing the predictability of scheduled-vehicle travel times
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2009One of the most desired and challenging services in collective transport systems is the real-time prediction of the near-future travel times of scheduled vehicles, especially public buses, thus improving the experience of the transportation users, who may be able to better schedule their travel, and also enabling system operators to perform real-time ...
Dalia Tiesyte, Christian S. Jensen
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Similarity-based prediction of travel times for vehicles traveling on known routes
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems, 2008The use of centralized, real-time position tracking is proliferating in the areas of logistics and public transportation. Real-time positions can be used to provide up-to-date information to a variety of users, and they can also be accumulated for uses in subsequent data analyses. In particular, historical data in combination with real-time data may be
Dalia Tiesyte, Christian S. Jensen
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A simple and effective method for predicting travel times on freeways
ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585), 2002We present a method to predict the time that will be needed to traverse a certain stretch of freeway when departure is at a certain time in the future. The prediction is done on the basis of the current traffic situation in combination with historical data. We argue that, for our purpose, the current situation of a stretch of freeway is well summarized
John Rice, Erik van Zwet
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AN ADAPTIVE SYSTEM FOR PREDICTING FREEWAY TRAVEL TIMES
International Journal of Information Technology & Decision Making, 2012This paper presents an adaptive system that embeds a Bayesian inference-based dynamic model (BDM) for predicting real-time travel time on a freeway corridor. Bayesian forecasting is a learning process that revises sequentially the state of a priori knowledge of travel time based on newly available information.
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Travel-Time Prediction for Freeway Corridors
Transportation Research Record: Journal of the Transportation Research Board, 1999The application of a nonlinear time series model to the prediction of traffic parameters on a freeway network is investigated. The nonlinear time series approach is a statistical technique that has strong potential for on-line implementation. A new approach for predicting corridor travel times is developed and tested with travel-time data.
D'Angelo, Matthew P. +2 more
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Online Prediction of Travel Time: Experience From a Pilot Trial
Transportation Planning and Technology, 2007This study was designed to present an online model which predicted travel times on an interurban two-lane two-way highway section on the basis of field measurements. The study included two parts: an evaluation of the performance of the model, and an examination of the possibility to improve the model in case of unsatisfactory performance. The model was
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Travel-time prediction with deep learning
2016 IEEE Region 10 Conference (TENCON), 2016Travel time prediction is a challenging problem in Intelligent Transportation Systems (ITS). Accurate travel time information helps motorists plan their routes more wisely. This, in turn, alleviates traffic congestion and improves operation efficiency.
Chaiyaphum Siripanpornchana +2 more
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Travel time prediction in transport and logistics
VINE Journal of Information and Knowledge Management Systems, 2019Purpose Many transport and logistics companies nowadays use raw vehicle GPS data for travel time prediction. However, they face difficult challenges in terms of the costs of information storage, as well as the quality of the prediction. This paper aims to systematically investigate various meta-data (features) that require significantly less storage ...
Xia Li +3 more
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