Results 251 to 260 of about 15,987,795 (287)
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Travel Time Prediction on Highways
2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing, 2015We describe the development of a predictive model for vehicle journey time on highways. Accurate travel time prediction is an important problem since it enables planning of cost effective vehicle routes and departure times, with the aim of saving time and fuel while reducing pollution.
Jan Rupnik +4 more
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Transportation Research Record: Journal of the Transportation Research Board, 2008
As reported in the literature for the applications of intelligent transportation systems with traffic detectors, various missing data patterns are frequently observed in such systems and may dramatically degrade their performance. This study presents two imputation approaches for contending with the missing data issues in travel time prediction.
Jianwei Wang, Nan Zou, Gang-Len Chang
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As reported in the literature for the applications of intelligent transportation systems with traffic detectors, various missing data patterns are frequently observed in such systems and may dramatically degrade their performance. This study presents two imputation approaches for contending with the missing data issues in travel time prediction.
Jianwei Wang, Nan Zou, Gang-Len Chang
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Experienced travel time prediction for freeway systems
2012 15th International IEEE Conference on Intelligent Transportation Systems, 2012Travel time is considered as one of the most important performance measures for roadway systems, and dissemination of travel time information can help travelers to make reliable travel decisions such as route choice or time departure. Since the traffic data collected in real time reflects the past or the current conditions on the roadway, a predictive ...
Mehmet Yildirimoglu, Nikolas Geroliminis
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Travel Time Functions Prediction for Time-Dependent Networks
Cognitive Computation, 2018The studies on the TDN (time-dependent network), in which the travel time of the same road segment varies depending on the time of the day, have attracted much attention of researchers, but there is little work focusing on the travel time functions prediction problem.
Jiajia Li 0003 +4 more
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Travel Time Prediction for Trams in Warsaw
2017The paper presents a comparison between different prediction methods for trams time travels in Warsaw. Predictions are constructed based on historical trams GPS positions. Three different prediction approaches were implemented and compared with the official timetables and real time travels.
Adam Zychowski +2 more
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On the Limitations of Linear Models in Predicting Travel Times
2007 IEEE Intelligent Transportation Systems Conference, 2007Traffic congestion is growing in major cities, and, consequently, delays are becoming more frequent. Route guidance systems can significantly reduce delays by assisting drivers in finding alternative routes. Due to simplicity and scalability, the linear predictors have been an essential part of route guidance systems in predicting the future travel ...
Erick J. Schmitt, Hossein Jula
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Travel-Time Prediction Methods: A Review
2018Near-future Travel-time information is helpful to implement Intelligent Transportation Systems (ITS). Travel-time prediction refers to predicting future travel-time. Researchers have developed various methods to predict travel-time in the past decades. This paper conducts a review focusing on literatures, including techniques proposed recently.
Mengting Bai +3 more
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Online travel time prediction based on boosting
2009 12th International IEEE Conference on Intelligent Transportation Systems, 2009Travel time prediction is a very important problem in intelligent transportation system research. We examine the use of boosting, a machine learning technique in travel time prediction, and combine boosting and neural network models to increase prediction accuracy.
Ying Li 0010 +2 more
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Travel time prediction with LSTM neural network
2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), 2016Travel time is one of the key concerns among travelers before starting a trip and also an important indicator of traffic conditions. However, travel time acquisition is time delayed and the pattern of travel time is usually irregular. In this paper, we explore a deep learning model, the LSTM neural network model, for travel time prediction.
Yanjie Duan +2 more
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Real-Time Freeway Travel-Time Prediction
Engineering & Technology Reference, 2015This article develops a framework that includes three major categories of methodologies for real-time freeway travel-time prediction. The proposed methodologies include traffic modelling, pattern recognition and recursive probabilistic algorithms. Each developed method attempts to predict travel times for different prediction horizons.
Hao Chen, Hesham Rakha
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