Searched for: subject%3A%22Traffic%255C+flow%255C+predictions%22
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Nachev, Nikola (author)
Accurate traffic forecasts are a key element in improving the traffic flow of urban cities. An efficient approach to this problem is to use a deep learning Long Short Term Memory (LSTM) model. Including weather data in the model can improve prediction accuracy because traffic volumes are sensitive to weather changes. The aim of this study is to...
bachelor thesis 2023
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Petsch, Carmen (author)
Traffic flow predictions are an important component in the rising demand for solutions to cope with the increasing pressure on transportation networks. Especially on a long prediction horizon, traffic flow predictions remain challenging due to the complex, nonlinear nature of traffic flow and the influence of both temporal and external features....
master thesis 2022
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Chen, Zhijun (author), Lu, Zhe (author), Chen, Qiushi (author), Zhong, Hongliang (author), Zhang, Yishi (author), Xue, J. (author), Wu, Chaozhong (author)
Short-term traffic flow prediction is a core branch of intelligent traffic systems (ITS) and plays an important role in traffic management. The graph convolution network (GCN) is widely used in traffic prediction models to efficiently handle the graphical structural data of road networks. However, the influence weights among different road...
journal article 2022
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Tao, Qinghua (author), Li, Zhen (author), Xu, Jun (author), Lin, Shu (author), De Schutter, B.H.K. (author), Suykens, Johan A.K. (author)
Traffic flow (TF) prediction is an important and yet a challenging task in transportation systems, since the TF involves high nonlinearities and is affected by many elements. Recently, neural networks have attracted much attention for TF prediction, but they are commonly black boxes with complex architectures and difficult to be interpreted,...
journal article 2022
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Simons, Koen (author)
As traffic demands are ever increasing and building new infrastructure poses challenges in densely populated areas, it is important to optimally utilise existing infrastructure. Short-term traffic forecasting can help with this task, as its predictions can help to prevent congestion by rerouting vehicles. Recently, neural networks developed for...
master thesis 2021
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van Senden, JanCees (author)
Traffic congestion at signalized intersections is a big economical and ecological problem. Handcrafted traffic light controllers (TLCs) are currently used to minimize the impact, but they are expensive to design and maintain and their performance degrades over time. Predictive TLCs and advanced driver assistance systems (ADAS) form a potential...
master thesis 2018
Searched for: subject%3A%22Traffic%255C+flow%255C+predictions%22
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