This work proposes including route information with onboard vehicle data to make longer speed predictions through the use of a new B-spline prediction concept.
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This work proposes including route in- formation with onboard vehicle data to make longer speed predictions.
Abstract—With the automotive industry moving more to the development of electric vehicles due to environmental and emissions restrictions, much work is ...
This paper presents the clustering of different road-shapes like cross junction (i.e. four-way road) or T-junction (i.e. three-way road) or straight road using ...
A deep recurrent neural network-based vehicle speed prediction using long-short term memory (LSTM) and gated recurrent units (GRU) is studied in this work.
Nov 30, 2022 · A deep recurrent neural network-based vehicle speed prediction using long-short term memory (LSTM) and gated recurrent units (GRU) is studied in this work.
Real-time vehicle-to-infrastructure (V2I) communications can provide an accurate speed prediction over a short prediction horizon (e.g., 30 s to 60 s), but not ...
In a typical car-following scenario, target vehicle speed fluctuations act as an external disturbance to the host vehicle and in turn affect its energy ...
Oct 24, 2024 · To deal with minimal data provides a method for short-term traffic prediction using the clustering algorithm, deep learning, and transfer ...
Oct 22, 2024 · Behaviour prediction function of an autonomous vehicle predicts the future states of the nearby vehicles based on the current and past ...