Results 41 to 50 of about 1,258,510 (324)
Multiple-Factor Based Sparse Urban Travel Time Prediction
Applied Sciences, 2018 The prediction of travel time is challenging given the sparseness of real-time traffic data and the uncertainty of travel, because it is influenced by multiple factors on the congested urban road networks.
Xinyan Zhu +5 more
doaj +1 more source
Travel Time Prediction in Real time for GPS Taxi Data Streams and its Applications to Travel Safety
Human-Centric Intelligent Systems, 2023 The analysis of data streams offers a great opportunity for development of new methodologies and applications in the area of Intelligent Transportation Systems.
Sayan Putatunda, Arnab Kumar Laha
doaj +1 more source
Explainable Federated Learning for Taxi Travel Time Prediction
International Conference on Vehicle Technology and Intelligent Transport Systems, 2021 Transportation data are geographically scattered across different places, detectors, companies, or organisations and cannot be easily integrated under data privacy and related regulations.
J. Fiosina
semanticscholar +1 more source
Travel Time Prediction on Long-Distance Road Segments in Thailand
Applied Sciences, 2022 This study proposes a method by which to predict the travel time of vehicles on long-distance road segments in Thailand. We adopted the Self-Attention Long Short-Term Memory (SA-LSTM) model with a Butterworth low-pass filter to predict the travel time on
Rathachai Chawuthai +4 more
doaj +1 more source
Sustainability, 2021 Travel time prediction is one of the most important parameters to forecast network-wide traffic conditions. Travelers can access traffic roadway networks and arrive in their destinations at the lowest costs guided by accurate travel time estimation on ...
Xiantong Li +3 more
semanticscholar +1 more source
Modelling travel time uncertainty in urban networks based on floating taxi data
European Transport Research Review, 2019 The prediction of the uncertainty of route travel time predictions for all possible routes in an urban road network is of importance for example for logistics. Such predictions need to take the essential features of the data set as well as the underlying
Dietmar Bauer +2 more
doaj +1 more source
Journal of Advanced Transportation, 2020 Freeway travel time prediction is a key technology of Intelligent Transportation Systems (ITS). Many scholars have found that periodic function plays a positive role in improving the prediction accuracy of travel time prediction models. However, very few
Xu Miao, Bing Wu, Yajie Zou, Lingtao Wu
doaj +1 more source
Travel Time Probability Prediction Based on Constrained LSTM Quantile Regression
Journal of Advanced Transportation, 2023 Travel time reliability assessment has been widely used in recent years to evaluate the performance of transportation networks and measure the operation level of transportation systems.
Hao Li +5 more
doaj +1 more source
Freeway Short-Term Travel Time Prediction Based on LightGBM Algorithm
IOP Conference Series: Earth and Environment, 2021 In order to realize the prediction of freeway travel time, a short-term travel time prediction model based on LightGBM (Light Gradient Boosting Machine) is proposed under the influence of weather factors, time period factors, and traffic factors.
Fujian Wang +3 more
semanticscholar +1 more source
Incorporating weather information into real-time speed estimates: comparison of alternative models [PDF]
, 2013 Weather information is frequently requested by travelers. Prior literature indicates that inclement weather is one of the most important factors contributing to traffic congestion and crashes.
Basak D. +3 more
core +1 more source