Emergency medical services and beyond: Addressing new challenges through a wide literature review
One of the most important health care services is emergency medical service as it plays a
vital role in saving people's lives and reducing the rate of mortality and morbidity. Over the …
vital role in saving people's lives and reducing the rate of mortality and morbidity. Over the …
[HTML][HTML] Emergency response facility location in transportation networks: A literature review
Y Liu, Y Yuan, J Shen, W Gao - Journal of traffic and transportation …, 2021 - Elsevier
Emergency response activity relies on transportation networks. Emergency facility location
interacts with transportation networks clearly. This review is aimed to provide a combined …
interacts with transportation networks clearly. This review is aimed to provide a combined …
Deep spatial–temporal 3D convolutional neural networks for traffic data forecasting
Reliable traffic prediction is critical to improve safety, stability, and efficiency of intelligent
transportation systems. However, traffic prediction is a very challenging problem because …
transportation systems. However, traffic prediction is a very challenging problem because …
Deep learning for short-term traffic flow prediction
NG Polson, VO Sokolov - Transportation Research Part C: Emerging …, 2017 - Elsevier
We develop a deep learning model to predict traffic flows. The main contribution is
development of an architecture that combines a linear model that is fitted using ℓ 1 …
development of an architecture that combines a linear model that is fitted using ℓ 1 …
Travel time estimation for urban road networks using low frequency probe vehicle data
E Jenelius, HN Koutsopoulos - Transportation Research Part B …, 2013 - Elsevier
The paper presents a statistical model for urban road network travel time estimation using
vehicle trajectories obtained from low frequency GPS probes as observations, where the …
vehicle trajectories obtained from low frequency GPS probes as observations, where the …
A simple baseline for travel time estimation using large-scale trip data
The increased availability of large-scale trajectory data provides rich information for the
study of urban dynamics. For example, New York City Taxi 8 Limousine Commission …
study of urban dynamics. For example, New York City Taxi 8 Limousine Commission …
Traffic flow prediction over muti-sensor data correlation with graph convolution network
W Li, X Wang, Y Zhang, Q Wu - Neurocomputing, 2021 - Elsevier
Accurate and real-time traffic flow prediction plays an important role in improving the traffic
planning capability of intelligent traffic systems. However, traffic flow prediction is a very …
planning capability of intelligent traffic systems. However, traffic flow prediction is a very …
Multiple dynamic graph based traffic speed prediction method
Traffic speed prediction is a crucial and challenging task for intelligent transportation
systems. The prediction task can be accomplished via graph neural networks with structured …
systems. The prediction task can be accomplished via graph neural networks with structured …
Predicting travel time reliability using mobile phone GPS data
Estimates of road speeds have become commonplace and central to route planning, but few
systems in production provide information about the reliability of the prediction. Probabilistic …
systems in production provide information about the reliability of the prediction. Probabilistic …
A novel generative adversarial network for estimation of trip travel time distribution with trajectory data
K Zhang, N Jia, L Zheng, Z Liu - Transportation Research Part C: Emerging …, 2019 - Elsevier
Abstract Knowledge of trip travel times serves an important role in transportation
management and control. Existing travel time estimation approaches generally cover …
management and control. Existing travel time estimation approaches generally cover …