Intelligent traffic management: A review of challenges, solutions, and future perspectives
R Ravish, SR Swamy - Transport and Telecommunication Journal, 2021 - sciendo.com
Congestion of traffic is a key problem faced in a majority of metro cities, especially in the
developing world. Traffic congestion comprises of queues, reduced speeds, and increased …
developing world. Traffic congestion comprises of queues, reduced speeds, and increased …
Day-ahead traffic flow forecasting based on a deep belief network optimized by the multi-objective particle swarm algorithm
Traffic flow forecasting is a necessary part in the intelligent transportation systems in
supporting dynamic and proactive traffic control and making traffic management plan …
supporting dynamic and proactive traffic control and making traffic management plan …
Predicting traffic demand during hurricane evacuation using Real-time data from transportation systems and social media
In recent times, hurricanes Matthew, Harvey, and Irma have disrupted the lives of millions of
people across multiple states in the United States. Under hurricane evacuation, efficient …
people across multiple states in the United States. Under hurricane evacuation, efficient …
Data-driven analysis and forecasting of highway traffic dynamics
The unpredictable elements involved in a vehicular traffic system, like human interaction and
weather, lead to a very complicated, high-dimensional, nonlinear dynamical system …
weather, lead to a very complicated, high-dimensional, nonlinear dynamical system …
Short-term traffic flow prediction using the modified elman recurrent neural network optimized through a genetic algorithm
A Sadeghi-Niaraki, P Mirshafiei, M Shakeri… - IEEE …, 2020 - ieeexplore.ieee.org
Traffic stream determining is an essential part of the intelligent transportation management
system. Precise prediction of traffic flow provides a basis for other tasks, like forecasting …
system. Precise prediction of traffic flow provides a basis for other tasks, like forecasting …
An integrated feature learning approach using deep learning for travel time prediction
Travel time data is a vital factor for numbers of performance measures in transportation
systems. Travel time prediction is both a challenging and interesting problem in ITS …
systems. Travel time prediction is both a challenging and interesting problem in ITS …
Bus dynamic travel time prediction: using a deep feature extraction framework based on RNN and DNN
Travel time data is an important factor for evaluating the performance of a public transport
system. In terms of time and space within the nature of uncertainty, bus travel time is …
system. In terms of time and space within the nature of uncertainty, bus travel time is …
[HTML][HTML] Short-term traffic flow prediction: an ensemble machine learning approach
G Dai, J Tang, W Luo - Alexandria Engineering Journal, 2023 - Elsevier
The inconvenience of travel, air pollution and consequent economic losses caused by traffic
congestion have seriously restricted the healthy and sustainable development of cities in …
congestion have seriously restricted the healthy and sustainable development of cities in …
[HTML][HTML] Decision support for improved construction traffic management and planning
N Brusselaers, A Fredriksson, D Gundlegård… - Sustainable Cities and …, 2024 - Elsevier
Densifying cities continuously call for new construction, renovation and demolition projects,
each generating vast amounts of heavy goods vehicle (HGV) transports. However, how …
each generating vast amounts of heavy goods vehicle (HGV) transports. However, how …
A deep learning approach for network-wide dynamic traffic prediction during hurricane evacuation
Proactive evacuation traffic management largely depends on real-time monitoring and
prediction of traffic flow at a high spatiotemporal resolution. However, evacuation traffic …
prediction of traffic flow at a high spatiotemporal resolution. However, evacuation traffic …