Macroscopic network-level traffic models: Bridging fifty years of development toward the next era
Network macroscopic fundamental diagrams (NMFD) and related network-level traffic
dynamics models have received both theoretical support and empirical validation with the …
dynamics models have received both theoretical support and empirical validation with the …
On the new era of urban traffic monitoring with massive drone data: The pNEUMA large-scale field experiment
E Barmpounakis, N Geroliminis - Transportation research part C: emerging …, 2020 - Elsevier
The new era of sharing information and “big data” has raised our expectations to make
mobility more predictable and controllable through a better utilization of data and existing …
mobility more predictable and controllable through a better utilization of data and existing …
Congestion prediction for smart sustainable cities using IoT and machine learning approaches
Congestion on road networks has a negative impact on sustainability in many cities through
the exacerbation of air pollution. Smart congestion management allows road users to avoid …
the exacerbation of air pollution. Smart congestion management allows road users to avoid …
[HTML][HTML] Multi-scale collision risk estimation for maritime traffic in complex port waters
Ship collision risk estimation is an essential component of intelligent maritime surveillance
systems. Traditional risk estimation approaches, which can only analyze traffic risk in one …
systems. Traditional risk estimation approaches, which can only analyze traffic risk in one …
Dynamic traffic assignment using the macroscopic fundamental diagram: A review of vehicular and pedestrian flow models
R Aghamohammadi, JA Laval - Transportation Research Part B …, 2020 - Elsevier
Abstract Link-level Dynamic Traffic Assignment (DTA) models of large cities may suffer from
prohibitive computation times, and calibration/validation can become the major challenge …
prohibitive computation times, and calibration/validation can become the major challenge …
Data efficient reinforcement learning and adaptive optimal perimeter control of network traffic dynamics
Existing data-driven and feedback traffic control strategies do not consider the heterogeneity
of real-time data measurements. Besides, traditional reinforcement learning (RL) methods …
of real-time data measurements. Besides, traditional reinforcement learning (RL) methods …
[HTML][HTML] Maritime traffic partitioning: An adaptive semi-supervised spectral regularization approach for leveraging multi-graph evolutionary traffic interactions
Maritime situational awareness (MSA) has long been a critical focus within the domain of
maritime traffic surveillance and management. The increasing complexities of ship traffic …
maritime traffic surveillance and management. The increasing complexities of ship traffic …
[HTML][HTML] A simple contagion process describes spreading of traffic jams in urban networks
The spread of traffic jams in urban networks has long been viewed as a complex spatio-
temporal phenomenon that often requires computationally intensive microscopic models for …
temporal phenomenon that often requires computationally intensive microscopic models for …
Maritime traffic clustering to capture high-risk multi-ship encounters in complex waters
Maritime traffic situational awareness is fundamental to the safety of maritime transportation.
The state-of-the-art research primarily attaches importance to collision risk estimation and …
The state-of-the-art research primarily attaches importance to collision risk estimation and …
Hierarchical control of heterogeneous large-scale urban road networks via path assignment and regional route guidance
High level of detail renders microscopic traffic models impractical for control purposes and
local control schemes cannot coordinate actions over large scale heterogeneously …
local control schemes cannot coordinate actions over large scale heterogeneously …