Energy saving potentials of connected and automated vehicles
A Vahidi, A Sciarretta - Transportation Research Part C: Emerging …, 2018 - Elsevier
Connected and automated vehicles (CAV) are marketed for their increased safety, driving
comfort, and time saving potential. With much easier access to information, increased …
comfort, and time saving potential. With much easier access to information, increased …
[HTML][HTML] Leveraging reinforcement learning for dynamic traffic control: A survey and challenges for field implementation
In recent years, the advancement of artificial intelligence techniques has led to significant
interest in reinforcement learning (RL) within the traffic and transportation community …
interest in reinforcement learning (RL) within the traffic and transportation community …
Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments
Traffic waves are phenomena that emerge when the vehicular density exceeds a critical
threshold. Considering the presence of increasingly automated vehicles in the traffic stream …
threshold. Considering the presence of increasingly automated vehicles in the traffic stream …
Network-wide traffic signal control optimization using a multi-agent deep reinforcement learning
Inefficient traffic control may cause numerous problems such as traffic congestion and
energy waste. This paper proposes a novel multi-agent reinforcement learning method …
energy waste. This paper proposes a novel multi-agent reinforcement learning method …
Optimal perimeter control for two urban regions with macroscopic fundamental diagrams: A model predictive approach
N Geroliminis, J Haddad… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
Recent analysis of empirical data from cities showed that a macroscopic fundamental
diagram (MFD) of urban traffic provides for homogenous network regions a unimodal low …
diagram (MFD) of urban traffic provides for homogenous network regions a unimodal low …
A physics-informed reinforcement learning-based strategy for local and coordinated ramp metering
This paper proposes a physics-informed reinforcement learning (RL)-based ramp metering
strategy, which trains the RL model using a combination of historic data and synthetic data …
strategy, which trains the RL model using a combination of historic data and synthetic data …
Economic model predictive control of large-scale urban road networks via perimeter control and regional route guidance
II Sirmatel, N Geroliminis - IEEE Transactions on Intelligent …, 2017 - ieeexplore.ieee.org
Local traffic control schemes fall short of achieving coordination with other parts of the urban
road network, whereas a centralized controller based on the detailed traffic models would …
road network, whereas a centralized controller based on the detailed traffic models would …
Parsimonious shooting heuristic for trajectory design of connected automated traffic part I: Theoretical analysis with generalized time geography
This paper studies a problem of designing trajectories of a platoon of vehicles on a highway
segment with advanced connected and automated vehicle technologies. This problem is …
segment with advanced connected and automated vehicle technologies. This problem is …
Controllability analysis and optimal control of mixed traffic flow with human-driven and autonomous vehicles
Connected and automated vehicles (CAVs) have a great potential to improve traffic
efficiency in mixed traffic systems, which has been demonstrated by multiple numerical …
efficiency in mixed traffic systems, which has been demonstrated by multiple numerical …
A new reinforcement learning-based variable speed limit control approach to improve traffic efficiency against freeway jam waves
Conventional reinforcement learning (RL) models of variable speed limit (VSL) control
systems (and traffic control systems in general) cannot be trained in real traffic process …
systems (and traffic control systems in general) cannot be trained in real traffic process …