[HTML][HTML] At-stop control measures in public transport: Literature review and research agenda
K Gkiotsalitis, O Cats - Transportation Research Part E: Logistics and …, 2021 - Elsevier
In this literature review, we systematically review studies on public transit control with a
specific focus on at-stop measures. In our synthesis of the relevant literature, we consider …
specific focus on at-stop measures. In our synthesis of the relevant literature, we consider …
Control for smart systems: Challenges and trends in smart cities
There have been tremendous developments in theories and technologies in control for
smart systems. In this paper we review applications to various systems that are crucial for the …
smart systems. In this paper we review applications to various systems that are crucial for the …
The multi-depot electric vehicle scheduling problem with power grid characteristics
Electric buses can bring significant environmental and social benefits in the future public
transportation systems. However, the large-scale adoption of electric buses faces major …
transportation systems. However, the large-scale adoption of electric buses faces major …
Data-driven estimation of energy consumption for electric bus under real-world driving conditions
Reliable and accurate estimation of an electric bus's instantaneous energy consumption is
critical in evaluating energy impacts of planning and control of electric bus operations. In this …
critical in evaluating energy impacts of planning and control of electric bus operations. In this …
Decentralized signal control for multi-modal traffic network: A deep reinforcement learning approach
Managing traffic flow at intersections in a large-scale network remains challenging. Multi-
modal signalized intersections integrate various objectives, including minimizing the queue …
modal signalized intersections integrate various objectives, including minimizing the queue …
Optimised traffic light management through reinforcement learning: Traffic state agnostic agent vs. holistic agent with current V2I traffic state knowledge
Traffic light control falls into two main categories: Agnostic systems that do not exploit
knowledge of the current traffic state, eg, the positions and velocities of vehicles …
knowledge of the current traffic state, eg, the positions and velocities of vehicles …
Bilevel optimization for bunching mitigation and eco-driving of electric bus lines
R Lacombe, S Gros, N Murgovski… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The problems of bus bunching mitigation and the energy management of groups of vehicles
have traditionally been treated separately in the literature and been formulated in two …
have traditionally been treated separately in the literature and been formulated in two …
A robust integrated multi-strategy bus control system via deep reinforcement learning
An efficient urban bus control system has the potential to significantly reduce travel delays
and streamline the allocation of transportation resources, thereby offering enhanced and …
and streamline the allocation of transportation resources, thereby offering enhanced and …
Deep Reinforcement Learning Two-Way Transit Signal Priority Algorithm for Optimizing Headway Adherence and Speed
Transit Signal Priority (TSP) is a broadly used traffic signal control strategy designed for
reducing transit delays at signalized intersections. Although recent TSP systems began to …
reducing transit delays at signalized intersections. Although recent TSP systems began to …
A cooperative control method combining signal control and speed control for transit with connected vehicle environment
K Teng, H Liu, Q Liu, X Lu - IET Control Theory & Applications, 2024 - Wiley Online Library
Transit operation efficiency and service quality can be enhanced through the
implementation of signal and speed control. Previous studies prefer to change driving speed …
implementation of signal and speed control. Previous studies prefer to change driving speed …