Exploiting battery storages with reinforcement learning: a review for energy professionals
The transition to renewable production and smart grids is driving a massive investment to
battery storages, and reinforcement learning (RL) has recently emerged as a potentially …
battery storages, and reinforcement learning (RL) has recently emerged as a potentially …
A bibliometric analysis and review on reinforcement learning for transportation applications
Transportation is the backbone of the economy and urban development. Improving the
efficiency, sustainability, resilience, and intelligence of transportation systems is critical and …
efficiency, sustainability, resilience, and intelligence of transportation systems is critical and …
Deep reinforcement learning for the dynamic and uncertain vehicle routing problem
W Pan, SQ Liu - Applied Intelligence, 2023 - Springer
Accurate and real-time tracking for real-world urban logistics has become a popular
research topic in the field of intelligent transportation. While the routing of urban logistic …
research topic in the field of intelligent transportation. While the routing of urban logistic …
Online parking assignment in an environment of partially connected vehicles: A multi-agent deep reinforcement learning approach
The advent of connected vehicles (CVs) provides new opportunities to address urban
parking issues due to the widespread application of online parking assignment (OPA) …
parking issues due to the widespread application of online parking assignment (OPA) …
Coordinating ride-sourcing and public transport services with a reinforcement learning approach
Combining ride-sourcing and public transit services (with ride-sourcing service to address
the first/last-mile issues) can bring many benefits, such as saving passengers' trip fares …
the first/last-mile issues) can bring many benefits, such as saving passengers' trip fares …
Coordinating matching, rebalancing and charging of electric ride-hailing fleet under hybrid requests
Due to the potential to reduce energy consumption and greenhouse gas emission, electric
vehicles have been widely adopted in ride-hailing services Besides the frequently …
vehicles have been widely adopted in ride-hailing services Besides the frequently …
Dynamic operations of an integrated mobility service system of fixed-route transits and flexible electric buses
As an emerging mobility service with a wide range of benefits, flexible buses balance
monetary costs, travel time, and comfort, and have evolved into a powerful supplement to …
monetary costs, travel time, and comfort, and have evolved into a powerful supplement to …
Two-sided deep reinforcement learning for dynamic mobility-on-demand management with mixed autonomy
Autonomous vehicles (AVs) are expected to operate on mobility-on-demand (MoD)
platforms because AV technology enables flexible self-relocation and system-optimal …
platforms because AV technology enables flexible self-relocation and system-optimal …
A robust deep reinforcement learning approach to driverless taxi dispatching under uncertain demand
With the progressive technological advancement of autonomous vehicles, taxi service
providers are expected to offer driverless taxi systems that alleviate traffic congestion and …
providers are expected to offer driverless taxi systems that alleviate traffic congestion and …
Vehicle dispatching and routing of on-demand intercity ride-pooling services: A multi-agent hierarchical reinforcement learning approach
The integrated development of city clusters has given rise to an increasing demand for
intercity travel. Intercity ride-pooling service exhibits considerable potential in upgrading …
intercity travel. Intercity ride-pooling service exhibits considerable potential in upgrading …