In recent years, online ride-hailing services have emerged as an important component of
urban transportation system, which not only provide significant ease for residents' travel …

There has been a paradigm-shift in urban logistic services in the last years; demand for real-
time, instant mobility and delivery services grows. This poses new challenges to logistic …

Applying and adapting deep reinforcement learning (DRL) to tackle transportation problems
is an emerging interdisciplinary field. While rapidly growing, a comprehensive and synthetic …

Autonomous driving has been successfully implemented in such particular areas as logistics
distribution centers, container terminals, and university campuses. Robotaxi represents one …

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 …

Electric vehicles (EVs) are being rapidly adopted due to their economic and societal
benefits. Autonomous mobility-on-demand (AMoD) systems also embrace this trend …

In this paper, we present a comprehensive, in-depth survey of the literature on reinforcement
learning approaches to decision optimization problems in a typical ridesharing system …

In Internet of Electric Vehicles (IoEV), mobile charging stations (MCSs) can be deployed to
complement fixed charging stations. Currently, the strategy of MCSs is to move towards the …

The rebalancing of idle vehicles is critical to mitigating the supply–demand imbalance in on-
demand ride services. Motivated by a ride service platform, this paper investigates a short …

In marine container terminals, truck dispatching optimization is often considered as the
primary focus as it provides crucial synergy between the sea-side operations and yard-side …