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

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 …

The idea of a smart city is one that utilises Internet-of-Things (IoT) technologies and data
analytics to optimise the efficiency of city operations and services, so as to provide a high …

Rough pavements cause ride discomfort and energy inefficiency for road vehicles. Existing
methods to address these problems are time-consuming and not adaptive to changing …

In smart manufacturing, robots gradually replace traditional machines as new processing
units, which have significantly liberated laborers and reduced manufacturing expenditure …

Cloud manufacturing provides a cloud platform to offer on-demand services to complete
consumers' tasks, but assigning tasks to enterprises with different services requires many-to …

Network-based systems are at the core of our everyday life. Whether it is electronic
networking, electricity grids or transportation, users expect the networks to function properly …

Solving link-based route guidance problems for large-scale networks is computationally
challenging and faces practical issues, such as spatial–temporal data coverage. Thus …

Public transport is considered as one of the most suitable candidates to benefit from
autonomous driving technologies. In this research, we develop a mathematical modeling …

The advent of connected vehicles (CVs) provides new opportunities to address urban
parking issues due to the widespread application of online parking assignment (OPA) …