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When voyage report data is utilized as the main data source for ship fuel efficiency analysis, its information on weather and sea conditions is often regarded as unreliable. To solve this issue, this study approaches AIS...

Unmanned aerial vehicles (UAVs) are increasingly crucial across various fields. There is a growing interest in using federated learning (FL) methods to enhance the efficiency of UAV operations. Nevertheless, incumbent me...

This paper considers the problem of supply-demand imbalances in Mobility-on-Demand (MoD) services. These imbalances occur due to uneven stochastic travel demand and can be mitigated by proactively rebalancing empty vehic...

With the continuous innovation in household appliance technology and the improvement of living standards, the production of discarded household appliances has rapidly increased, making their recycling increasingly signif...

Controllability is a fundamental property of control systems, serving as the prerequisite for controller design. While controllability test is well established in modelic (i.e., model-driven) control systems, extending i...

Maritime transport is the backbone of international trade and globalization. Maritime transport research can be roughly divided into two categories, namely the shipping side and the port side. Most of the classic approac...

Communication delays within connected and autonomous vehicles (CAVs) pose significant risks. It is imperative to address these issues to ensure the safe and effective operation of CAVs. However, the exploration of commun...

Although the available traffic data from navigation systems have increased steadily in recent years, it only reflects average travel time and possibly Origin-Destination information as samples, exclusively. However, the ...

The COVID pandemic has accelerated the growth of ecommerce and reshaped shopping patterns, which in turn impacts trip-making and vehicle miles traveled. The objectives of this study are to define shopping styles and quan...

Road traffic congestion has become an everyday phenomenon in today's cities all around the world. The reason is clear: at peak hours, the road network operates at full capacity. In this way, growing traffic demand cannot...

In a mixed traffic environment consisting of connected autonomous vehicles (CAVs) and human-driven vehicles (HVs), platooning intensity serves as a critical metric, quantifying the strength of CAV clustering, with inhere...

In practice, speed limits on road networks are often determined pragmatically, which can give suboptimal solutions for traffic performance and unfair results for the underlying user classes. This study presents an elegan...

The evolution of metropolitan cities and increasing travel demand impose stringent requirements on traffic assignment methods. Multi-agent reinforcement learning (MARL) approaches outperform traditional methods in modeli...

Space–time prism (STP) modeling offers a theoretical base for various person-based space–time accessibility measures. It has been challenging to construct STPs in multimodal transportation networks because of the vas...

Autonomous vehicles (AVs) are a promising emerging technology that is likely to be widely deployed in the near future. People's perception on AV safety is critical to the pace and success of deploying the AV technology. ...

Transportation networks are sized to efficiently achieve some set of service objectives. Under particular circumstances, such as the COVID-19 pandemic, the demand for transportation can significantly change, both qualita...

Road traffic crashes are among the leading causes of death and injury worldwide. While urban planning and design are known to influence road safety, it is not clear how features of the built environment contribute to tra...

In the era of emerging technologies, the transportation system is witnessing the introduction of innovative mobility services, such as autonomous vehicles, which possess unique service features that cannot be seen from c...

Car-following models (CFMs) are fundamental to traffic flow analysis and autonomous driving. Although calibrated physics-based and trained data-driven CFMs can replicate human driving behavior, their reliance on specific...

On-demand ride services or ride-sourcing services have been experiencing fast development and steadily reshaping the way people travel in the past decade. Various optimization algorithms, including reinforcement learning...

This research presents a multi-objective optimization framework for incremental siting of capacitated vertiports that integrates real land use data and aims to maximize generalized cost savings while minimizing infrastru...

This paper analyzes the day-to-day adjustment process of users’ behaviors in a transport network which is affected by relevant alterations such as disruptions due to critical events which cause the impossibility to use...

The dynamic range limitation is intrinsic to conventional RGB cameras, which reduces global contrast and causes the loss of high-frequency details such as textures and edges in complex, dynamic traffic environments (e.g....