Buscar recursos académicos

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...

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...

Human driven vehicles (HDVs) with selfish objectives cause low traffic efficiency in an un-signalized intersection. On the other hand, autonomous vehicles can overcome this inefficiency through perfect coordination. In t...

Cross-city transfer learning (CCTL) has emerged as a crucial approach for managing the growing complexity of urban data and addressing the challenges posed by rapid urbanization. This paper provides a comprehensive revie...

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...

In recent years, the advancement of artificial intelligence techniques has led to significant interest in reinforcement learning (RL) within the traffic and transportation community. Dynamic traffic control has emerged a...

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...

High-granularity vehicle trajectory data can help researchers develop traffic simulation models, understand traffic flow characteristics, and thus propose insightful strategies for road traffic management. This paper pro...

While physics models for predicting system states can reveal fundamental insights owing to their parsimonious structure, they may not always yield the most accurate predictions, particularly for complex systems. As an al...

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...

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...

Solving optimal control problems serves as the basic demand of industrial control tasks. Existing methods like model predictive control often suffer from heavy online computational burdens. Reinforcement learning has sho...

Mandatory lane changes (MLCs) pose significant challenges to trajectory planning at intersections, where vehicles are required to change lanes mid-block to reach designated turn lanes before the stop bar. MLCs often gene...

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...

Trajectory reconstruction from sparse and noisy GPS data is critical for applications such as urban mobility analysis, transportation planning, and navigation systems. However, large sampling intervals and the typically ...

Video-based road intelligent detection constitutes a critical component in modern intelligent transportation systems, serving as a crucial role for comprehensive transportation planning and emergency traffic management. ...

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...

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...

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....

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...