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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...

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...

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...

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...

Striking a balance between societal benefits and costs of transportation lies at the heart of transport planning and transport systems analysis. Increased transport and urbanization enable the many benefits of modern soc...

Amid escalating global climate concerns, the reliance of the transportation sector on high-carbon fossil fuels urgently demands sustainable alternatives. Hydrogen has emerged as a potent solution because of its zero-emis...

In recent years, the resilience of road traffic during abnormal events has drawn considerable attention. Intelligent navigation systems, which proactively guide drivers along optimal routes in such situations, are viewed...

Artificial intelligence and advanced sensing technologies have significantly advanced the intelligent transportation system and autonomous vehicles. Perception, a critical component, extracts real-time traffic informatio...

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. ...

The estimation and analysis of road traffic represent the preliminary steps towards satisfying the current needs for smooth, safe, and green transportation. Therefore, effective traffic monitoring is an essential topic a...

Recent studies and industry developments indicate that modular autonomous vehicles (MAVs) have the potential to enhance transportation systems by offering vehicles with adjustable capacities en route. However, the practi...

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...

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 ...

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...

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...

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...

Ride-pooling has the potential to offer a sustainable solution for urban mobility by reducing vehicle use and emissions through shared trips. However, its adoption remains limited due to poor matching performance. Many r...

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 ...

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...

In the field of autonomous vehicles (AVs), accurately discerning commander intent and executing linguistic commands within a visual context presents a significant challenge. This paper introduces a sophisticated encoder-...

This study presents a comprehensive analysis of the relationship between congestion and lane changing, using vehicle trajectory data from the M1 motorway in Sydney. We establish a connection between the distribution of t...