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Cities have undergone significant changes due to the rapid increase in urban population, heightened demand for resources, and growing concerns over climate change. To address these challenges, digital transformation has become a necessity.…
This paper implements a traffic signal control system by using real-time traffic flow feedback. This system is designed to deal with two-lane intersections. We construct an experiment field similar to the roads and drivers in Taiwan using…
This paper devotes to the development of an optimal acceleration/speed profile for autonomous vehicles approaching a traffic light. The design objective is to achieve both short travel time and low energy consumption as well as avoid idling…
Traffic signal control (TSC) is a high-stakes domain that is growing in importance as traffic volume grows globally. An increasing number of works are applying reinforcement learning (RL) to TSC; RL can draw on an abundance of traffic data…
The emergence of reinforcement learning (RL) methods in traffic signal control tasks has achieved better performance than conventional rule-based approaches. Most RL approaches require the observation of the environment for the agent to…
Traffic congestion is becoming a challenge in the rapidly growing urban cities, resulting in increasing delays and inefficiencies within urban transportation systems. To address this issue a comprehensive methodology is designed to optimize…
We present methods and applications for the development of digital twins (DT) for urban traffic management. While the majority of studies on the DT focus on its ``eyes," which is the emerging sensing and perception like object detection and…
This paper presents a new approach to congestion management at traffic-light intersections. The approach is based on controlling the relative lengths of red/green cycles in order to have the congestion level track a given reference. It uses…
While measures, such as traffic calming and advance driver assistance systems, can improve safety for Vulnerable Road Users (VRUs), their effectiveness ultimately relies on the responsible behavior of drivers and pedestrians who must adhere…
Recent studies on transportation networks have shown that real-time route guidance can inadvertently induce congestion or oscillatory traffic patterns. Nevertheless, such technologies also offer a promising opportunity to manage traffic…
Reinforcement learning (RL) constitutes a promising solution for alleviating the problem of traffic congestion. In particular, deep RL algorithms have been shown to produce adaptive traffic signal controllers that outperform conventional…
Many studies confirmed that a proper traffic state representation is more important than complex algorithms for the classical traffic signal control (TSC) problem. In this paper, we (1) present a novel, flexible and efficient method, namely…
Traffic congestion has become a nightmare to modern life in metropolitan cities. On average, a driver spending X hours a year stuck in traffic is one of most common sentences we often read regarding traffic congestion. Our aim in this…
Steering traffic in cities is a very complex task, since improving efficiency involves the coordination of many actors. Traditional approaches attempt to optimize traffic lights for a particular density and configuration of traffic. The…
With the era of big data, an explosive amount of information is now available. This enormous increase of Big Data in both academia and industry requires large-scale data processing systems. A large body of research is behind optimizing…
Traffic congestion is a persistent problem in urban areas, which calls for the development of effective traffic signal control (TSC) systems. While existing Reinforcement Learning (RL)-based methods have shown promising performance in…
Advancements in Intelligent Traffic Systems (ITS) have made huge amounts of traffic data available through automatic data collection. A big part of this data is stored as trajectories of moving vehicles and road users. Automatic analysis of…
Security of Intelligent Transportation Systems (ITS) heavily depends on the security of the underlying components that create such a smart ecosystem. Adaptive Cruise Control (ACC) is embedded into most modern vehicles. In this report, we…
Leveraging the accuracy and consistency of vehicle motion control enabled by the connected and automated vehicle technology, we propose the rhythmic control (RC) scheme that allows vehicles to pass through an intersection in a conflict-free…
The measurement and provision of precise and upto-date traffic-related key performance indicators is a key element and crucial factor for intelligent traffic controls systems in upcoming smart cities. The street network is considered as a…