Related papers: Smart City Intelligent System Traffic Congestion O…
In this paper we study the routing and rebalancing problem for a fleet of autonomous vehicles providing on-demand transportation within a congested urban road network (that is, a road network where traffic speed depends on vehicle density).…
Intelligent Transportation Systems (ITS) use data and information technology to improve the operation of our transportation network. ITS contributes to sustainable development by using technology to make the transportation system more…
Despite the promising benefits that ride-sharing offers, there has been a lack of research on the benefits of high-capacity ride-sharing services. Prior research has also overlooked the relationship between traffic volume and the degree of…
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.…
The rapid urbanization and increasing traffic have serious social, economic, and environmental impact on metropolitan areas worldwide. It is of a great importance to understand the complex interplay of road networks and traffic conditions.…
We show that the capacity of a complex network that models a city street grid to support congested traffic can be optimized by using routes that collectively minimize the maximum ratio of betweenness to capacity in any link. Networks with a…
This paper offers a finite-state abstraction of traffic coordination and congestion in a network of interconnected roads (NOIR). By applying mass conservation, we model traffic coordination as a Markov process. Model Predictive Control…
In many "smart city" applications, congestion arises in part due to the nature of signals received by individuals from a central authority. In the model of Marecek et al. [arXiv:1406.7639, Int. J. Control 88(10), 2015], each agent uses one…
Traffic congestion has become one of the most critical issues worldwide. The costs due to traffic gridlock and jams are approximately $160 billion in the United States, more than {\pounds}13 billion in the United Kingdom, and over one…
There has been a lot of discussion on Net Neutrality and policies that various network service providers and distributors adopt, at times leading to greater network congestion and thus more debates. The aim of this project is to use…
Traffic is essential for many dynamic processes on real networks, such as internet and urban traffic systems. The transport efficiency of the traffic system can be improved by taking full advantage of the resources in the system. In this…
Vehicle-to-everything (V2X) networks support a variety of safety, entertainment, and commercial applications. This is realized by applying the principles of the Internet of Vehicles (IoV) to facilitate connectivity among vehicles and…
To address the challenge of conflicting traffic flows that complete on opposing cycle times in a specific phase of the traffic light, we proposed a novel decentralized traffic light control methodology based on the identification of the…
The way of analyzing, designing and building of real-time projects has been changed due to the rapid growth of internet, mobile technologies and intelligent applications. Most of these applications are intelligent, tiny and distributed…
How to build an effective large-scale traffic state prediction system is a challenging but highly valuable problem. This study focuses on the construction of an effective solution designed for spatio-temporal data to predict large-scale…
The optimal information feedback has a significant effect on many socioeconomic systems like stock market and traffic systems aiming to make full use of resources. In this paper, we studied dynamics of traffic flow with real-time…
Ill-managed intersections are the primary reasons behind the increasing traffic problem in urban areas, leading to nonoptimal traffic-flow and unnecessary deadlocks. In this paper, we propose an automated intersection management system that…
Traffic congestion research is on the rise, thanks to urbanization, economic growth, and industrialization. Developed countries invest a lot of research money in collecting traffic data using Radio Frequency Identification (RFID), loop…
Simple physical models based on fluid mechanics have long been used to understand the flow of vehicular traffic on freeways; analytically tractable models of flow on an urban grid, however, have not been as extensively explored. In an ideal…
Traffic congestion is a complex, nonlinear spatiotemporal modeling problem. By collecting and analyzing a vast quantity and different categories of information, traffic flow, and road congestion can be predicted and controlled on an…