Researchers are increasingly turning to roadway traffic flow theory to propose effective solutions for challenges such as traffic congestion and low efficiency in waterway transportation. However, since roadway traffic flow theory was originally deve...
Traffic in large cities is increasing due to continuous urbanization, the construction of new housing complexes and the accompanying new street network. The growth of cities creates prerequisites for increasing the intensity of transport, pedestrian,...
The fundamental relationship of traffic flow and bivariate relations between speed and flow, speed and density, and flow and density are of great importance in transportation engineering. Fundamental relationship models may be applied to assess and f...
Present experience shows that it is impossible to solve the problem of traffic congestion without intelligent transport systems. Traffic management in many cities uses the data of detectors installed at controlled intersections. Further, to assess th...
As traffic congestion in cities becomes serious, intelligent traffic signal control has been actively studied. Deep Q-Network (DQN), a representative deep reinforcement learning algorithm, is applied to various domains from fully-observable game envi...
Traffic-flow modelling has been of prime interest to traffic engineers and planners since the mid-20th century. Most traffic-flow models were developed for the purpose of characterizing homogeneous traffic flow. Some of these models are extended to c...
The paper takes an analysis of traffic conditions in a developing country, namely, India. India is a country with a rapidly growing economy and a large market, and it has the second largest population in the world, which was 1.3 billion in 2018. Indi...
Autonomous vehicles have the potential to significantly improve modes of transportation, and many businesses and research facilities are developing such systems. Although there are studies on the social implementation of autonomous vehicles, these st...
Sustainable traffic management relies on accurate traffic flow prediction to reduce congestion, fuel consumption, and emissions and minimise the external environmental impacts of traffic operations. This study contributes to this objective by develop...
Traffic speed prediction plays an important role in intelligent transportation systems, and many approaches have been proposed over recent decades. In recent years, methods using graph convolutional networks (GCNs) have been more promising, which can...
By linking computational intelligence technology directly to urban transportation systems, a framework for scheduling traffic lights is proposed to enhance their flexibility in adaptation to traffic fluctuation. First, based on the flexible neural tr...
Main roads are usually equipped with traffic flow monitoring devices in the road network to record the traffic flow data of the main roads in real time. Three complex scenarios, i.e., Y-junctions, multi-lane merging, and signalized intersections, are...
Nowadays, many cities have problems with traffic congestion at certain peak hours, which produces more pollution, noise and stress for citizens. Neural networks (NN) and machine-learning (ML) approaches are increasingly used to solve real-world probl...
Intelligent transportation has become a hot research field in recent years The development direction of road traffic construction in the future, the relevant technologies and methods in the process of gradual promotion and application of intelligent...
The advent of high-resolution minute-level traffic flow data from video surveillance on roads has opened up new opportunities for enhancing the estimation of traffic noise levels. In this study, we propose an innovative method that utilizes time seri...
Bicycle riding requires a high standard width and continuity of lanes, as an appropriate width directly improves the service level of the lanes. Therefore, the width of bicycle lanes should be designed considering the characteristics of the bicycle t...
Road surfaces are affected by rain, snow, and ice, which influence traffic flow. In this paper, a microscopic traffic flow model based on weather conditions is proposed. This model characterizes traffic based on the weather severity index. The Intell...
To fully leverage the spatiotemporal dynamic correlations in air traffic flow and enhance the accuracy of traffic flow prediction models, thereby providing a more precise basis for perceiving congestion situations in the air route network, a study wa...
This article is dedicated to the study of traffic flow forecasting at the intersection of Bogishamol Street in Tashkent, Uzbekistan. In the context of the rapid growth of vehicular traffic and frequent congestion, developing effective forecasting mod...
As the main road type in an urban traffic system, the increasingly severe congestion of the expressway restricts social and economic development. It is essential to explore the evolution law of congestion and dissipation to ensure the efficient opera...
The intersection is a bottleneck in an urban roadway network. As traffic demand increases, there is a growing congestion problem at urban intersections. Short-term traffic flow forecasting is crucial for advanced trip planning and traffic management....
The accurate and effective prediction of the traffic flow of vehicles plays a significant role in the construction and planning of signalized road intersections. The application of artificially intelligent predictive models in the prediction of the p...
Maritime traffic can reflect the diverse and complex relations between countries and regions, such as economic trade and geopolitics. Based on the AIS (Automatic Identification System) trajectory data of ships, this study constructs the Maritime Silk...
For smart cities, the issue of how to solve traffic chaos has always attracted public attention. Many studies have proposed various solutions for traffic flow prediction, such as ARIMA, ANN, and SVM. With the breakthrough of deep learning technology,...
Short-term traffic flow forecasting is the technical basis of the intelligent transportation system (ITS). Higher precision, short-term traffic flow forecasting plays an important role in alleviating road congestion and improving traffic management e...
Addressing urban traffic congestion is a pressing issue requiring efficient solutions that need to be analyzed regarding travel time and pollutant emissions. The traffic weighted multi-maps (TWM) method has been proposed as an efficient mechanism for...
In this paper, we consider a simple road intersection with traffic light control and suggest a queueing model for the traffic flow in the intersection. The suggested model implements the well-known queue with state-dependent departure rates. Using th...
Urban transport traffic surveillance is of great importance for public traffic control and personal travel path planning. Effective and efficient traffic flow prediction is helpful to optimize these real applications. The main challenge of traffic fl...
Traffic flow patterns severely impact vehicle carbon emissions. A field test was conducted in this study to obtain fuel consumption and traffic volume data under various traffic flow patterns and to explore the relationship between traffic flow patte...
This paper proposes the development of a smart traffic light prototype based on vehicular traffic flow measurement in the stretch between two avenues in the city of Limeira, SP, Brazil, focusing on the stretch towards UNICAMP’s School of Techno...
In the Taihang Mountain Tourism Development Plan (2020–2035), the Taihang Mountain Expressway is included in the construction of the National Tourism Scenic Road around Taihang Mountain to promote the integrated development of regional transpor...
In order to promote the sustainable development of urban traffic systems, improve the accuracy of traffic system analysis in the urban planning stage and reduce the possibility of traffic congestion in the operation stage of road networks, the coupli...
The prediction of traffic flow is of great significance in the traffic field. However, because of the high uncertainty and complexity of traffic data, it is challenging that doing traffic flow prediction. Most of the existing methods have achieved go...
In this work, we examine a fractal vehicular traffic flow problem. The partial differential equations describing a fractal vehicular traffic flow are solved with the aid of the local fractional homotopy perturbation Sumudu transform scheme and the lo...
Overloaded heavy vehicles (HVs) have significant negative impacts on traffic conditions due to their inferior driving performance. Highway authorities need to understand the impact of overloaded HVs to assess traffic conditions and set management str...
Recently, traffic flow prediction has gained popularity in the implementation of intelligent transportation systems. Most of the existing models for traffic flow prediction focus on increasing the prediction performance and providing fast predictions...
Vehicular traffic flow prediction for a specific day of the week in a specific time span is valuable information. Local police can use this information to preventively control the traffic in more critical areas and improve the viability by decreasing...
With the development of intelligent connected vehicles (ICVs) and communication technology, collaborative operation among vehicles will become the trend of the future. Thus, traffic flow will be mixed with manual driving vehicles and ICVs. A mixed tr...
Traditional nonintelligent signal control systems are typically used in road traffic signal systems, which cannot provide optimal guidance and have low traffic efficiency during rush hour. This study proposes a traffic signal phase dynamic timing opt...
The rapid development of Connected and Autonomous Vehicles (CAVs) presents challenges in managing mixed traffic flows. Previous studies have primarily focused on mixed traffic flow involving CAVs and Human-Driven Vehicles (HDVs), or on the combinatio...
Speed dispersion is an important indicator to portray the quality of traffic flow and is closely related to the road safety operation level. In order to clarify the influence of posted speed limits on the dispersion of traffic flow speed, three secti...
An improved cellular automata model (CA model) considering driving styles is proposed to analyze traffic flow characteristics and study traffic congestion’s dissipation mechanism. The data were taken from a particular case in the Next Generatio...
Smart cities can effectively improve the quality of urban life. Intelligent Transportation System (ITS) is an important part of smart cities. The accurate and real-time prediction of traffic flow plays an important role in ITSs. To improve the predic...
Intelligent transportation systems need to realize accurate traffic congestion prediction. The spatio-temporal features of traffic flow are essential to analyze and predict congestion. Our study proposes a data-driven model to predict the traffic con...
Traffic congestion has increased significantly in today’s rapidly urbanizing world, influencing people’s daily lives. Traffic signal control systems (TSCSs) play an important role in alleviating congestion by optimizing traffic light timi...
CO2 emissions from burning fossil fuels make a relevant contribution to atmospheric changes and climate disruptions. In cities, the contribution by traffic of CO2 is very relevant, and the general CO2 estimation can be computed (i) on the basis of th...
Analysis of traffic flow signals plays an important role in traffic prediction and management. As an intrinsic property, the singular point of a traffic flow signal labels a new nonsteady status. Therefore, detecting the singular point is an effectiv...
Since the inception of the traffic flow theory, numerous traffic flow models have been formulated by scholars in an effort to more accurately delineate the relationships between various traffic flow parameters. However, only a limited number of studi...
Traffic flow prediction is one of the most important and attractive topics in geographical information science (GIS), traffic management, and logistics. Traffic flows exhibit significant complexity and dynamics, requiring a thorough understanding of...
To improve the forecasting accuracy of traffic flow, this paper proposes a traffic flow forecasting algorithm based on Principal Component Analysis (PCA) and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for data proces...
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