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...
Based on comparative studies on correlation coefficient theory and utility theory, a series of rules that utility functions on dual hesitant fuzzy rough sets (DHFRSs) should satisfy, and a kind of novel utility function on DHFRSs are proposed. The ch...
With the exhaustion of IPv4 addresses, research on the adoption, deployment, and prediction of IPv6 networks becomes more and more significant. This paper analyzes the IPv6 traffic of two campus networks in Shanghai, China. We first conduct a series...
With the rapid development of positioning techniques, a large amount of human travel trajectory data is collected. These datasets have become an effective data resource for obtaining urban traffic patterns. However, many traffic analyses are only bas...
Buses, as the most commonly used public transport, play a significant role in cities. Predicting bus traffic flow cannot only build an efficient and safe transportation network but also improve the current situation of road traffic congestion, which...
The growing abundance of traffic data offers new opportunities to uncover dynamic traffic patterns in urban road networks, providing valuable insights for promoting sustainable mobility. By leveraging these data, road segments can be grouped into com...
With the increasing severity of traffic congestion, the impact of random traffic patterns has emerged as an indispensable factor in the fatigue design and assessment of highway bridges. In this study, an analytical approach has been proposed for mode...
In response to the lack of ability to handle multidimensional data in current research methods for shared bicycle travel patterns, and the fact that correlation analysis is only conducted on a single feature, this study investigates the travel patter...
Traffic anomaly detection is crucial for urban management, yet current research is often confined to small-scale endeavors. This study collected 9 months of real-time Wuhan traffic-monitoring data from Amap. We propose Traffic-ConvLSTM, a multi-scale...
Landscape patterns are closely related to ecological processes. Different spatial scales and research methods may lead to different results. Therefore, it is crucial to choose suitable research methods when studying different landscape patterns and e...
In the realm of urban vehicular ad hoc networks (VANETs), cross-domain data has constituted a multifaceted amalgamation of information sources, which significantly enhances the accuracy and response speed of traffic prediction. However, the interplay...
The spatial–temporal prediction of traffic flow is very important for traffic management and planning. The most difficult challenges of traffic flow prediction are the temporal feature extraction and the spatial correlation extraction of nodes....
Short-term traffic forecasting plays an important part in intelligent transportation systems. Spatiotemporal k-nearest neighbor models (ST-KNNs) have been widely adopted for short-term traffic forecasting in which spatiotemporal matrices are construc...
Traffic volume estimation is a fundamental task in Intelligent Transportation Systems (ITS). The highly unbalanced and asymmetric spatiotemporal distribution of traffic flow combined with the sparse and uneven deployment of sensors pose significant c...
This study investigates the spatiotemporal density aggregation and pattern distribution of vessel traffic amidst bustling maritime logistics scenarios. Firstly, a relatively new spatiotemporal segmentation and reconstruction method is proposed for sh...
Childhood obesity is associated with both near- and longer-term health implications. Few studies have been conducted to explore the associations between dietary patterns and obesity among Chinese children and adolescents. The present study was design...
Telecommuting and telelearning have gradually become mainstream lifestyles in the post-epidemic era. The extensive interconnection of massive terminals gives attackers more opportunities, which brings more significant challenges to network traffic se...
Path flow always plays a critical role in extracting vehicle travel patterns and reflecting network-scale traffic features. However, the comprehensive topological structure of urban road networks induces massive route choices, so frequent travel rout...
Accurate traffic prediction is vital for traffic management, control, and urbanization construction. Extensive research efforts have diligently focused on capturing the intricate spatio-temporal relationships that are inherent in traffic data. Howeve...
The rapid growth in the number of motor vehicles has exacerbated traffic congestion. The occurrence of congestion not only poses significant challenges for traffic management authorities but also severely impacts residents’ travel and daily rou...
15 February 2023
Prediction of traffic violations plays a key role in transportation safety. Combining with deep learning to predict traffic violations has become a new development trend. However, existing methods are based on regular spatial grids which leads to a f...
In the realm of Intelligent Transportation Systems (ITSs), traffic flow prediction is crucial for multiple applications. The primary challenge in traffic flow prediction lies in the handling and modeling of the intricate spatial–temporal correl...
Issues of missing data have become increasingly serious with the rapid increase in usage of traffic sensors. Analyses of the Beijing ring expressway have showed that up to 50% of microwave sensors pose missing values. The imputation of missing traffi...
Traffic prediction plays a significant part in creating intelligent cities such as traffic management, urban computing, and public safety. Nevertheless, the complex spatio-temporal linkages and dynamically shifting patterns make it somewhat challengi...
With the escalating global cyber threats, Distributed Denial of Service (DDoS) attacks have become one of the most disruptive and prevalent network attacks. Traditional DDoS detection systems face significant challenges due to the unpredictable natur...
30 November 2022
Taking truck drivers’ braking patterns as the research objects, this study used a large amount of truck running data. A recognition method of truck drivers’ braking patterns was proposed to determine the distribution of braking patterns d...
This study applies Transfer Entropy (TE) to floating car data from the urban road network of Catania (Italy) to investigate directional dependencies in traffic flows and identify relevant patterns of information transfer. Unlike traditional correlati...
Short-time traffic flow prediction is essential for intelligent traffic management. By accurately predicting traffic conditions in the near future, it helps to alleviate congestion, improve road efficiency, reduce accidents, and support timely traffi...
The paper presents an analysis of ship traffic using the port of Świnoujście and the problems associated with modelling vessel traffic flows. Navigation patterns were studied using the Automatic Identification System (AIS); an analysis of vessel traf...
The COVID-19 pandemic has had a substantial impact on the lives of city residents and has reshaped working patterns, with a concomitant impact on traffic accidents. We correlated data from multiple sources to explore the impact of residents’ mo...
Investigating the correlation between urban mobility patterns and the built environment is crucial to support an integrated approach to transportation and land-use planning in modern cities. In this study, we aim to conduct a data-driven analysis of...
7 May 2012
Emission of heavy metals from traffic activities is an important pollution source to roadside farmland ecosystems. However, little previous research has been conducted to investigate heavy metal concentrations of roadside farmland soil in mountainous...
The transport of information packets in complex networks is a prototype system for the study of traffic jamming, a nonlinear dynamic phenomenon that arises with increased traffic load and limited network capacity. The underlying mathematical framewor...
Metropolitan areas shoulder the crucial task of regional and even national economic development. Analyzing the spatial patterns and influencing factors of metropolitan traffic dominance can provide a scientific basis for the optimization of its trans...
Transport planning strategies regard cycling promotion as a suitable means for tackling problems connected with motorized traffic such as limited space, congestion, and pollution. However, the evidence base for optimizing cycling promotion is weak in...
With the rapid development of the global economy and trade, the number of ships serving ports in China is increasing continuously. Port traffic is becoming busier, and ship behavior is more complex and changeable. The analysis of ship behavior patter...
In this 21st century, there has been an increase in the usage of renewable products for the economic drifting of vehicle transportations systems. Furthermore, due to recent trends in climate change, researchers have started focusing on statistical op...
City-wide traffic flow forecasting is a significant function of the Intelligent Transport System (ITS), which plays an important role in city traffic management and public travel safety. However, this remains a very challenging task that is affected...
Regional comprehensive transportation infrastructures constitute the fundamental basis for the development of inland urban agglomerations. To elucidate the role of comprehensive transportation in shaping the spatial organization and expansion of urba...
The discovery of spatio-temporal dependencies within urban road networks that cause Recurrent Congestion (RC) patterns is crucial for numerous real-world applications, including urban planning and the scheduling of public transportation services. Whi...
The interaction among social economy, geography, and environment leads to the occurrence of traffic accidents, which shows the relationship between time and space. Therefore, it is necessary to study the temporal and spatial correlation and provide a...
It is crucial for both traffic management organisations and individual commuters to be able to forecast traffic flows accurately. Graph neural networks made great strides in this field owing to their exceptional capacity to capture spatial correlatio...
Urban air pollution remains a major public health concern, with road traffic representing one of the dominant sources of particulate matter and volatile organic compounds in growing cities. This study evaluates the level of chemical air pollution in...
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...
Individual mobility patterns are an important factor in urban traffic planning and traffic flow forecasting. How to understand the spatio-temporal distribution of passengers deeply and accurately, so as to provide theoretical support for the planning...
Nitrogen dioxide (NO2) is a short-lived atmospheric pollutant primarily emitted by road traffic, maritime shipping, and industrial combustion. It is a key indicator of anthropogenic air pollution due to its harmful health effects, its role in the for...
Understanding how traffic contributes to air pollution, especially in urban areas, is essential for designing effective strategies to reduce air pollution emissions. This study examines the hourly association between traffic volume and concentrations...
4 November 2022
Traffic speed prediction is an essential part of urban transportation systems that contributes to minimizing the environmental pollution caused by vehicle emissions. The existing traffic speed prediction studies have achieved good results, but some c...
The accurate forecasting of urban taxi demands, which is a hot topic in intelligent transportation research, is challenging due to the complicated spatial-temporal dependencies, the dynamic nature, and the uncertainty of traffic. To make full use of...
Traffic congestion is a critical problem in urban areas, and understanding the relationship between land use and congestion source is crucial for traffic management and urban planning. This study investigates the relationship between land-use charact...
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