A bi-level model for traffic signal optimization is developed. The model predictive framework is applied for traffic control in an urban traffic network. The potential of the bi-level formalization is used to increase the space of control influences...
Vehicular transportation is one of the most widely used modes in modern cities for reaching key destinations such as workplaces, healthcare facilities, recreational areas, and educational institutions, among others. However, the performance of vehicu...
Urban infrastructure systems, such as water supply and transportation networks, are highly interdependent, making them susceptible to cascading disruptions. This paper introduces a bi-level optimization framework designed to coordinate water supply n...
As a product of urban motorized traffic, sharing roads between pedestrians and non-motor vehicles has been widely used in the world. In order to improve the service quality of slow traffic, it is necessary to evaluate the service level of the shared-...
To address the challenges of facility–demand mismatch, aggravated congestion, and imbalanced benefit distribution caused by the interdependence between dynamic wireless charging systems (DWCS) and transportation networks, this study proposes an...
Region-level traffic information can characterize dynamic changes of urban traffic at the macro level. Real-time region-level traffic prediction help city traffic managers with traffic demand analysis, traffic congestion control, and other activities...
Over recent decades, roundabouts have become increasingly used when building new at-grade intersections or up-grade junctions all over the world. Consequently, control of traffic flows at at-grade intersections and up-grade junctions using roundabout...
With the continuous development of smart cities, intelligent transportation systems (ITSs) have ushered in many breakthroughs and upgrades. As a solid foundation for an ITS, traffic flow prediction effectively helps the city to better manage intricat...
Level 3 automated driving systems could introduce challenges to traffic systems as they require a specific lead time in their procedures to ensure the safe return of vehicle control to the driver. These processes, called ’transitions of control...
In the field of macro-level safety studies, road traffic safety is significantly related to socioeconomic factors, such as population, number of vehicles, and Gross Domestic Product (GDP). Due to different levels of economic and urbanization, the inf...
Traffic situation awareness and alerting assisted by adverse weather conditions contributes to improve traffic safety, disaster coping mechanisms, and route planning for government agencies, business sectors, and individual travelers. However, at the...
Peer-to-peer (P2P) applications have been popular among users for more than a decade. They consume a lot of network bandwidth, due to the fact that network administrators face several issues such as congestion, security, managing resources, etc. Henc...
Irregular and non-cyclical railway level-crossing closures generate traffic disruptions that cannot be directly assessed using standard intersection analysis methods. Railway level crossings interrupt road traffic in irregular, non-cyclical intervals...
Bluetooth monitoring systems (BTMS) have opened a new era in traffic sensing, providing a reliable, economical, and easy-to-deploy solution to uniquely identify vehicles. Raw data from BTMS have traditionally been used to calculate travel time and or...
To ensure the equity of exclusive bus lane (EBL) allocation under multimodal traffic conditions, a bi-level programming model is first constructed. The upper-level model is the minimum total system cost considering the Gini coefficient and the lower-...
This study investigates the various factors contributing to the severity of traffic collisions, with specific attention given to elements such as the involvement of pedestrians and cyclists, the roles played by motor vehicles, prevailing weather cond...
Connected and Autonomous Vehicles (CAVs) are expected to reshape future transportation systems. During the long transition period, in which CAVs and human-driven vehicles (HVs) coexist, deploying CAV-dedicated lanes offers a promising approach to enh...
Motor vehicle headlamps are the only light sources that create visibility conditions for the driver in nighttime non-urban traffic. Therefore, a suitable design of these lighting systems is of the highest relevance to allow the driver an early detect...
With the increasing complexity of transportation systems, traditional qualitative descriptions fail to objectively reflect the level of autonomy in traffic signal control systems—especially the lack of a systematic evaluation framework that lin...
This study delves into the intricate dynamics of urban mobility, a pivotal aspect for policymakers, businesses, and communities alike. By deciphering patterns of movement within a city, stakeholders can craft targeted interventions to mitigate traffi...
This study presents a machine learning framework for predicting traffic accident occurrence and congestion intensity using artificial neural networks (ANNs) trained on real-world traffic data collected from a central urban corridor in Egypt. The rese...
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...
Traffic noise is a major pollution problem in Hong Kong and many large cities throughout the world. Indeed, traffic noise and traffic flow patterns interact, however, there is a very little research effort studying it. To the best knowledge of the au...
Pedestrian safety in school zones is shaped by traffic conditions and street design characteristics, whose combined effects involve uncertainty and gradual transitions rather than sharp thresholds. This study presents an integrated assessment framewo...
The negative external effects caused by traffic growth have been recognized as the main factors that degrade city quality of life. Therefore, research around the world is being conducted to understand the impact of traffic better and find adequate me...
Road infrastructure has an impact on the occurrence of road traffic crashes. The aim of this study was to analyze the impact of road geometric formation on road traffic crashes. Based on the nature, convenience, and availability of data, the study us...
This paper proposes a neural network that fuses the data received from a camera system on a gantry to detect moving objects and calculate the relative position and velocity of the vehicles traveling on a freeway. This information is used to estimate...
Accurate evaluation of the prevailing traffic operations plays an important part in developing sustainable transport systems. This research examines the suitability of the level of service (LOS) criteria developed by the Indian and United States (US)...
The purpose of this work is to determine the influence of the low beam intensity of motor vehicle headlights on detection conditions in urban traffic. For this purpose, studies with fourteen subjects are conducted on three differently illuminated tes...
Recently, deep learning has been successfully applied to network security assessments and intrusion detection systems (IDSs) with various breakthroughs such as using Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) to classify ma...
Recently, the issue of sound quality inside vehicles has attracted interest from both researchers and industry alike due to health concerns and also to increase the appeal of vehicles to consumers. This work extends the analysis of interior acoustic...
This study applied 2019 macro-level data from DATASUS to model traffic fatalities at the scene. Ordinary least squares (OLS) and censored regression models (TOBIT) were the methodologies used to identify the significant variables explaining the occur...
28 July 2021
This study aimed to investigate the association between traffic-related air pollution (TRAP) exposure and histone H3 modification among school children in high-traffic (HT) and low-traffic (LT) areas in Malaysia. Respondents’ background information a...
Due to the escalating transportation demand and the significant ramifications of traffic congestion, there is an imperative to investigate the sources of congestion, known as “congestion bottlenecks”. The implementation of control methods...
Traffic accidents occur frequently, causing significant losses to people’s lives and property safety. Accurately predicting the severity level of traffic accidents is of great significance. Based on traffic accident data, this study comprehensi...
Typically, the production data centers function with various risk factors, such as for instance the network dynamicity, topological asymmetry, and switch failures. Hence, the load-balancing schemes should consider the sensing accurate path circumstan...
Buses constitute a crucial component of public transportation systems in numerous urban centers. Integrating autonomous driving technology into the bus transportation ecosystem has the potential to enhance overall urban mobility. The management of mi...
31 July 2022
According to recent research, the COVID-19 pandemic has impacted road traffic quality. This study aims to analyze the impacts of COVID-19 travel restriction policies on the traffic quality of the national and provincial trunk highway network (NPTHN)...
In the era of “carbon dioxide peaking and carbon neutrality”, low-carbon development of road traffic and transportation has now become a rigid demand in China. Considering the fact that socioeconomic and demographic characteristics vary s...
Encrypted traffic classification is crucial for network security and management, enabling applications like QoS control and malware detection. However, the emergence of new encryption protocols, particularly TLS 1.3, poses challenges for traditional...
Road transport is a major source of urban carbon emissions. Numerous studies have investigated the factors influencing road traffic emissions. However, the nonlinear relationships between carbon emissions and their determinants have yet to be fully q...
With the steadily growing of global transportation market, the traffic load has increased dramatically over the past decades, which may develop into a risk source for existing bridges. The simultaneous presence of heavy trucks that are random in natu...
The present article contains a microsimulation analysis of the impact of the number of pedestrians on pedestrian crossings controlled by traffic lights. To analyze the level of freedom of movement using the HCM 2010 method based on the level of servi...
In urban areas, noise levels can largely vary in space and time due to the great complexity of these environments. The time required for the fluctuations of the running equivalent level LAeq to be limited within a preset variability range is a key is...
Measuring the traffic quality and congestion level is fundamental in highway engineering, and several decades of studies and research have pursued this specific objective, especially for freeways. Nowadays, smart technologies on personal devices and...
Although road horizontal curves are high-risk sections for accidents, current road safety assessments often neglect the dynamic evolution of superelevation and the friction factor. The connotation for road safety level was clarified by examining the...
Mobile traffic prediction enables the efficient utilization of network resources and enhances user experience. In this paper, we propose a state transition graph-based spatial–temporal attention network (STG-STAN) for cell-level mobile traffic...
Accurate prediction of road traffic crash severity is essential for developing data-driven safety strategies and optimizing resource allocation. This study presents a predictive modeling framework that utilizes Random Forest (RF), Gradient Boosting (...
The deployment of intelligent transportation systems (ITS) in emerging urban areas faces significant challenges due to the scarcity of historical data. Knowledge transfer across cities has shown exciting potential in addressing this issue, yet existi...
Due to the expansion of Artificial Intelligence (AI), especially Machine Learning (ML), it is more common to face confidentiality regulations about using sensitive data in learning models generally hosted in cloud environments. Confidentiality regula...
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