To alleviate the queue spillovers at intersections of urban roads during rush hours, a solution to the cross-spill problem based on vehicle networking technologies is proposed. This involves using connected vehicle technology, to realize the interact...
With the development of intelligent transportation system (ITS) and vehicle to X (V2X), the connected vehicle is capable of sensing a great deal of useful traffic information, such as queue length at intersections. Aiming to solve the problem of exis...
In the Intelligent Transportation System (ITS) realm, queue length estimation is one of an essential yet a challenging task. Queue lengths are important for determining traffic density in traffic lanes so that possible congestion in any lane can be m...
This paper introduces a two-stage adaptive Kalman filter algorithm to estimate and predict traffic states required for real-time traffic signal control. Leveraging probe vehicle trajectory and upstream detector data, turning movement (TM) counts in t...
Signal retiming is the most cost-efficient measure to reduce vehicle delay and alleviate congestion on urban roads. Previous studies have explored the potential of using connected vehicle data for signal retiming specifically under the current low-pe...
In smart cities, it is expected that transport, communication as well as the movement of people and goods will take place in the shortest possible time while maintaining a high level of safety. In recent years, due to the significant increase in the...
With the development of Internet of Vehicles (IoV) technology, the need for real-time data processing and communication in vehicles is increasing. Traditional request-based methods face challenges in terms of latency and bandwidth limitations. Mode 4...
Automated vehicles are expected to greatly boost traffic efficiency. However, how to estimate traffic breakdown probability for the mixed flow of autonomous vehicles and human driven vehicles around ramping areas remains to be answered. In this paper...
The Internet of Vehicles (IoV) is attracting many researchers with the emergence of autonomous or smart vehicles. Vehicles on the road are becoming smart objects equipped with lots of sensors and powerful computing and communication capabilities. In...
Real-time queue length information is an important input for many traffic applications. This paper presents a novel method for real-time queue length detection with roadside LiDAR data. Vehicles on the road were continuously tracked with the LiDAR da...
Nowadays, traffic infrastructures and vehicles are connected through the network benefiting from the development of Internet of Things (IoT). Connected automated cars can provide some useful traffic information. An architecture and algorithm of mobil...
Traffic congestion has several causes, including insufficient road capacity, unrestricted demand and improper scheduling of traffic signal phases. A great variety of efforts have been made to properly program such phases. Some of them are based on tr...
This study analyzes the performance of a queue length-dependent overload control policy using a leaky bucket (LB) scheme. This queueing model is applied to the operation of a battery swapping and charging station for electric vehicles (EVs). In addit...
Fatigue assessments of bridges depend on vehicle interactions, occurring when several vehicles travel simultaneously on the bridge or when two individual stress histories, caused by vehicles traveling in different times, generate a more damaging comb...
A pick-up zone links a hub of inter-city transportation (e.g., airplane and rail, etc.) with a connected roadway belonging to the city road network. Passengers depart through the pick-up zone and the interactions between passengers and vehicles lead...
Establishing electric vehicle supply equipment (EVSE) to keep up with the increasing number of electric vehicles (EVs) is the most realistic and direct means of promoting their spread. Using traffic data collected in one area; we estimated the EV cha...
Sufficient and convenient fast-charging facilities are crucial for the effective integration of electric vehicles. To construct enough fast electric vehicle-charging stations, station owners need to earn a reasonable profit. This paper proposed an op...
This paper presents our research on a traffic signal control system (TSCS) at V2X intersections. The overall objective of the study is to create an implementable TSCS. The specific objective of this paper is to investigate a distributed system toward...
With the government’s strong promotion of the transformation of new and old driving forces, the electrification of buses has developed rapidly. In order to improve resource utilization, many cities have decided to open bus charging stations (CS...
This study combines Visible Light Communication (VLC) and Artificial Intelligence (AI) to enhance traffic signal control, reduce congestion, and improve safety, through real-time monitoring and dynamic traffic management. Leveraging VLC technology, t...
Although electric vehicles (EVs) have been regarded as promising to reduce tailpipe emissions and energy consumption, a mixed traffic flow of EVs and internal combustion engine vehicles (ICEVs) makes the energy/emissions reduction objective more diff...
Manual traffic surveillance can be a daunting task as Traffic Management Centers operate a myriad of cameras installed over a network. Injecting some level of automation could help lighten the workload of human operators performing manual surveillanc...
This paper proposes a new approach to assessing the impact of changes in the traffic flow on pollutant emissions and the traffic capacity of signal-controlled intersections. We present an intelligent vision system tailored to monitor the traffic beha...
Today, smart cities are turning to electric transport, carpooling and zero emission zones. The growing number of electric vehicles on the roads makes it increasingly necessary to have a public charging infrastructure. On the other hand, the main limi...
Route planning for electric vehicles (EVs) is a critical challenge in sustainable transportation, as it directly addresses concerns about greenhouse gas emissions and energy efficiency. This study presents a novel approach that combines K-means clust...
The rapid increase in electric vehicle (EV) ownership necessitates the adaptation of fuel stations to charging infrastructure and the re-evaluation of capacity planning. In the literature, demand forecasting and installation costs are mostly examined...
In complex urban wireless environments, unmanned aerial vehicle–mobile edge computing (UAV-MEC) systems face challenges like link blockage and single-antenna eavesdropping threats. The traditional single reconfigurable intelligent surface (RIS)...
We propose a thread-based modeling and analysis method for a vehicle-to-everything (V2X) communication device, according to the performance requirements of the V2X application. For a developer to develop a V2X device or application, its performance r...
The demand for transportation has increased significantly in recent decades in line with the increasing demand for passenger and freight mobility, especially in urban areas. One of the most negative impacts is the increasing level of traffic congesti...
To quantify the travel time and cost characteristics of mixed traffic involving electric vehicles (EVs) and fuel-powered vehicles on roads, in this paper, we comprehensively consider three factors affecting road impedance: queue length, waiting time,...
In urban environments, the highly complex communication environment often leads to blockages in the link between ground users (GUs) and unmanned aerial vehicles (UAVs), resulting in poor communication quality. Although traditional reconfigurable inte...
Assuming a full market penetration rate of connected and autonomous vehicles (CAVs) would provide an opportunity to remove costly and inefficient traffic lights from intersections, this paper presents a signal-free intersection control system relying...
We present the ML-CALMO framework, which integrates machine learning with queueing theory for last-mile delivery optimization under dynamic conditions. The system combines Long Short-Term Memory (LSTM) demand forecasting, Convolutional Neural Network...
This study addresses the problem of non-stop passage by vehicles at intersections based on special processing of data from a road camera or video detector. The basic task in this article is formulated as a forecast for the release time of a controlle...
This study assessed the impacts of a toll information sign with different toll lane configurations on queue length and collision risk at a toll plaza with an estimated high percentage of heavy vehicles (HVs). The toll information sign displays inform...
Automated guided vehicles (AGVs) stand out as a paradigmatic application of Industry 4.0, requiring the seamless integration of new concepts and technologies to enhance productivity while reducing labor costs, energy consumption, and emissions. In th...
The real-time vehicular traffic system is an integral part of the urban vehicular traffic system, which provides effective traffic signal control for a large multifaceted traffic network and is a highly challenging distributed control problem. Coordi...
With the continuous advancements in electrification, connectivity, and intelligence in the automotive industry, the mixed traffic of vehicles with different levels of driving automation is changing the carbon emission characteristics in the impact ar...
Efficient toll processing is critical for mitigating traffic congestion and enhancing transportation network efficiency at toll stations. This study explores the Neelamangala Toll Plaza on India’s National Highway 48, employing artificial intelligenc...
With the large-scale adoption of electric vehicles (EVs) on expressways, the exploration of a guiding-based charging method to effectively adjust interactions between EVs and the fast charging stations (CSs) is urgently needed. This paper proposes a...
How to sustainably conduct intersection operations is a key issue of the current research. For an actuated control intersection, queued vehicles, control parameters, and phase schemes all affect the operation effect. This paper discusses queued vehic...
The deployment of electric trucks is recognized as a crucial tool for reducing dependence on traditional fossil fuels and mitigating pollution from transportation systems. However, insufficient and unbalanced distribution of charging stations may hin...
The mathematical study known as queueing theory has recently become a major point of interest for many government agencies and private companies for increasing efficiency. One such application is vehicle queueing at an international port-of-entry (PO...
Signal intersections are key nodes in urban road traffic networks, and real-time queue length information serves as a core performance indicator for formulating effective signal management schemes in modern adaptive traffic signal control systems, th...
Due to the increasing use of private cars for urbanization and urban transport, the travel time of urban transportation is increasing. People spend a lot of time in the streets, and the queue length of waiting increases accordingly; this has direct e...
In Cooperative Vehicle Infrastructure System (CVIS), the roadside unit (RSU) obtains many kinds of monitoring data through observation equipment carried by the RSU. The monitoring data from RSUs are transmitted to an RSU that is connected to the back...
In the lane-based signal optimization model, permitted turn directions in the form of lane markings that guide road users to turn at an intersection are optimized with traffic signal settings. The spatial queue requirements of approach lanes should b...
Oversaturation of highways occurs due to their inadequate assessment and design. In this paper, we propose both a mathematical queuing model and a Discrete-Event Simulation (DES) framework based on Newell’s triangular flow-density relationship...
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...
Coordinated adaptive signal control is a proven strategy for improving traffic efficiency and minimizing vehicular delays. First, we develop a Queue Evolution and Delay Model (QEDM) that establishes the relationship between detector-measured queue le...
of 6