This paper investigates the impacts of a bus holding strategy on the mutual interference between buses and passenger cars in a non-dedicated bus route,as well as the impacts on the characteristics of pollutant emissio...This paper investigates the impacts of a bus holding strategy on the mutual interference between buses and passenger cars in a non-dedicated bus route,as well as the impacts on the characteristics of pollutant emissions of passenger cars.The dynamic behaviors of these two types of vehicles are described using cellular automata(CA)models under open boundary conditions.Numerical simulations are carried out to obtain the phase diagrams of the bus system and the trajectories of buses and passenger cars before and after the implementation of the bus holding strategy under different probabilities of passenger cars entering a two-lane mixed traffic system.Then,we analyze the flow rate,satisfaction rate,and pollutant emission rates of passenger cars together with the performance of a mixed traffic system.The results show that the bus holding strategy can effectively alleviate bus bunching,whereas it has no significant impact on the flow rate and pollutant emission rates of passenger cars;the flow rate,satisfaction rate,and pollutant emission rates of passenger cars for either the traffic system or for each lane are influenced by the bus departure interval and the number of passengers arriving at bus stops.展开更多
The slow traffic system is an important component of urban transportation,and the prerequisite and necessary condition for Beijing to continue promoting“green priority”are establishing a good urban slow traffic syst...The slow traffic system is an important component of urban transportation,and the prerequisite and necessary condition for Beijing to continue promoting“green priority”are establishing a good urban slow traffic system.Shijingshan District of Beijing City is taken as a research object.By analyzing and processing population distribution data,POI data,and shared bicycle data,the shortcomings and deficiencies of the current slow traffic system in Shijingshan District are explored,and corresponding solutions are proposed,in order to provide new ideas and methods for future urban planning from the perspective of data.展开更多
At present,problems such as insufficient road infrastructure and supporting facilities,and limited parking spaces are increasingly prevalent,and there are large conflicts of interest in the process of urban renewal.Th...At present,problems such as insufficient road infrastructure and supporting facilities,and limited parking spaces are increasingly prevalent,and there are large conflicts of interest in the process of urban renewal.Therefore,it is crucial to improve the quality of the road network.This paper presents an analysis on the current situation of the road traffic system in a completed area outside the Third Ring Road in Xindu District,Chengdu,and provides corresponding road traffic optimization strategies,with aims of solving the existing road traffic problems,improve road service levels,and promote the overall development of the area and improve the quality of urban space.展开更多
Due to excessive car usage,pollution and traffic have increased.In urban cities in Saudi Arabia,such as Riyadh and Jeddah,drivers and air quality suffer from traffic congestion.Although the government has implemented ...Due to excessive car usage,pollution and traffic have increased.In urban cities in Saudi Arabia,such as Riyadh and Jeddah,drivers and air quality suffer from traffic congestion.Although the government has implemented numerous solutions to resolve this issue or reduce its effect on the environment and residents,it still exists and is getting worse.This paper proposes an intelligent,adaptive,practical,and feasible deep learning method for intelligent traffic control.It uses an Internet of Things(IoT)sensor,a camera,and a Convolutional Neural Network(CNN)tool to control traffic in real time.An image segmentation algorithm analyzes inputs from the cameras installed in designated areas.This study considered whether CNNs and IoT technologies could ensure smooth traffic flow in high-speed,high-congestion situations.The presented algorithm calculates traffic density and cars’speeds to determine which lane gets high priority first.A real case study has been conducted on MATLAB to verify and validate the results of this approach.This algorithm estimates the reduced average waiting time during the red light and the suggested time for the green and red lights.An assessment between some literature works and the presented algorithm is also provided.In contrast to traditional traffic management methods,this intelligent and adaptive algorithm reduces traffic congestion,automobile waiting times,and accidents.展开更多
It has been long believed there should be some relations between traffic system and urbanization,but the in-teraction between them,especially on the regional level,has been not in consideration due to the difficulty i...It has been long believed there should be some relations between traffic system and urbanization,but the in-teraction between them,especially on the regional level,has been not in consideration due to the difficulty in quantitative analysis.Based on the development of Jilin Province during 1981-2003,the paper analyzed the relation with the grey-relation model which was adjusted to fit specific problem,and came to some conclusions.Firstly,there exists ob-vious and strong correlation between traffic system and urbanization.Secondly,urbanization responds to the develop-ment of traffic system mainly on the level of urbanization,such as population and developed area,however,less on urbanization quality.Thirdly,traffic system influences urbanization as a whole except for several peculiar factors,which means we should optimize the whole traffic system to promote urbanization.Based on those conclusions,the paper illustrated the mechanism of traffic system,promoting urbanization scale and urbanization quality.展开更多
In order to give a new way for modeling driving behavior, identifying road traffic accident causation and solving a variety of road traffic safety problems such as driving errors prevention and driving behavior analys...In order to give a new way for modeling driving behavior, identifying road traffic accident causation and solving a variety of road traffic safety problems such as driving errors prevention and driving behavior analysis, a new driving behavior shaping model is proposed, which could be used to assess the degree of effect of driving error upon road traffic safety. Driver behavior shaping model based on driving reliability and safety analysis could be used to identify the road traffic accident causation, to supply data for driver's behavior training, to evaluate driving procedures, to human factor design of road traffic system.展开更多
Chaotic characteristics of traffic flow time series is analyzed to further investigate nonlinear characteristics of air traffic system.Phase space is reconstructed both by time delay which is built through mutual info...Chaotic characteristics of traffic flow time series is analyzed to further investigate nonlinear characteristics of air traffic system.Phase space is reconstructed both by time delay which is built through mutual information,and by embedding dimension which is based on false nearest neighbors method.In order to analyze chaotic characteristics of time series,correlation dimensions and the largest Lyapunov exponents are calculated through Grassberger-Procaccia(G-P)algorithm and small-data method.Five-day radar data from the control center in Guangzhou area are analyzed and the results show that saturated correlation dimensions with self-similar structures exist in time series,and the largest Lyapunov exponents are all equal to zero and not sensitive to initial conditions.Air traffic system is affected by multiple factors,containing inherent randomness,which lead to chaos.Only grasping chaotic characteristics can air traffic be predicted and controlled accurately.展开更多
Information feedback strategies can influence the traffic efficiency of intelligent traffic systems greatly.Based on the more practical symmetrical two-route scenario with one entrance and one exit,an improved weighte...Information feedback strategies can influence the traffic efficiency of intelligent traffic systems greatly.Based on the more practical symmetrical two-route scenario with one entrance and one exit,an improved weighted mean velocity feedback strategy（WMVFS） is proposed,which is not sensitive to the precision of global position system（GPS） devices.The applicability of WMVFS to different weight factors,aggressive probabilities,densities of dynamic vehicles,and different two-route scenarios（symmetrical scenario and asymmetrical scenario with a speed limit bottleneck） is analyzed.Results show that WMVFS achieves the best performance compared with three other information feedback strategies when considering the traffic flux and stability.展开更多
In this paper, we study the dynamics of the synchronous totally asymmetric simple exclusion process （TASEP） on lattices with two consecutive junctions in a multiple-input-multiple-output （MIMO） traffic system, whi...In this paper, we study the dynamics of the synchronous totally asymmetric simple exclusion process （TASEP） on lattices with two consecutive junctions in a multiple-input-multiple-output （MIMO） traffic system, which consists of m sub-chains for the input and the output, respectively. In the middle of the system, there are n （n 〈 m） sub-chains via two consecutive junctions linking m sub-chains of input and m sub-chains of output, respectively. This configuration is a type of complex geometry that is relevant to many biological processes as well as to vehicular traffic flow. We use a mean-field approach to calculate this typical geometry and obtain the theoretical results for stationary particle currents, density profiles, and a phase diagram. With the values of m and n synchronously increasing, the vertical phase boundary moves toward the right and the horizontal phase boundary moves toward the upside in the phase diagram. The boundary conditions of the system as well as the numbers of input and output determine the no-equilibrium stationary states, stationary-states phases, and phase boundaries. We use the results to compare with computer simulations and find that they are in very good agreement with each other.展开更多
In this work, we propose a new model of evolution networks, which is based on the evolution of the traffic flow. In our method, the network growth does not take into account preferential attachment, and the attachment...In this work, we propose a new model of evolution networks, which is based on the evolution of the traffic flow. In our method, the network growth does not take into account preferential attachment, and the attachment of new node is independent of the degree of nodes. Our aim is that employing the theory of evolution network, we give a further understanding about the dynamical evolution of the traffic flow. We investigate the probability distributions and scaling properties of the proposed model The simulation results indicate that in the proposed model, the distribution of the output connections can be well described by scale-free distribution. Moreover, the distribution of the connections is largely related to the traffic flow states, such as the exponential distribution （i.e., the scale-free distribution） and random distribution etc.展开更多
Based on combing of urban integrated traffic planning report in Ganzhou City and its contrastive study with revised traffic model of general planning,it is found that there is great difference between integrated traff...Based on combing of urban integrated traffic planning report in Ganzhou City and its contrastive study with revised traffic model of general planning,it is found that there is great difference between integrated traffic planning and its actual development in medium-sized cities.Combining new process of reform and opening-up in the past 40 years,the development of urban integrated planning is looked ahead and explored.展开更多
The measurements on actual traffic have revealed the existence of meta-stable states with high flow. Such nonlinear phenomena have not been observed in the classic Nagel-Schreckenberg traffic flow model. Here we just ...The measurements on actual traffic have revealed the existence of meta-stable states with high flow. Such nonlinear phenomena have not been observed in the classic Nagel-Schreckenberg traffic flow model. Here we just add a constraint to the classic model by introducing a velocity-dependent randomization. Two typical randomization strategies are adopted in this paper. It is shown that the Matthew effect is a necessary condition to induce traffic meta-stable states, thus shedding a light on the prerequisites for the emergence of hysteresis loop in the fundamental diagrams.展开更多
With increasing of serious environment problems and the coming of the aging society, new traffic systems should be urgently rebuilt. It is necessary to evaluate the traffic service level by utilizing new technique and...With increasing of serious environment problems and the coming of the aging society, new traffic systems should be urgently rebuilt. It is necessary to evaluate the traffic service level by utilizing new technique and tool. This paper takes Kitakyushu city as case study to carry out an evaluation of urban traffic system. The concept of accessibility and mobility is used to evaluate the present condition of existing public traffic system based on GIS technology, and then establishment of new route is discussed according to the evaluation results. Additionally, this paper established GIS database and illustrated the relationship between the public traffic and population density. The regions without enough existing traffic were identified. Moreover, the essential terms and considerations were put forward to simulate a new route of public traffic line.展开更多
Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation systems.Traditional approaches require traffic signal ...Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation systems.Traditional approaches require traffic signal professionals to manually intervene on traffic control devices at the intersection level,utilizing their knowledge and expertise.However,this process is cumbersome,labor-intensive,and cannot be applied on a large network scale.Recent studies have begun to explore the applicability of recommendation system for urban traffic control,which offer increased control efficiency and scalability.Such a decision recommendation system is complex,with various interdependent components,but a systematic literature review has not yet been conducted.In this work,we present an up-to-date survey that elucidates all the detailed components of a recommendation system for urban traffic control,demonstrates the utility and efficacy of such a system in the real world using data and knowledgedriven approaches,and discusses the current challenges and potential future directions of this field.展开更多
In the rapidly evolving field of cybersecurity,the challenge of providing realistic exercise scenarios that accurately mimic real-world threats has become increasingly critical.Traditional methods often fall short in ...In the rapidly evolving field of cybersecurity,the challenge of providing realistic exercise scenarios that accurately mimic real-world threats has become increasingly critical.Traditional methods often fall short in capturing the dynamic and complex nature of modern cyber threats.To address this gap,we propose a comprehensive framework designed to create authentic network environments tailored for cybersecurity exercise systems.Our framework leverages advanced simulation techniques to generate scenarios that mirror actual network conditions faced by professionals in the field.The cornerstone of our approach is the use of a conditional tabular generative adversarial network(CTGAN),a sophisticated tool that synthesizes realistic synthetic network traffic by learning fromreal data patterns.This technology allows us to handle technical components and sensitive information with high fidelity,ensuring that the synthetic data maintains statistical characteristics similar to those observed in real network environments.By meticulously analyzing the data collected from various network layers and translating these into structured tabular formats,our framework can generate network traffic that closely resembles that found in actual scenarios.An integral part of our process involves deploying this synthetic data within a simulated network environment,structured on software-defined networking(SDN)principles,to test and refine the traffic patterns.This simulation not only facilitates a direct comparison between the synthetic and real traffic but also enables us to identify discrepancies and refine the accuracy of our simulations.Our initial findings indicate an error rate of approximately 29.28%between the synthetic and real traffic data,highlighting areas for further improvement and adjustment.By providing a diverse array of network scenarios through our framework,we aim to enhance the exercise systems used by cybersecurity professionals.This not only improves their ability to respond to actual cyber threats but also ensures that the exercise is cost-effective and efficient.展开更多
With the development of intelligent and interconnected traffic system,a convergence of traffic stream is anticipated in the foreseeable future,where both connected automated vehicle(CAV)and human driven vehicle(HDV)wi...With the development of intelligent and interconnected traffic system,a convergence of traffic stream is anticipated in the foreseeable future,where both connected automated vehicle(CAV)and human driven vehicle(HDV)will coexist.In order to examine the effect of CAV on the overall stability and energy consumption of such a heterogeneous traffic system,we first take into account the interrelated perception of distance and speed by CAV to establish a macroscopic dynamic model through utilizing the full velocity difference(FVD)model.Subsequently,adopting the linear stability theory,we propose the linear stability condition for the model through using the small perturbation method,and the validity of the heterogeneous model is verified by comparing with the FVD model.Through nonlinear theoretical analysis,we further derive the KdV-Burgers equation,which captures the propagation characteristics of traffic density waves.Finally,by numerical simulation experiments through utilizing a macroscopic model of heterogeneous traffic flow,the effect of CAV permeability on the stability of density wave in heterogeneous traffic flow and the energy consumption of the traffic system is investigated.Subsequent analysis reveals emergent traffic phenomena.The experimental findings demonstrate that as CAV permeability increases,the ability to dampen the propagation of fluctuations in heterogeneous traffic flow gradually intensifies when giving system perturbation,leading to enhanced stability of the traffic system.Furthermore,higher initial traffic density renders the traffic system more susceptible to congestion,resulting in local clustering effect and stop-and-go traffic phenomenon.Remarkably,the total energy consumption of the heterogeneous traffic system exhibits a gradual decline with CAV permeability increasing.Further evidence has demonstrated the positive influence of CAV on heterogeneous traffic flow.This research contributes to providing theoretical guidance for future CAV applications,aiming to enhance urban road traffic efficiency and alleviate congestion.展开更多
Enhancing road safety globally is imperative,especially given the significant portion of traffic-related fatalities attributed to motorcycle accidents resulting from non-compliance with helmet regulations.Acknowledgin...Enhancing road safety globally is imperative,especially given the significant portion of traffic-related fatalities attributed to motorcycle accidents resulting from non-compliance with helmet regulations.Acknowledging the critical role of helmets in rider protection,this paper presents an innovative approach to helmet violation detection using deep learning methodologies.The primary innovation involves the adaptation of the PerspectiveNet architecture,transitioning from the original Res2Net to the more efficient EfficientNet v2 backbone,aimed at bolstering detection capabilities.Through rigorous optimization techniques and extensive experimentation utilizing the India driving dataset(IDD)for training and validation,the system demonstrates exceptional performance,achieving an impressive detection accuracy of 95.2%,surpassing existing benchmarks.Furthermore,the optimized PerspectiveNet model showcases reduced computational complexity,marking a significant stride in real-time helmet violation detection for enhanced traffic management and road safety measures.展开更多
To address traffic congestion,this study improves Mobile Netv2-you only look once version 4(YOLOv4)target detection algorithm(Mobile Netv2-YOLOv4-K++F)and introduces an embedded traffic information processing solution...To address traffic congestion,this study improves Mobile Netv2-you only look once version 4(YOLOv4)target detection algorithm(Mobile Netv2-YOLOv4-K++F)and introduces an embedded traffic information processing solution based on edge computing.We transition models initially designed for large-scale graphics processing units(GPUs)to edge computing devices,maximizing the strengths of both deep learning and edge computing technologies.This approach integrates embedded devices with the current traffic system,eliminating the need for extensive equipment updates.The solution enables real-time traffic flow monitoring and license plate recognition at the edge,synchronizing instantaneously with the cloud,allowing for intelligent adjustments of traffic signals and accident forewarnings,enhancing road utilization,and facilitating traffic flow optimization.Through on-site testing using the RK3399PRO development board and the Mobile Netv2-YOLOv4-K++F object detection algorithm,the upgrade costs of this approach are less than one-tenth of conventional methods.Under favorable weather conditions,the traffic flow detection accuracy reaches as high as 98%,with license plate recognition exceeding 80%.展开更多
Large cities suffer from traffic congestion,particularly at intersections,due to a large number of vehicles,which leads to the loss of time by increasing carbon emissions,including fuel consumption.Therefore,the need ...Large cities suffer from traffic congestion,particularly at intersections,due to a large number of vehicles,which leads to the loss of time by increasing carbon emissions,including fuel consumption.Therefore,the need for optimising the flow of vehicles at different intersections and reducing the waiting time is a critical challenge.Conventional traffic lights have been used to control traffic flow at different intersections and have been improved to become more efficient by using different algorithms,sensors and cameras.However,they also face some challenges,such as high-cost installation,operation,and maintenance issues.This paper develops a new system based on the Virtual Traffic Light(VTL)technology to improve traffic flow at different intersections and reduce the encountered loss of time and vehicles’travel time.Additionally,it reduces the costs of installation,maintenance and operation over various conventional traffic light systems.Consequently,the system proposes algorithms for traffic scheduling and lane identification by using vehicle ID,priority and time of arrival.To evaluate the system,four scenarios were presented where each scenario uses a different number of vehicles consisting of three types(emergency vehicles,public buses and private vehicles),each given a different priority.The proposed system is evaluated by integrating two simulators,namely,(OMNeT++)and(SUMO),and two frameworks,namely,(VEINS)and(INET)to prepare an appropriate working environment.the results prove that an improvement in the average travel time for several vehicles reaches 44.43%–49.76%compared with conventional traffic lights.Further,it is proven from the obtained results that the average waiting time for emergency vehicles is enhanced by 96.63%–97.63%,while the average waiting time for public buses is improved by 94.81%–97.23%.On the other hand,the waiting time for private vehicles‘improved by 87.14%to 89.71%’.展开更多
Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit the prediction acc...Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit the prediction accuracy of most existing models, which simply stack temporal and spatial modules and fail to capture spatial-temporal features effectively. To improve the prediction accuracy, a multi-head attention spatial-temporal graph neural network (MSTNet) is proposed in this paper. First, the traffic data is decomposed into unique time spans that conform to positive rules, and valuable traffic node attributes are mined through an adaptive graph structure. Second, time and spatial features are captured using a multi-head attention spatial-temporal module. Finally, a multi-step prediction module is used to achieve future traffic condition prediction. Numerical experiments were conducted on an open-source dataset, and the results demonstrate that MSTNet performs well in spatial-temporal feature extraction and achieves more positive forecasting results than the baseline methods.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.52172314)the Natural Science Foundation of Liaoning Province,China(Grant No.2022-MS-150)the Special Funding Project of Taishan Scholar Engineering.
文摘This paper investigates the impacts of a bus holding strategy on the mutual interference between buses and passenger cars in a non-dedicated bus route,as well as the impacts on the characteristics of pollutant emissions of passenger cars.The dynamic behaviors of these two types of vehicles are described using cellular automata(CA)models under open boundary conditions.Numerical simulations are carried out to obtain the phase diagrams of the bus system and the trajectories of buses and passenger cars before and after the implementation of the bus holding strategy under different probabilities of passenger cars entering a two-lane mixed traffic system.Then,we analyze the flow rate,satisfaction rate,and pollutant emission rates of passenger cars together with the performance of a mixed traffic system.The results show that the bus holding strategy can effectively alleviate bus bunching,whereas it has no significant impact on the flow rate and pollutant emission rates of passenger cars;the flow rate,satisfaction rate,and pollutant emission rates of passenger cars for either the traffic system or for each lane are influenced by the bus departure interval and the number of passengers arriving at bus stops.
基金Sponsored by Beijing Natural Science Foundation General Project(8212009)Construction of Philosophy and Social Sciences Base in Beijing-Research on Beijing Urban Renewal and Comprehensive Management of Old Community En-vironment2023 Education Reform Project of North China University of Technology(108051360023XN264-25).
文摘The slow traffic system is an important component of urban transportation,and the prerequisite and necessary condition for Beijing to continue promoting“green priority”are establishing a good urban slow traffic system.Shijingshan District of Beijing City is taken as a research object.By analyzing and processing population distribution data,POI data,and shared bicycle data,the shortcomings and deficiencies of the current slow traffic system in Shijingshan District are explored,and corresponding solutions are proposed,in order to provide new ideas and methods for future urban planning from the perspective of data.
文摘At present,problems such as insufficient road infrastructure and supporting facilities,and limited parking spaces are increasingly prevalent,and there are large conflicts of interest in the process of urban renewal.Therefore,it is crucial to improve the quality of the road network.This paper presents an analysis on the current situation of the road traffic system in a completed area outside the Third Ring Road in Xindu District,Chengdu,and provides corresponding road traffic optimization strategies,with aims of solving the existing road traffic problems,improve road service levels,and promote the overall development of the area and improve the quality of urban space.
基金This research work was funded by Institutional Fund Projects under Grant No.(IFPIP:707-829-1443)The authors gratefully acknowledge technical and financial support provided by theMinistry of Education and King Abdulaziz University,DSR,Jeddah,Saudi Arabia.
文摘Due to excessive car usage,pollution and traffic have increased.In urban cities in Saudi Arabia,such as Riyadh and Jeddah,drivers and air quality suffer from traffic congestion.Although the government has implemented numerous solutions to resolve this issue or reduce its effect on the environment and residents,it still exists and is getting worse.This paper proposes an intelligent,adaptive,practical,and feasible deep learning method for intelligent traffic control.It uses an Internet of Things(IoT)sensor,a camera,and a Convolutional Neural Network(CNN)tool to control traffic in real time.An image segmentation algorithm analyzes inputs from the cameras installed in designated areas.This study considered whether CNNs and IoT technologies could ensure smooth traffic flow in high-speed,high-congestion situations.The presented algorithm calculates traffic density and cars’speeds to determine which lane gets high priority first.A real case study has been conducted on MATLAB to verify and validate the results of this approach.This algorithm estimates the reduced average waiting time during the red light and the suggested time for the green and red lights.An assessment between some literature works and the presented algorithm is also provided.In contrast to traditional traffic management methods,this intelligent and adaptive algorithm reduces traffic congestion,automobile waiting times,and accidents.
基金Under the auspices of the National Natural Science Foundation of China(No.40341008)
文摘It has been long believed there should be some relations between traffic system and urbanization,but the in-teraction between them,especially on the regional level,has been not in consideration due to the difficulty in quantitative analysis.Based on the development of Jilin Province during 1981-2003,the paper analyzed the relation with the grey-relation model which was adjusted to fit specific problem,and came to some conclusions.Firstly,there exists ob-vious and strong correlation between traffic system and urbanization.Secondly,urbanization responds to the develop-ment of traffic system mainly on the level of urbanization,such as population and developed area,however,less on urbanization quality.Thirdly,traffic system influences urbanization as a whole except for several peculiar factors,which means we should optimize the whole traffic system to promote urbanization.Based on those conclusions,the paper illustrated the mechanism of traffic system,promoting urbanization scale and urbanization quality.
文摘In order to give a new way for modeling driving behavior, identifying road traffic accident causation and solving a variety of road traffic safety problems such as driving errors prevention and driving behavior analysis, a new driving behavior shaping model is proposed, which could be used to assess the degree of effect of driving error upon road traffic safety. Driver behavior shaping model based on driving reliability and safety analysis could be used to identify the road traffic accident causation, to supply data for driver's behavior training, to evaluate driving procedures, to human factor design of road traffic system.
文摘Chaotic characteristics of traffic flow time series is analyzed to further investigate nonlinear characteristics of air traffic system.Phase space is reconstructed both by time delay which is built through mutual information,and by embedding dimension which is based on false nearest neighbors method.In order to analyze chaotic characteristics of time series,correlation dimensions and the largest Lyapunov exponents are calculated through Grassberger-Procaccia(G-P)algorithm and small-data method.Five-day radar data from the control center in Guangzhou area are analyzed and the results show that saturated correlation dimensions with self-similar structures exist in time series,and the largest Lyapunov exponents are all equal to zero and not sensitive to initial conditions.Air traffic system is affected by multiple factors,containing inherent randomness,which lead to chaos.Only grasping chaotic characteristics can air traffic be predicted and controlled accurately.
基金Project supported by the Ph. D. Programs Foundation of the Ministry of Education of China （Grant No. 20093108110019）
文摘Information feedback strategies can influence the traffic efficiency of intelligent traffic systems greatly.Based on the more practical symmetrical two-route scenario with one entrance and one exit,an improved weighted mean velocity feedback strategy（WMVFS） is proposed,which is not sensitive to the precision of global position system（GPS） devices.The applicability of WMVFS to different weight factors,aggressive probabilities,densities of dynamic vehicles,and different two-route scenarios（symmetrical scenario and asymmetrical scenario with a speed limit bottleneck） is analyzed.Results show that WMVFS achieves the best performance compared with three other information feedback strategies when considering the traffic flux and stability.
基金Project supported by the State Key Program for Basic Research of China(Grant No 2005CB724206)
文摘In this paper, we study the dynamics of the synchronous totally asymmetric simple exclusion process （TASEP） on lattices with two consecutive junctions in a multiple-input-multiple-output （MIMO） traffic system, which consists of m sub-chains for the input and the output, respectively. In the middle of the system, there are n （n 〈 m） sub-chains via two consecutive junctions linking m sub-chains of input and m sub-chains of output, respectively. This configuration is a type of complex geometry that is relevant to many biological processes as well as to vehicular traffic flow. We use a mean-field approach to calculate this typical geometry and obtain the theoretical results for stationary particle currents, density profiles, and a phase diagram. With the values of m and n synchronously increasing, the vertical phase boundary moves toward the right and the horizontal phase boundary moves toward the upside in the phase diagram. The boundary conditions of the system as well as the numbers of input and output determine the no-equilibrium stationary states, stationary-states phases, and phase boundaries. We use the results to compare with computer simulations and find that they are in very good agreement with each other.
基金The project supported by National Natural Science Foundations of China under Grant Nos and Technology Foundation of Beijing Jiaotong University under Grant No. 2004SM026 70471088 and 70225005 and Che Science.
文摘In this work, we propose a new model of evolution networks, which is based on the evolution of the traffic flow. In our method, the network growth does not take into account preferential attachment, and the attachment of new node is independent of the degree of nodes. Our aim is that employing the theory of evolution network, we give a further understanding about the dynamical evolution of the traffic flow. We investigate the probability distributions and scaling properties of the proposed model The simulation results indicate that in the proposed model, the distribution of the output connections can be well described by scale-free distribution. Moreover, the distribution of the connections is largely related to the traffic flow states, such as the exponential distribution （i.e., the scale-free distribution） and random distribution etc.
文摘Based on combing of urban integrated traffic planning report in Ganzhou City and its contrastive study with revised traffic model of general planning,it is found that there is great difference between integrated traffic planning and its actual development in medium-sized cities.Combining new process of reform and opening-up in the past 40 years,the development of urban integrated planning is looked ahead and explored.
文摘The measurements on actual traffic have revealed the existence of meta-stable states with high flow. Such nonlinear phenomena have not been observed in the classic Nagel-Schreckenberg traffic flow model. Here we just add a constraint to the classic model by introducing a velocity-dependent randomization. Two typical randomization strategies are adopted in this paper. It is shown that the Matthew effect is a necessary condition to induce traffic meta-stable states, thus shedding a light on the prerequisites for the emergence of hysteresis loop in the fundamental diagrams.
文摘With increasing of serious environment problems and the coming of the aging society, new traffic systems should be urgently rebuilt. It is necessary to evaluate the traffic service level by utilizing new technique and tool. This paper takes Kitakyushu city as case study to carry out an evaluation of urban traffic system. The concept of accessibility and mobility is used to evaluate the present condition of existing public traffic system based on GIS technology, and then establishment of new route is discussed according to the evaluation results. Additionally, this paper established GIS database and illustrated the relationship between the public traffic and population density. The regions without enough existing traffic were identified. Moreover, the essential terms and considerations were put forward to simulate a new route of public traffic line.
基金supported by the National Key Research and Development Program of China(2021YFB2900200)the Key Research and Development Program of Science and Technology Department of Zhejiang Province(2022C01121)Zhejiang Provincial Department of Transport Research Project(ZJXL-JTT-202223).
文摘Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation systems.Traditional approaches require traffic signal professionals to manually intervene on traffic control devices at the intersection level,utilizing their knowledge and expertise.However,this process is cumbersome,labor-intensive,and cannot be applied on a large network scale.Recent studies have begun to explore the applicability of recommendation system for urban traffic control,which offer increased control efficiency and scalability.Such a decision recommendation system is complex,with various interdependent components,but a systematic literature review has not yet been conducted.In this work,we present an up-to-date survey that elucidates all the detailed components of a recommendation system for urban traffic control,demonstrates the utility and efficacy of such a system in the real world using data and knowledgedriven approaches,and discusses the current challenges and potential future directions of this field.
基金supported in part by the Korea Research Institute for Defense Technology Planning and Advancement(KRIT)funded by the Korean Government’s Defense Acquisition Program Administration(DAPA)under Grant KRIT-CT-21-037in part by the Ministry of Education,Republic of Koreain part by the National Research Foundation of Korea under Grant RS-2023-00211871.
文摘In the rapidly evolving field of cybersecurity,the challenge of providing realistic exercise scenarios that accurately mimic real-world threats has become increasingly critical.Traditional methods often fall short in capturing the dynamic and complex nature of modern cyber threats.To address this gap,we propose a comprehensive framework designed to create authentic network environments tailored for cybersecurity exercise systems.Our framework leverages advanced simulation techniques to generate scenarios that mirror actual network conditions faced by professionals in the field.The cornerstone of our approach is the use of a conditional tabular generative adversarial network(CTGAN),a sophisticated tool that synthesizes realistic synthetic network traffic by learning fromreal data patterns.This technology allows us to handle technical components and sensitive information with high fidelity,ensuring that the synthetic data maintains statistical characteristics similar to those observed in real network environments.By meticulously analyzing the data collected from various network layers and translating these into structured tabular formats,our framework can generate network traffic that closely resembles that found in actual scenarios.An integral part of our process involves deploying this synthetic data within a simulated network environment,structured on software-defined networking(SDN)principles,to test and refine the traffic patterns.This simulation not only facilitates a direct comparison between the synthetic and real traffic but also enables us to identify discrepancies and refine the accuracy of our simulations.Our initial findings indicate an error rate of approximately 29.28%between the synthetic and real traffic data,highlighting areas for further improvement and adjustment.By providing a diverse array of network scenarios through our framework,we aim to enhance the exercise systems used by cybersecurity professionals.This not only improves their ability to respond to actual cyber threats but also ensures that the exercise is cost-effective and efficient.
基金Project supported by the Fundamental Research Funds for Central Universities,China(Grant No.2022YJS065)the National Natural Science Foundation of China(Grant Nos.72288101 and 72371019).
文摘With the development of intelligent and interconnected traffic system,a convergence of traffic stream is anticipated in the foreseeable future,where both connected automated vehicle(CAV)and human driven vehicle(HDV)will coexist.In order to examine the effect of CAV on the overall stability and energy consumption of such a heterogeneous traffic system,we first take into account the interrelated perception of distance and speed by CAV to establish a macroscopic dynamic model through utilizing the full velocity difference(FVD)model.Subsequently,adopting the linear stability theory,we propose the linear stability condition for the model through using the small perturbation method,and the validity of the heterogeneous model is verified by comparing with the FVD model.Through nonlinear theoretical analysis,we further derive the KdV-Burgers equation,which captures the propagation characteristics of traffic density waves.Finally,by numerical simulation experiments through utilizing a macroscopic model of heterogeneous traffic flow,the effect of CAV permeability on the stability of density wave in heterogeneous traffic flow and the energy consumption of the traffic system is investigated.Subsequent analysis reveals emergent traffic phenomena.The experimental findings demonstrate that as CAV permeability increases,the ability to dampen the propagation of fluctuations in heterogeneous traffic flow gradually intensifies when giving system perturbation,leading to enhanced stability of the traffic system.Furthermore,higher initial traffic density renders the traffic system more susceptible to congestion,resulting in local clustering effect and stop-and-go traffic phenomenon.Remarkably,the total energy consumption of the heterogeneous traffic system exhibits a gradual decline with CAV permeability increasing.Further evidence has demonstrated the positive influence of CAV on heterogeneous traffic flow.This research contributes to providing theoretical guidance for future CAV applications,aiming to enhance urban road traffic efficiency and alleviate congestion.
基金funded by the Deanship of Scientific Research at Northern Border University,Arar,Kingdom of Saudi Arabia through Research Group No.(RG-NBU-2022-1234).
文摘Enhancing road safety globally is imperative,especially given the significant portion of traffic-related fatalities attributed to motorcycle accidents resulting from non-compliance with helmet regulations.Acknowledging the critical role of helmets in rider protection,this paper presents an innovative approach to helmet violation detection using deep learning methodologies.The primary innovation involves the adaptation of the PerspectiveNet architecture,transitioning from the original Res2Net to the more efficient EfficientNet v2 backbone,aimed at bolstering detection capabilities.Through rigorous optimization techniques and extensive experimentation utilizing the India driving dataset(IDD)for training and validation,the system demonstrates exceptional performance,achieving an impressive detection accuracy of 95.2%,surpassing existing benchmarks.Furthermore,the optimized PerspectiveNet model showcases reduced computational complexity,marking a significant stride in real-time helmet violation detection for enhanced traffic management and road safety measures.
基金supported by the National Natural Science Foundation of China(No.62066041)。
文摘To address traffic congestion,this study improves Mobile Netv2-you only look once version 4(YOLOv4)target detection algorithm(Mobile Netv2-YOLOv4-K++F)and introduces an embedded traffic information processing solution based on edge computing.We transition models initially designed for large-scale graphics processing units(GPUs)to edge computing devices,maximizing the strengths of both deep learning and edge computing technologies.This approach integrates embedded devices with the current traffic system,eliminating the need for extensive equipment updates.The solution enables real-time traffic flow monitoring and license plate recognition at the edge,synchronizing instantaneously with the cloud,allowing for intelligent adjustments of traffic signals and accident forewarnings,enhancing road utilization,and facilitating traffic flow optimization.Through on-site testing using the RK3399PRO development board and the Mobile Netv2-YOLOv4-K++F object detection algorithm,the upgrade costs of this approach are less than one-tenth of conventional methods.Under favorable weather conditions,the traffic flow detection accuracy reaches as high as 98%,with license plate recognition exceeding 80%.
文摘Large cities suffer from traffic congestion,particularly at intersections,due to a large number of vehicles,which leads to the loss of time by increasing carbon emissions,including fuel consumption.Therefore,the need for optimising the flow of vehicles at different intersections and reducing the waiting time is a critical challenge.Conventional traffic lights have been used to control traffic flow at different intersections and have been improved to become more efficient by using different algorithms,sensors and cameras.However,they also face some challenges,such as high-cost installation,operation,and maintenance issues.This paper develops a new system based on the Virtual Traffic Light(VTL)technology to improve traffic flow at different intersections and reduce the encountered loss of time and vehicles’travel time.Additionally,it reduces the costs of installation,maintenance and operation over various conventional traffic light systems.Consequently,the system proposes algorithms for traffic scheduling and lane identification by using vehicle ID,priority and time of arrival.To evaluate the system,four scenarios were presented where each scenario uses a different number of vehicles consisting of three types(emergency vehicles,public buses and private vehicles),each given a different priority.The proposed system is evaluated by integrating two simulators,namely,(OMNeT++)and(SUMO),and two frameworks,namely,(VEINS)and(INET)to prepare an appropriate working environment.the results prove that an improvement in the average travel time for several vehicles reaches 44.43%–49.76%compared with conventional traffic lights.Further,it is proven from the obtained results that the average waiting time for emergency vehicles is enhanced by 96.63%–97.63%,while the average waiting time for public buses is improved by 94.81%–97.23%.On the other hand,the waiting time for private vehicles‘improved by 87.14%to 89.71%’.
文摘Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit the prediction accuracy of most existing models, which simply stack temporal and spatial modules and fail to capture spatial-temporal features effectively. To improve the prediction accuracy, a multi-head attention spatial-temporal graph neural network (MSTNet) is proposed in this paper. First, the traffic data is decomposed into unique time spans that conform to positive rules, and valuable traffic node attributes are mined through an adaptive graph structure. Second, time and spatial features are captured using a multi-head attention spatial-temporal module. Finally, a multi-step prediction module is used to achieve future traffic condition prediction. Numerical experiments were conducted on an open-source dataset, and the results demonstrate that MSTNet performs well in spatial-temporal feature extraction and achieves more positive forecasting results than the baseline methods.
