Traffic Flow Density Research Articles

Traffic Prediction of Urban Intersections based on ARIMA Model

In the urban planning, road traffic planning as an important part, through the formation of traffic layout network, can further accelerate the pace of urban development. However, the blockage will cause the car to start and stop regularly, and the car engine will emit a large amount of exhaust gas in these two stages, resulting in increased environmental pollution. Therefore, the focus needs to be on how to predict traffic flow efficiently. This paper focuses on the traffic flow density of intersections in one month, presents the change of traffic density by means of mapping, reasonably divides the training set and the test set, and uses ARIMA model to make effective prediction. It shows the changing relationship between traffic flow and time. Through reasonable prediction, the congestion problem is found in the first time, and at the same time, the solution measures are given, the traffic infrastructure is scientifically allocated, and the safety control system is set up, which provides reference for the later urban traffic development.

Перспективи застосування жорсткого дорожнього одягу під час будування автомобільних доріг та удосконалення підходів до його конструювання і розрахування

Introduction. This article examines the issue of improving the methods of designing and calculating rigid road surfaces, outlined in the DSTU project “Guidelines for the Design of Rigid Road Surfaces” (hereinafter referred to as the DSTU project). The specified methods were developed on the basis of domestic and global experience in the design of highways with rigid road surfaces, analysis of current legal acts, regulatory documents, technical literature related to the object of standardization, taking into account the availability of modern road construction materials and technologies. density of traffic flow, diversity of subsoil, including in complex engineering and geological conditions, peculiarities of road and climatic regions of Ukraine, etc. Problem statement. The need for improvement and a unified approach to the design of rigid road clothing, taking into account the peculiarities of its operation, with the determination of the appropriate parameters depending on the initial data and the effective use of material and technical resources.

Numerical solution of nonlinear equations of traffic flow density using spectral methods by filter

Numerical solution of nonlinear equations of traffic flow density using spectral methods by filter

Application of dynamic desired headway based adaptive backstepping sliding mode control design to mixed traffic system

To optimize the mixed car-following behavior of connected autonomous vehicles (CAVs) and human-driven vehicles (HDVs), an adaptive backstepping sliding mode control (ABSMC) strategy for longitudinal velocity and distance control model (namely, MCF-ABSMCM) is put forth. First, the variable desired headway model (VDHM) is designed based on the vehicle-to-vehicle and vehicle-to-infrastructure information. Also, an asymmetric stochastic car-following model (ASCM) is designed to realistically describe the stochastic factor as well as vehicle acceleration and braking behaviors in mixed car-following. Second, an adaptive cruise sliding mode control law with a backstepping approach is devised to precisely track the desired following distance based on the VDHM. After creating the basic diagram of the two-model traffic flow, the intelligent driver model (IDM) is used as a baseline to compare and analyze the traffic capacity. Lastly, the effectiveness of the MCF-ABSMCM approach is confirmed in terms of both the mixed traffic flow density wave evolution and the vehicle control strategy, and the MCF-ABSMCM is validated under various adversary inputs. The simulation results demonstrate that the mixed-flow queue can finish headway tracking and keep a safe distance when using the MCF-ABSMCM described. This control strategy has been validated in VISSIM to significantly improve the efficiency of traffic operations compared to IDM and ASCM.

Research on a Simulation and Prediction Method of Traffic Flow Information Based on PINN

Traffic flow prediction can help intelligent transportation effectively be carried out. This paper employs the Physics-Informed Neural Network (PINN) as a deep learning method and partial differential equation (PDE) multivariable methods to approximate solutions for the Lighthill-Whitham-Richards (LWR) traffic flow equation system. The relationship between traffic flow density function and time/displacement is obtained by setting different function conditions and initial boundary constraints. Furthermore, a series of three-dimensional graphics are generated during the research process through dynamic comparisons and evaluations of independent variables to intuitively display and analyze traffic flow trends and gradients. Additionally, before the commencement of the study, the authors propose specific initial condition combinations corresponding to real-world application scenarios to enhance the practicality of the research. Moreover, through the interpretation and reflection on the obtained images, the study identifies inconsistencies between actual situations and predictions, leading to necessary adjustments. Furthermore, the research explores the compatibility of the u(x) function and hard constraint conditions in different scenarios, aiming to accurately predict traffic information and ultimately enhance the utilization of traffic resources. By leveraging PINN and PDE technologies, this study contributes to advancing traffic flow analysis and optimization, potentially influencing urban planning and traffic management strategies positively.

Performance Analysis of Unsignalized Intersection Using PTV VISSIM Software Modeling (Case Study of Sakra 4-way intersection, East Lombok)

Sakra 4-way intersection is one of the unsignalled intersections in East Lombok. At certain times of the day, there are frequent traffic jams and queues of moving vehicles at this intersection because the area surrounding the intersection is a commercial area, as evidenced by the presence of settlements, markets, mosques, village heads’ offices, shops, and other shopping centers. This research aims to determine the movement of traffic flow at the 4-way Sakra intersections in East Lombok using Vissim software modeling. Data collection was obtained from literature studies and direct surveys at the research site. Direct questionnaires at the research location and literature reviews were used to collect data. Using PTV VISSIM software modeling, the intersection of Sakra East Lombok was modeled under the current conditions on Monday and Sunday. The results showed that values for Monday were Queue Length (Qlen) 34.77 m and Tundaan (VehDelay) 19.95 sec / skr. The value of Tundaan (VehDelay) on Sundays is 16.68 sec/skr, the value of Queue Length (Qlen) on Sundays is 23.76 m, and the service level of the junction (LOS) on Monday and Sunday is C (not good). And for the movement of vehicle flow passing at intersection 4 Sakra East Lombok, which indicates the density of vehicles traffic flow is moderate, internal traffic barriers begin to affect speed and drivers still have adequate discretion over their speed and the lane they use on the road.

Effect of road pricing on the spatial distribution of traffic flow in a grid network

This paper develops a continuous approximation model for analyzing the effect of road pricing on the spatial distribution of traffic flow. The traffic flow density, which describes traffic flow as a function of position, is derived for a rectangular city with a grid network. The analytical expression for the traffic flow density demonstrates how the toll level, the size and shape of the toll area, and the shape of the city affect the spatial distribution of traffic flow. As the size of the toll area increases, reducing the traffic flow density at the city center becomes difficult. As the aspect ratio of the toll area increases, the traffic flow density at the city center increases. The shape of the city has less impact on the traffic flow density than the shape of the toll area.

Modeling and stability analysis of an extended car-following model behavior of the currents vehicle based on delay of response and signal interruption probability

This paper studies the modeling and stability analysis of an extended car-following model based on delay of response and signal interruption probability. First, by linear analysis, we give the stability condition of the model. The result shows that the stability region of the traffic flow will expand with the decrease in the probability p of signal transmission interruption. When the delay of response effect of the driver weakens, the traffic flow will become more and more stable. Second, the mKdV equation is derived based on the nonlinear reduction perturbation method. This result shows that with the decrease of parameter p, the amplitude of the traffic flow density wave decreases, the traffic flow becomes more and more stable, and the traffic congestion is gradually improved. Finally, numerical simulation verifies the correctness of the solution results.

Шумовое загрязнение территории многоэтажных жилых застроек города Ставрополя

The article provides measurement results and an assessment of the noise load on the territory of the «Perspektivny» and «Rossiysky» residential complexes in Stavropol. Noise measurements were carried out in the spring-summer and autumn-winter periods of 2022–2023. The measurement results are presented as average noise exposure levels. Based on the data obtained, a mathematical model of the propagation of noise from traffic flow during the deciduous and leafless period was built. To conduct a study and assess the noise load in a multistorey building on the territory of the South-Western district of Stavropol. The measurement of the noise load was carried out in accordance with GOST 23337-2014 “Noise. Methods for measuring noise in residential areas and in residential and public buildings”. To analyze and compare the data obtained with the maximum permissible value, SanPiN 1.2.3685-21 “Hygienic standards and requirements for ensuring the safety and (or) harmlessness of environmental factors for humans” was used. The measurement results revealed excess of maximum permissible noise level on the territory of the residential complex «Perspektivny» and «Rossiysky», and the houses within the residential complex «Perspektivny» suffer most from the proximity of the roadway and the absence or partial landscaping. Noise values were recorded near residential buildings in the range of 70 dBA. On the territory of the residential complex “Rossiysky”, high indicators are found on the sidewalk near the South-Western bypass. No excess of maximum permissible noise load level was noticed directly at the houses. The resulting mathematical model reflects the dependence of the noise level on the presence and absence of foliage and the density of traffic flow. Based on the data obtained, we can conclude that the residential complexes «Perspektivny» and «Rossiysky» are subject to significant noise pollution. This can be attributed to shortcomings in the planning of territory development and the increase in the number of vehicles.

Reliability assessment and optimization of computer networks based on neural networks

Abstract Amidst the swift evolution of computer technologies, the prevalence of computer networks has become pivotal across diverse sectors, increasingly reliant on their robust functionality. This study rigorously evaluates and enhances the reliability of computer networks by leveraging an index system and an evaluation model devised through neural networks. To strengthen network dependability, this research employs a Hopfield neural network to address multi-constraint Quality of Service (QoS) multicast routing challenges, thereby elevating network reliability. Simulation experiments demonstrate that the Hopfield neural network effectively mitigates network latency and exhibits superior convergence performance compared to conventional QoS multicast routing methods. Further, this paper applies the neural network-based evaluation model to analyze the reliability of the air traffic network within the H-area after integrating the optimized computer network framework. It is observed that the most significant contributor to traffic flow loss is the network's degree value. An analysis of traffic flow density, employing actual sector flow data, reveals that high traffic volumes typically precipitate congestion. Nonetheless, the traffic flow density value consistently exceeds 100, suggesting that the enhanced computer network model holds practical applicability in real-world scenarios.

Прогнозування завантаженості вулиць великих міст з урахуванням коливань щільності та швидкості руху транспортних потоків

The work has developed a methodical approach for forecasting the congestion of the streets of large cities, taking into account the fluctuations in the density of traffic flows and the speed of movement of cars in the traffic flow, which are associated with "peak hours". The methodological approach, unlike the previously known ones, complements the well-known robustness criterion developed by the authors in previous publications, which allows to increase the accuracy of forecasting the occurrence of traffic jams. Time-varying functions of traffic flow density and vehicle speed in the traffic flow are proposed. In addition to real time, functions contain variable parameters in the form of amplitude of oscillations and period of oscillations. This makes it possible to adapt the forecasting model to the real road network, taking into account the period of network congestion and road infrastructure. The dependences of the change in the range of robustness of the traffic flow when the density and speed of movement of vehicles in the flow change. It has been proven that in the presence of fluctuations of the listed parameters, the appearance of traffic jams occurs at average values of density and speed. A significant influence of the amplitude of fluctuations in the density and speed of movement of vehicles in the stream on the appearance of traffic jams has been proven. It is shown that the magnitude of the amplitude of oscillations during "peak times" significantly reduces the stability range of the traffic flow. The influence of the "peak hour" period on the loss of stability of the traffic flow is given. It has been proven that the period of oscillations is an insignificant factor in forecasting traffic jams. However, accounting for such a factor will allow to adapt the mathematical model to the real conditions of traffic flow behavior and thereby increase the accuracy of forecasting. It is shown that accounting for the fluctuating component of the traffic flow expands the possibilities of applying the robustness criterion presented by the authors in previous publications and makes it possible to provide a more accurate forecast for various sections of the road network of large cities.

User Opinion on Factors Affecting Drivers Frequent Lane-Changing Behavior: A National Sample of Drivers in Pakistan

Abstract: In recent years massive traffic volume increase has demanded the implementation of traffic improvement plans in Pakistan. The urban Highway transportation networks are becoming congested in developed as well as in most of the developing countries. The main causes of unmanageable heterogeneous traffic congestion on the highway are an increase in population, change in lifestyle, and economic development of a country. To recognize the characteristics of a driver who frequently changes lanes and analyze the techniques of frequent lane-changing behavior. The researchers collected data via a questionnaire survey and analyzed the influence of traffic environment and driver characteristics violation on frequent lane-changing behavior on travel speed in detail by manually Excel statistics. Results showed that the impact of a heterogeneous traffic environment of two lanes and three lanes cars, and traffic flow density was sharply associated with frequent lane-changing behavior. The drivers were the main factors affecting frequent lane-changing behavior in heterogeneous traffic conditions, which was most popular during aggressive driving. Only 8.33% of drivers were never involved in this behavior. Most liable to frequent lane-changing behavior were males as compared to females, 31–40-year-old drivers, and those with low academic qualifications and private vehicle personalities. Among various traffic factors, changes in required speed had the most significant impact on how often lane changes occurred. The findings of the current study highlight the most significant traffic parameters that influence the lane change frequency. This research recommends strict enforcement of lane discipline to counter traffic congestion and the remedial measures that are to be taken for the improvement of better and sustainable road infrastructure conditions. Overall the research study will have practical implications for improving traffic management and safety on highways, and it provides a foundation for further research in the field of traffic-related technologies.

Hopf bifurcation control of macroscopic traffic flow model considering vehicle braking effect.

Traffic congestion not only has a great impact on people's travel, but also increases energy consumption and air pollution. The control analysis of the macroscopic traffic flow model considering the vehicle braking effect is particularly important, reflecting the impact on the actual traffic flow density wave, so as to better solve the actual traffic problems. In this paper, based on a speed difference optimization speed model, the micro-macro-variables are transformed into a high-order continuous traffic flow model. Then, a random function considering the physical correlation of random components is added to the high-order continuous traffic flow model to establish a random traffic flow model that can reflect the uncertain behavior of traffic flow acceleration or deceleration. Based on this stochastic traffic model, the existence of Hopf bifurcation and bifurcation control of the traffic flow system model considering stochastic characteristics are derived by using Hopf bifurcation theorem. By Chebyshev polynomial approximation method, the stochastic problem of the system is transformed into the bifurcation control problem of its equivalent deterministic system. A feedback controller is designed to delay the occurrence of Hopf bifurcation and control the amplitude of the limit cycle. Without changing the equilibrium point of the system, the complete elimination of Hopf bifurcation can be achieved by controlling the amplitude of the limit cycle. That is, the feedback controller is used to modify the bifurcation characteristics of the system, such as the bifurcation appearing at the equilibrium point in the control system moves forward, moves backward or disappears, so as to achieve the effect of preventing or alleviating traffic congestion.

Proximal policy optimization learning based control of congested freeway traffic

AbstractIn this paper, a delay compensation feedback controller based on reinforcement learning is proposed to adjust the time interval of the adaptive cruise control (ACC) vehicle agents in the traffic congestion by introducing the proximal policy optimization (PPO) scheme. The high‐speed traffic flow is characterized by a two‐by‐two Aw Rasle Zhang nonlinear first‐order partial differential equations (PDEs). Unlike the backstepping delay compensation control,23 the PPO controller proposed in this paper consists of the current traffic flow velocity, the current traffic flow density and the previous one step control input. Since the system dynamics of the traffic flow are difficult to be expressed mathematically, the control gains of the three feedback can be determined via learning from the interaction between the PPO and the digital simulator of the traffic system. The performance of Lyapunov control, backstepping control and PPO control are compared with numerical simulation. The results demonstrate that PPO control is superior to Lyapunov control in terms of the convergence rate and control efforts for the traffic system without delay. As for the traffic system with unstable input delay value, the performance of PPO controller is also equivalent to that of backstepping controller. Besides, PPO is more robust than backstepping controller when the parameter is sensitive to Gaussian noise.

Comparison of Headway Measurement Methods for Heterogeneous Traffic Conditions

Abstract: This paper covers research aimed at determining if moving method (MM) is capable enough to accurately determine traffic parameters including headway, traffic flow, and traffic density on 2-lane highways under heterogeneous traffic conditions of Pakistan. For this, stationary method (SM) is set as base and results obtained by MM are compared. Linear model is developed to compare headway measured using MM. Results indicated that for 2-lane highway, chi-square value is 0.65 indicating 65% of results obtained by MM are compatible to SM. Percentage difference b/w the results obtained by MM and SM for traffic flow and traffic density are 2.32 and 5.17 respectively. Overall performance of MM for traffic parameter determination is quite satisfactory however, these results are only valid in generalized conditions. For specific conditions of traffic and road, these models need to be re-evaluated

Modeling of Traffic Flows Sustainability on Highway Network Stretches

Assessing the transport flow robustness is a significant aspect of a qualitative solution to traffic management problems. Therefore, management should be based on appropriate criteria, accounting for different factors characterizing traffic flow sustainability. That’s why it is crucial to establish the impact rate for each group of factors on the robustness criterion. Therefore, the current study aims to obtain the dependence of the criterion changes for traffic flow sustainability on the traffic jam occurrence when changing the gradients’ product of traffic flow density and its speed. The value of the robustness criterion allows for performing an impact rating for input factors on traffic flow sustainability. All factors affecting transport flow robustness are divided into three groups. Based on simulation results, factors rating that impact the robustness margin value of the traffic flow is presented. Length and weight of automobiles are at first place according to impact terms on the sustainability loss of the traffic flow. In second place of impact on sustainability loss are the temporary factors group and factors group that considers the roadway environment’s infrastructure. Hence, the results can be used to analyze sustainability traffic flows in controlled highway network stretches and develop measures to increase sustainability reserve.

Dynamic Response Threshold Model for Self-Organized Task Allocation in a Swarm of Foraging Robots

In swarm-robotics foraging, the purpose of task allocation is to adjust the number of active foraging robots dynamically based on the task demands and changing environment. It is a difficult challenge to generate self-organized foraging behavior in which each robot can adapt to environmental changes. To complete the foraging task efficiently, this paper presents a novel self-organized task allocation strategy known as the dynamic response threshold model (DRTM). To adjust the behavior of the active foraging robots, the proposed DRTM newly introduces the traffic flow density, which can be used to evaluate the robot density. Firstly, the traffic flow density and the amount of obstacle avoidance are used to adjust the threshold which determines the tendency of a robot to respond to a stimulus in the environment. Then, each individual robot uses the threshold and external stimulus to calculate the foraging probability that determines whether or not to go foraging. This paper completes the simulation and physical experiments, respectively, and the performance of the proposed method is evaluated using three commonly used performance indexes: the average deviation of food, the energy efficiency, and the number of obstacle avoidance events. The experimental results show that the DRTM is superior to and more efficient than the adaptive response threshold model (ARTM) in all three indexes.

Traffic Flow Video Image Recognition and Analysis Based on Multi-Target Tracking Algorithm and Deep Learning

Traffic flow parameters are an important data support for the research and development of several technologies in the intelligent transportation system. Therefore, accurate and real-time estimation of traffic flow is particularly important for urban traffic. In this study, a real-time traffic flow detection system framework was constructed based on video image collection and analysis. According to the vehicle detection and tracking results, a traffic flow parameter estimation model and an improved LSTM network are proposed for spatiotemporal counting feature recognition. The results conclude that the developed framework can estimate the traffic flow density and count vehicles, as well as estimate the traffic flow velocity and traffic volume to estimate and optimize traffic flow, respectively. Additionally, the simulation results show that the proposed method can not only counts the two-way traffic vehicles quickly and accurately, but also avoids the use of the complex multi-target tracking method to spatiotemporal correlation of a single target, increases the speed and accuracy of the spatiotemporal information processing procedure, and has stronger scene adaptability.

Optimization of Roadside Unit Deployment on Highways under the Evolution of Intelligent Connected-Vehicle Permeability

With the increasing number of Connected and Autonomous Vehicles (CAVs), the heterogeneous traffic flow on highways now consists of a mix of CAVs and Non-networked Autonomous Vehicles (NAVs). The current deployment of Roadside Units (RSUs) on highways is mostly based on uniform or hotspot locations. However, when the permeability of CAVs on the road varies, the communication network may face challenges such as excessive energy consumption due to closely spaced RSU deployments at high CAV permeability or communication interruptions due to widely spaced RSU deployments at low CAV permeability. To address this issue, this paper proposes an improved D-LEACH clustering algorithm based on vehicle clustering; analyzes the impact of RSU and vehicle communication radius, mixed traffic density, and different CAV permeabilities in the heterogeneous traffic flow on the RSU deployment interval; and calculates the rational and effective RSU deployment interval schemes under different CAV permeabilities on highways in the heterogeneous traffic flow. When the heterogeneous traffic flow density is stable and CAV continues to penetrate, the RSU communication radius and deployment interval can be adjusted to ensure that the network connectivity is maintained at a high level. When the RSU and vehicle communication radius are stable, the mixed traffic density is 0.05, and the CAV permeability is 0.2, the RSU deployment interval can be set to 1235 m; when the mixed traffic density is 0.08 and the CAV penetration rate is 0.7, the RSU deployment interval can be set to 1669 m to ensure that the network connectivity is maintained at a high level.

PERFORMANCE ANALYSIS OF BANJAR SUGIHAN ROAD (STA 0+000-03+000) DIRECTION TO BENOWO, SURABAYA CITY, EAST JAVA PROVINCE USING MKJI 1997 METHOD

Transportation is important as a tool for to go everyday. The increased demand for transportation causes an increase in traffic flow and volume of vehicles which will then cause congestion. One of the traffic jams that occur in the city of Surabaya is on the Banjar Sugihan road. The purpose of this study is to review and analyze the density of traffic flow that occurs on the Banjar Sugihan road, so that it can solve congestion problems and improve services. The method in this study was carried out by conducting traffic surveys to collect primary data which was carried out for three days during rush hour (06.00-17.00) which was guided by the 2014 PKJI. This research resulted in a large volume of vehicles, large capacity roads, as well as the performance of the Banjar Sugihan highway section. From the results of the study it can be concluded that the Banjar Sugihan highway is a road that is densely packed with vehicles, the performance of the Banjar Sugihan Street section has a forced or jammed flow, low speed, volume below capacity. The queues were long and there were big obstacles.