Traffic Flow Simulation Research Articles

Simulation of Traffic Flow under Heterogeneous Traffic Conditions using VISSIM

Simulation of Traffic Flow under Heterogeneous Traffic Conditions using VISSIM

Mitigating oscillations of mixed traffic flows at a signalized intersection: A multiagent trajectory optimization approach based on oscillation prediction

To mitigate the traffic oscillations generated when traffic flow encounters a red light at a signalized intersection, many studies have used reinforcement learning to control connected and automated vehicles (CAVs) trajectories to avoid oscillations. These methods, which are effective in mitigating oscillations in a pure CAV environment, perform poorly when applied to mixed traffic streams, due to the fact that most of the methods ignore that human vehicles (HVs) in mixed traffic flows stop at red lights and trigger oscillations, resulting in significant “trajectory fluctuation” phenomena in some CAVs, which will lead to poor effectiveness in mitigating oscillations.To address this problem, We propose a method that combines oscillation prediction and multiagent trajectory optimization to mitigate the oscillations generated by HVs. First, we predict the oscillation caused by HVs stopping during a red light, and after that, we use the Newell model to predict the propagation range of the oscillation. According to whether the HV ahead produces oscillation or not, we classify CAVs into two types of agents and design the control scheme separately. The first type of CAVs are immediately adjacent to the oscillation, and we use a jam-absorption driving (JAD) strategy to treat them as absorbing vehicles to absorb the oscillation. While the second type of CAVs are vehicles other than the first type of CAVs, we use the deep reinforcement learning (DRL) method to control them to arrive at the intersection within the predicted green light time. We tested the method in a mixed traffic flow simulation environment. Experimental results show that this method can effectively suppress the phenomenon of “trajectory fluctuations” under different CAV penetration rates, achieving the goal of effectively mitigating oscillations thus significantly improving traffic efficiency and reducing vehicle fuel consumption. Meanwhile, the method also has the advantages of fast convergence during training and high stability during testing compared with traditional reinforcement learning methods.

Impact of Autonomous Vehicles on Traffic Flow in Rural and Urban Areas Using a Traffic Flow Simulator

Autonomous vehicles have the potential to significantly improve modes of transportation, and many businesses and research facilities are developing such systems. Although there are studies on the social implementation of autonomous vehicles, these studies are based on limited conditions such as predetermined driving environments. Therefore, in this study, we target urban areas and rural areas, and we simulate a behavioral algorithm for autonomous vehicles being developed and owned by Kanazawa University. In this study, a traffic flow simulation system (Aimsun) was constructed to reproduce the current situation of traffic flow in the city during normal times, using data from a person-trip survey conducted by the local government. In addition, we varied the mixing rate of automated vehicles and evaluated its effect on the delay time between ODs. We assume the gradual replacement of existing vehicles by autonomous vehicles on actual road networks and for realistic traffic volumes, and we investigate their impact on traffic flow. We vary the mixing rate of autonomous vehicles into actual traffic environments, and we measure the delay in the origin-destination (OD) interval to evaluate the impact of autonomous vehicles on traffic flow. The results obtained show that as the mixing rate of autonomous vehicles increases, the delay between OD intervals increases. Then, once the mixing rate exceeds a certain value, the delay between OD intervals gradually decreased. The delay time for all vehicles slightly increases as the mixing rate of autonomous vehicles increased from 10 to 45%. When the mixing rate increased from 45 to 50%, the delay time for all vehicles decreased notably, and when the mixing rate was 50 to 100%, it remained constant. Analytical results showed that when socially implementing autonomous vehicles, their mixing rate impacts the traffic flow; thus, there is a need to determine appropriate distribution scenarios and areas for implementation.

Traffic study using unmanned aerial vehicle & simulation of traffic flow at congested junctions of Salem City using hybrid approach

The number of road accidents in 2022 increased by 11.9% compared to 2021. Similarly, the number of deaths and injuries on account of road accidents also increased by 9.4% and 15.3% respectively. Road collision incidences in India are increasing at a rate of 5% faster than the world average. Since everyone moves about a lot in their everyday lives, transportation has become a part of everyone’s existence. All people, regardless of age, must travel to do their daily tasks, which causes roadways to get blocked. This research examines how urbanization and industry are causing traffic congestion in the current environment. In the Salem Corporation specified road network, 162 road links were chosen for the study and surveyed with unmanned aerial vehicles. By adopting this digital aerial survey, local authorities may overcome their challenges in estimating the varied road network required at any time from all aspects. Drone have been used to conduct extensive investigations of the condition of the Five Roads Junction, Kondalampatti, Seelanaikanpatti, Shewapett, Junction Main Roads in the Salem district. The intersections were selected because they see a higher volume of traffic, particularly during peak hours. The manual traffic study was conducted to determine the reasons for traffic congestion. Pedestrian laws, appropriate bus stops, signalized junctions, and other measures can all be used to manage traffic. Unlike conventional methods, traffic simulation software such as PTV VISSIM and Any-logic are being used in this research to minimize the identified problems since it may be the alternative approach. This research deals with the Salem district traffic issue at five complex intersections and offers some fundamental remedies.

An Anti-Collision Algorithm for Self-Organizing Vehicular Ad-Hoc Network Using Deep Learning

The rapid increase of the number of motor vehicles over the last several decades has driven a corresponding increase in the severity of traffic congestion, which has exhibited a considerable human impact. Intelligent anti-collision control via inter-vehicle communication technology can facilitate vehicles adhering to spacing speed standards and improve road utilization and traffic efficiency. In this paper, we apply a deep learning image estimation model based on joint attention mechanism. The network framework uses a deep estimation network Yolov5 and a location based VANET information fast transmission strategy to work together. This paper mainly considers vehicle distance measurement technology as a point of entry to study multi-sensor information fusion for vehicle collision prevention technology based on the self-organizing vehicular ad-hoc network (VANET). This paper also proposes a solution based on the strategy of one-way transmission of shared information and dynamic valuation of a cluster distance threshold with vehicle density. The proposed vehicle anti-collision control algorithm is designed to realize dynamic vehicle control via inter-vehicle communication. In this paper, the two-way coupling of traffic flow and network simulator is used to randomly generate vehicle nodes on the road, and the behavior of the anti-collision system is simulated. The experimental results show that the predetermined control goal is achieved, which demonstrates the effectiveness of the proposed algorithm.

VISSIM Based Traffic Flow Simulation Analysis on Road Network

The urban transport system is a heterogeneous system and is in serious trouble. Traffic congestion has become a major socio-economic problem in both urban and rural areas. Traffic congestion is managed through signage, interchanges, and road widening. Traffic analysis remains a difficult task, especially in countries like India where the number of vehicles is constantly increasing and the roads are increasingly busy, because it is difficult to generate alternatives. Traffic simulation systems such as PTV VISSIM are tools dedicated to the analysis of traffic problems. VISSIM is a simulation software that is widely used to create simulations in dynamic traffic situations before evaluating traffic conditions and creating a realistic plan. Dynamic simulation of traffic flow using VISSIM and appropriate techniques to reduce traffic congestion. The main objective is to examine the study area and prepare a sample for it to find out the root causes of the traffic problem and give the necessary suggestions to solve the problem.

Incident detection on urban roads - A case study using synthetic floating car data

Within the scope of this paper we examine incident detection on inner-city roads using floating car data (FCD) under different traffic conditions and data qualities. We used synthetic FCD to analyze incidents under variable conditions, such as different traffic volumes. They are generated from microscopic traffic flow simulations with the software tool PTV Vissim. Automated processing of the synthetic FCD gained from the microsimulation models also makes it possible to analyze different data qualities resulting from the choice of penetration rate and transmission frequency. We investigated the recognizability of the incidents using five laboratory examples, which depict different traffic incidents, and a real inner-city road in Karlsruhe, Germany. Graphical and quantitative evaluations are used for incident detection, whereby violin plots and the proposed incident indicator have the most reliable detection rate. Incident detection decreases significantly if several incidents overlap, the severity of the incidents or the traffic volume is reduced, the data quality decreases, or if there is no current speed information in the data. For additional insights, we recommend considering the different figures created in the graphical analysis alongside the incident indicator used in the quantitative analysis.

Electric charging stations for electric vehicles in a traffic flow simulation model

This article substantiates the need to use simulation modeling in planning the location of parking lots equipped with charging stations for electric cars. Moscow is actively developing infrastructure for the use of electric cars for personal use, but there is a limited number of charging stations in the city districts. This increases the load on the transportation framework of the capital. Creating a simulation model of the transport system allows us to identify its “bottlenecks” related to the effective organization of road traffic and the creation of a sustainable environment. The use of methods of structural analysis, synthesis, groupings, information and simulation modeling allowed to establish all key objects of the problem area, their qualitative and quantitative characteristics necessary to create a simulation model. The created simulation model is based on the developed formal models of changes in the states of each class of objects, corresponding to the behavior in the real urban environment. To demonstrate the obtained results, a three-dimensional model corresponding to the simulation model is developed.

Environmental aspect in traffic flow simulation modeling

The article deals with the problem of air pollution by automobile transportation. Such emissions are a problem in modern cities worldwide, and they harm numerous aspects of human life and the environment. Changing traffic flows and modernization of road infrastructure are ways to reduce the load on the ecological state of urban areas. Developing concepts and assessing their impact on the transportation system and the environment is possible through simulation models. The study establishes all the objects and their qualitative and quantitative characteristics necessary to create a digital twin of traffic flows. Using parametric modeling techniques allowed us to create a simulation model reflecting all aspects of the subject area. The developed model allows conducting experiments on changing the parameters of objects to predict changes in the system’s behavior in terms of its ecological state.

Experience in calibrating the VISSIM microscopic simulation model for an unsignalized intersection in Pekanbaru, Indonesia

Traffic activity is unique and occurs throughout the region. All moving traffic movements cause a build up of vehicles when there are conflicts between vehicles and result in congestion, one of which is in the intersection area located on Jalan SM Amin, Pekanbaru. Traffic modelling can assist traffic management through accurate simulation results with field conditions based on driving behavior value VISSIM is a simulation tool used to simulate dynamic traffic flow conditions. The research has aim to modelling and calibrating driver behavior value based on traffic flow conditions at unsignalised intersections in Pekanbaru. This research uses simulation modelling with VISSIM as the modeler and GEH and MAPE as validation tools to choose which right model. Simulation process will used calibration process based on driving behavior value for the right model by trial and error method.. The result showed that simulation model based on default parameter of driving Behavior cannot represent for real traffic. Then changes in the combination of Driving Behaviour values affect the accuracy of model conditions with field conditions. The accuracy is measured using the reference volume of vehicles exiting the unsignalled intersection. Therefore, this research could be can assist in smoothing traffic flow model in Pekanbaru which more easily by using live traffic flow simulation that can be utilized for traffic intersection management scenarios.

Traffic flow simulation study under large gathering activities based on VISSIM

Based on the above background, this paper starts from the theory of traffic flow and the macro-basic diagram, and simulates and researches the traffic congestion problems generated in the period of large-scale gathering activities during festivals. First of all, this paper summarizes the time correlation and spatial correlation of traffic flow, analyses the judgement method and rating index of traffic congestion, and completes the macroscopic basic map; after defining the simulation parameters of each road segment and signal intersection in the road network, it is implemented by using the VISSIM simulation software; finally, it carries out the simulation analysis with the example of the New Year's Eve firework display at the Chaotianmen Gate in Chongqing, and calculates and analyses the traffic flow state of the road network with output data, and then compares the output data with that of the road network. Finally, we use the output data to calculate and analyses the traffic flow status of the road network, compare it with the traffic flow data under the smooth period, judge the congestion characteristics, draw the macroscopic basic map of the road network under each period, simulate the changes of the macroscopic basic map, analyses the impact of traffic congestion on the traffic flow of the road network, calculate the degree of improvement of the traffic status of the network, and put forward the reasonable optimization scheme to provide a decision-making basis for the evacuation of the traffic under the festival and large-scale gathering activities.

Performance Analysis of One-Level Signalized Urban Intersections with Exclusive Pedestrian Phases and Diagonal Crossings

The exclusive pedestrian (hereinafter P) phase with a diagonal crossing is routinely introduced to improve P safety at high-volume intersections. The article analyses and evaluates the feasibility of the exclusive P phase and diagonal crossing at single-level smaller intersections, identifying the advantages and disadvantages of the exclusive P phase and diagonal crossing from the point of view of time losses. In the experimental part, traffic flow modelling is carried out. The traffic flow simulations show that an exclusive P phase is most beneficial in terms of time losses at an intersection with 2+2 lane intersecting streets and ≥ 900 P/hour with ≥ 1600 vehicles/hour (hereinafter V). In addition, an exclusive P phase can be implemented at the small intersections analysed in this paper, where the volume of V is low or medium, regardless of the number of P at the intersection.

Performance Analysis of One-Level Signalized Urban Intersections with Exclusive Pedestrian Phases and Diagonal Crossings

The exclusive pedestrian (hereinafter P) phase with a diagonal crossing is routinely introduced to improve P safety at high-volume intersections. The article analyses and evaluates the feasibility of the exclusive P phase and diagonal crossing at single-level smaller intersections, identifying the advantages and disadvantages of the exclusive P phase and diagonal crossing from the point of view of time losses. In the experimental part, traffic flow modelling is carried out. The traffic flow simulations show that an exclusive P phase is most beneficial in terms of time losses at an intersection with 2+2 lane intersecting streets and ≥ 900 P/hour with ≥ 1600 vehicles/hour (hereinafter V). In addition, an exclusive P phase can be implemented at the small intersections analysed in this paper, where the volume of V is low or medium, regardless of the number of P at the intersection.

Numerička simulacija prometnog toka

The paper discusses the concept of traffic flow described by hyperbolic differential equations. In this paper the Lighthill-Whitham-Richards model (LWR model) is used to describe traffic flow. The said model uses two parameters to describe the traffic flow – density and average speed of vehicles. Numerical approximation of the LWR model is formulated through scalar conservation laws. The finite volume method is used for numerical results. The term of shock wave and propagation of rarefaction wave in traffic flow are described. This paper focuses on numerical simulation of traffic flow via fluid dynamics model for a single road with a traffic light. The results obtained in this paper are compared with previous studies.

A guidance assistance strategy for intersections based on vehicle speed prediction sequences

To improve the efficiency of urban traffic systems and environments, a speed guidance model based on a predictive vehicle speed sequence is proposed in this study. The model introduces a multi-step model of vehicle speed prediction based on nonlinear autoregressive models with a multi-source exogenous inputs (NARXs) neural network, with fusion of multi-source exogenous inputs into the speed guidance model to assist the vehicles in efficiently passing the intersections. The implementation of traffic flow simulation of urban road networks was established using SUMO-Python software, and experiments were carried out from the two dimensions of different speed guidance models and traffic networks with different numbers of lanes. The results demonstrate that the guidance accuracy of the proposed guidance strategy is higher than that of the previous vehicle speed guidance strategy, which can be improved by 16.5 %, significantly reducing the idle time of vehicles at intersections and improving urban traffic safety and operational efficiency. Moreover, the proposed speed guidance strategy is applicable to different urban road networks, which can reduce fuel consumption and pollutant emissions to a greater extent, efficiently improving the economy, sustainability, and operational environment of urban traffic.

Simulation-Based Testing and Performance Evaluation of Vehicle Safety Functions

<div>The progressive development toward highly automated driving poses major challenges for the release and validation process in the automotive industry, because the immense number of test kilometers that have to be covered with the vehicle cannot be tackled to any extent with established test methods, which are highly focused on the real vehicle. For this reason, new methodologies are required. Simulation-based testing and, in particular, virtual driving tests will play an important role in this context. A basic prerequisite for achieving a significant reduction in the test effort with the real vehicle through these simulations are realistic test scenarios. For this reason, this article presents a novel approach for generating relevant traffic situations based on a traffic flow simulation in SUMO and a vehicle dynamics simulation in CarMaker. The procedure is shown schematically for an emergency braking function. A driving function under test faces the major challenges when the other road users commit driving errors. Therefore, the driving behavior models in this traffic flow simulation are modified in such a way that critical scenarios can arise because of these driving errors. In order to be able to make a statement about the correct behavior of the driving function under test in these traffic situations, objective criteria are necessary to evaluate the triggering behavior and the handling of the traffic situations. Based on the performance evaluation of the driving function under test, characteristic test scenarios are then identified that evenly cover the test space. The comparison of the deviations in covering this test space with full and the reduced dataset is small except in areas where there are no scenarios in both datasets. Finally, these selected scenarios are used to perform an application of the driving function under test. The procedure is exemplified for the triggering time and the maximum deceleration of an emergency braking function. When comparing the distributions, it is shown that the performance in both datasets improves in the same way when parameters are optimized. For example, the mean performance of the driving function increases by more than 0.3 in each case when optimizing the triggering time. Thus, it is no longer necessary to use all scenarios for parameterization in virtual driving tests.</div>

LWR and shockwave analysis - Failures under a concave fundamental diagram and unexpected induced disturbances

This paper undertakes a detailed empirical study of traffic dynamics on a freeway. The results show the traffic dynamics that systematically determine the shape of the fundamental diagram, FD, can also violate the stationarity assumptions of both shockwave analysis and Lighthill, Whitham and Richard's models, thereby inhibiting the applicability of these classical macroscopic traffic flow theories. The outcome is challenging because there is no way to identify the problem using only the macroscopic detector data. The research examines conditions local to vehicle detector stations to establish the FD while the single vehicle passage method is used to analyze the composition of vehicles underlying the aggregate samples. Then, traffic states are correlated between successive stations to measure the actual signal velocities and show they are inconsistent with the classical theories. This analysis also revealed that conditions in one lane can induce signals in another lane. Rather than exhibiting a single signal passing a given point in time and space, the induced and intrinsic signals are superimposed on one another in the given lane. We suspect the subtle dynamics revealed in this research have gone unnoticed because they are far below the resolution of conventional traffic monitoring. The findings could have implications to other traffic flow models that rely on the FD, so care should be taken to assess if a given model is potentially sensitive to the non-stationary dynamics presented herein.The results have a direct impact on practice. Traffic flow theory is a critical input to many aspects of surface transportation, e.g., traffic management, traffic control, network design, vehicle routing, traveler information, and transportation planning all depend on models or simulation software that are based upon traffic flow theory. If the underlying traffic flow theory is flawed it puts the higher level applications at risk. So, the findings in this paper should lead to caution in accepting the predictions from traffic flow models and simulation software when the traffic exhibits a concave FD.

AN APPLICATION OF AGENT-BASED TRAFFIC FLOW MODEL FOR MARITIME SAFETY MANAGEMENT EVALUATION

This paper aims to analyse maritime traffic safety assessment via a traffic flow simulation model. The model developed via NetLogo platform, agent-based modelling and simulation approach. And it is implemented on an open sea area, at the Aegean Sea to show its applicability. The model is verified through experiments conducted in the area. The simulation outputs give the risky locations and scores. Risky locations and risk scores in the area are determined as the outputs of the simulation runs. A traffic separation scheme is established to prove the suitability of the model as adaptable and updatable. After the scheme is implemented, it shows that the potential collision locations and scores change considerably. The developed model is convenient to simulate various conditions by changing the input parameters on maritime traffic safety

An integrated resilience assessment model of urban transportation network: A case study of 40 cities in China

The transportation network is essential in providing daily accessibility and essential service to societies. An acceptable level of service needs to be maintained in critical infrastructures, even in the case of disruptions. We develop an integrated model to assess the resilience of urban transportation networks when exposed to different disruptions. Resilience is evaluated from perspectives of both traffic network topology and traffic flow. This model contains three parts: (1) a traffic flow simulation model to get flow distributed throughout the whole network, (2) different real-world disruptions are abstracted as random, localized, and flood disturbances, (3) functional and topological resilience are accessed by analyzing variations in travel time and connected components before and after a disruption occurs. 40 major cities are chosen to conduct resilience assessments. As the intensity of the disruption increases, common trends in the changes of functional and topological resilience values are observed and analyzed across all studied cities. In most cases, flood disruption is the least disruptive one of all three types of disruptions. Regression models are developed to estimate functional and topological resilience after random, localized, and flood disturbances. Possible resilience enhancement strategies are discussed based on analyses of regression models. This study could aid stakeholders in gaining a clear understanding of resilience not only topologically but also from the perspective of traffic flow and offer them practical strategies to enhance resilience in face of disruptions.

Simulation-based quantitative methods for vehicle emissions and a CO2 charging policy

With the worsening vehicle emissions, carbon emission charges are becoming an increasingly popular policy to reduce emissions. This paper proposes a policy to charge for the additional CO2 emissions due to the increasing traffic flow for each vehicle, thereby extending traditional travel time-based traffic assignment to emissions-charged traffic assignment. Considering that vehicle movements in the network are affected by signal timings and the car-following together with lanechanging interactions of different types of vehicles, microscopic traffic flow simulation is combined with a CO2 emission model to formulate the relations between link flow and emissions of different types of vehicles. Accordingly, the additional CO2 emissions due to increasing traffic flow are quantified and charged for each vehicle, leading to multi-vehicle-type and multi-criteria traffic assignment. Through an example network, the proposed flow-emissions model is verified and the impacts of different CO2 charging prices in the morning peak hour are investigated. Analysis of the results shows monotone increasing relations between price and reduced total emissions as well as increased revenue within the price range. In addition, the charging policy also leads to traffic assignment that achieves a system-optimal assignment since the CO2 pricing aligns with the general concept of pricing externality, thereby reducing the total travel time.