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Journal articles on the topic 'Traffic flow modelling'

Author: Grafiati

Published: 4 June 2021

Last updated: 7 September 2023

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1

Ahmed, Afzal, Mir Shabbar Ali, and Toor Ansari. "Modelling Heterogeneous and Undisciplined Traffic Flow using Cell Transmission Model." International Journal of Traffic and Transportation Management 02, no. 01 (November 11, 2020): 01–05. http://dx.doi.org/10.5383/jttm.02.01.001.

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This research calibrates Cell Transmission Model (CTM) for heterogeneous and non-lane disciplined traffic, as observed in Pakistan and some other developing countries by constructing a flow-density fundamental traffic flow diagram. Currently, most of the traffic simulation packages used for such heterogonous and non-lane-disciplined traffic are not calibrated for local traffic conditions and most of the traffic flow models are developed for comparatively less heterogeneous and lane-disciplined traffic. The flow-density fundamental traffic flow diagram is developed based on extensive field data collected from Karachi, Pakistan. The calibrated CTM model is validated by using actual data from another road and it was concluded that CTM is capable of modelling heterogeneous and non-lane disciplined traffic and performed very reasonably. The calibrated CTM will be a useful input for the application of traffic simulation and optimization packages such as TRANSYT, SIGMIX, DISCO, and CTMSIM.

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2

Guseynov, Sharif E., and Alexander V. Berezhnoy. "MODELLING OF URBAN TRAFFIC FLOW." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 1 (June 15, 2017): 109. http://dx.doi.org/10.17770/etr2017vol1.2632.

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In this paper non-deterministic motion of urban traffic is studied under certain assumptions. Based on those assumptions discrete and continuous mathematical models are developed: continuous model is written as the Cauchy initial-value problem for the integro-differential equation, whence among other things it is obtained the Fokker-Planck equation. Besides, the sufficient condition ensuring the mathematical legitimacy of the developed continuous model is formulated.

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3

Mercier, Magali. "Traffic flow modelling with junctions." Journal of Mathematical Analysis and Applications 350, no. 1 (February 2009): 369–83. http://dx.doi.org/10.1016/j.jmaa.2008.09.040.

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4

Bonzani, I., and L. Mussone. "Stochastic modelling of traffic flow." Mathematical and Computer Modelling 36, no. 1-2 (July 2002): 109–19. http://dx.doi.org/10.1016/s0895-7177(02)00107-3.

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5

Kushchenko, L., and R. Dubrov. "Traffic flow modelling to reduce traffic block process." Актуальные направления научных исследований XXI века: теория и практика 3, no. 4 (October 26, 2015): 356–59. http://dx.doi.org/10.12737/13965.

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6

Chronopoulos, A., A. Lyrintzis, P. Michalopoulos, C. Rhee, and P. Yi. "Traffic flow simulation through high order traffic modelling." Mathematical and Computer Modelling 17, no. 8 (April 1993): 11–22. http://dx.doi.org/10.1016/0895-7177(93)90150-w.

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7

Junevičius, Raimundas, and Marijonas Bogdevičius. "MATHEMATICAL MODELLING OF NETWORK TRAFFIC FLOW." TRANSPORT 24, no. 4 (December 31, 2009): 333–38. http://dx.doi.org/10.3846/1648-4142.2009.24.333-338.

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The article describes mathematical models of traffic flows to initiate different traffic flow processes. Separate elements of traffic flow models are made in a way to be connected together to get a single complex model. A model of straight road with different boundary conditions is presented as a separate part of the network traffic flow model. First testing is conducted in case the final point of the whole modelled traffic line is closed and no output from that point is possible. The second test is performed when a constant value of traffic flow speed and traffic flow rate is entered. Mathematical simulation is carried out and the obtained results are listed.

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Jin, Sheng, Lixiao Shen, Meiqi Liu, and Dongfang Ma. "Modelling speed–flow relationships for bicycle traffic flow." Proceedings of the Institution of Civil Engineers - Transport 170, no. 4 (August 2017): 194–204. http://dx.doi.org/10.1680/jtran.15.00115.

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Wen, Yuanqiao, Yamin Huang, Chunhui Zhou, Junlan Yang, Changshi Xiao, and Xiaochun Wu. "Modelling of marine traffic flow complexity." Ocean Engineering 104 (August 2015): 500–510. http://dx.doi.org/10.1016/j.oceaneng.2015.04.051.

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10

Junevičius, Raimundas, and Marijonas Bogdevičius. "DETERMINATION OF TRAFFIC FLOW PARAMETERS IN DIFFERENT TRAFFIC FLOW INTERACTION CASES." TRANSPORT 22, no. 3 (September 30, 2007): 236–39. http://dx.doi.org/10.3846/16484142.2007.9638131.

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Modelling of straight road section consisting of one traffic line gives the opportunity to simulate “follow the car” system. In general it looks like a line of vehicles, going one after another. Kinetic theory, used in this paper describes traffic flow system as a straight unbroken line with limited flow speed and concentration. Such model also gives the opportunity to derive traffic lines intersections. For example, intersection could be derived like a point with traffic lines coming and outgoing from this point by only changing boundary conditions. Mathematical model is built using characteristic method.

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11

Arasan, Venkatachalam Thamizh, and Shriniwas Shrikant Arkatkar. "MODELLING HETEROGENEOUS TRAFFIC FLOW ON UPGRADES OF INTERCITY ROADS." TRANSPORT 25, no. 2 (June 30, 2010): 129–37. http://dx.doi.org/10.3846/transport.2010.16.

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The effect of an upgrade and its length is very significant for traffic flow characteristics. Road traffic in developing countries like India is highly heterogeneous comprising vehicles of wide ranging physical dimensions, weight and dynamic characteristics such as engine power, acceleration rate, etc. Due to these variations, the effect of grade on vehicles in heterogeneous traffic may vary significantly among vehicle categories. Variation in the level of the interaction between vehicles on upgrades may result in different sets of traffic flow characteristics. Hence, it is necessary to model traffic flow on upgrades and study, in depth, changes in traffic flow characteristics with alteration in the magnitude of an upgrade and its length. Computer simulation has emerged as an effective technique for modelling traffic flow due to its capability to account for randomness related to traffic. This study is concerned with applying a simulation model of heterogeneous traffic flow, named HETEROSIM, to study the traffic flow characteristics and performance of different vehicle types on upgrades of different magnitudes.

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12

Kerner, B. S. "Experimental Characteristics of Traffic Flow for Evaluation of Traffic Modelling." IFAC Proceedings Volumes 30, no. 8 (June 1997): 765–70. http://dx.doi.org/10.1016/s1474-6670(17)43914-0.

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13

Myronenko, Sergiy, and Dominique Gillis. "Modelling of road traffic for traffic flow optimization of modern regional center as an example of Odessa, Ukraine." Odes’kyi Politechnichnyi Universytet. Pratsi, no. 3 (December 23, 2016): 41–45. http://dx.doi.org/10.15276/opu.3.50.2016.10.

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14

Mallikarjuna, Ch, and K. Ramachandra Rao. "Heterogeneous traffic flow modelling: a complete methodology." Transportmetrica 7, no. 5 (September 2011): 321–45. http://dx.doi.org/10.1080/18128601003706078.

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15

Papageorgiou, Markos. "Some remarks on macroscopic traffic flow modelling." Transportation Research Part A: Policy and Practice 32, no. 5 (September 1998): 323–29. http://dx.doi.org/10.1016/s0965-8564(97)00048-7.

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16

Borah, Kaustav Jyoti, and Abul Abbas Barbhuiya. "Stochastic modelling for traffic flow: a review." International Journal of Intelligent Systems Design and Computing 1, no. 3/4 (2017): 262. http://dx.doi.org/10.1504/ijisdc.2017.090873.

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Borah, Kaustav Jyoti, and Abul Abbas Barbhuiya. "Stochastic modelling for traffic flow: a review." International Journal of Intelligent Systems Design and Computing 1, no. 3/4 (2017): 262. http://dx.doi.org/10.1504/ijisdc.2017.10011927.

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18

Junker, Ulrich. "Air traffic flow management with heuristic repair." Knowledge Engineering Review 27, no. 3 (July 26, 2012): 333–42. http://dx.doi.org/10.1017/s0269888912000240.

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AbstractThe European air traffic flow management problem poses particular challenges on optimization technology as it requires detailed modelling and rapid online optimization capabilities. Constraint programming proved successful in addressing these challenges for departure time slot allocation by offering fine-grained modelling of resource constraints and fast allocation through heuristic-repair strategies.

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19

Kerner, B. S. "Synchronized flow as a new traffic phase and related problems for traffic flow modelling." Mathematical and Computer Modelling 35, no. 5-6 (March 2002): 481–508. http://dx.doi.org/10.1016/s0895-7177(02)80017-6.

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20

Olayode, Isaac Oyeyemi, Lagouge Kwanda Tartibu, and Tiziana Campisi. "Stability Analysis and Prediction of Traffic Flow of Trucks at Road Intersections Based on Heterogenous Optimal Velocity and Artificial Neural Network Model." Smart Cities 5, no. 3 (September 2, 2022): 1092–114. http://dx.doi.org/10.3390/smartcities5030055.

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The evolution of traffic-related accidents caused by long, short, and medium trucks at signalized road intersections have been underemphasized in the last few years. Far, little attention has been paid to the modelling of trucks traffic flow using an artificial neural network model and evaluating the stability analysis of trucks depending on the heterogenous optimal velocity. This research evaluates the effect of trucks on some specific traffic flow features. Over the years, it has been deduced that trucks, irrespective of their sizes, significantly impact their surrounding traffic flow due to their body sizes and operational features. In this study, we focused on modelling the traffic flow of trucks at signalized road intersections using traffic flow variables such as speed, traffic volume, traffic density, and time as our inputs and outputs. The truck traffic data was collected using up-to-date equipment such as video cameras and inductive loop detectors from the South Africa transportation network. During the ANN modelling of the truck traffic flow, we used 956 traffic datasets divided into 70% for training and 15% each for testing and validation. The ANN model results show testing regression values of R2 (0.99901). This shows that the inputs and output are well correlated and the ANN model’s superiority in predicting truck traffic flow at signalized road intersections. Based on the HEOV model results, the result of the research indicates that in the mixed traffic flow of trucks in real-life scenarios, the proportion of different trucks on the signalized road intersections rather than the proportions of types of trucks can be used in the determination of traffic flow stability of each truck. This research extends our knowledge of truck traffic flow modelling and provides a blueprint for examining the stability analysis of long, short, and medium trucks in their immediate driving environment.

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21

ZHANG, Huiling, and Bangshun XI. "Heterogeneous Pedestrian Traffic Flow Modelling at Signalised Intersections." Promet - Traffic&Transportation 34, no. 2 (March 31, 2022): 165–77. http://dx.doi.org/10.7307/ptt.v34i2.3829.

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Different types of pedestrians exhibit different speed characteristics and heterogeneity. In the case of mixed pedestrian flow at signalised intersections, pedestrian traffic flow modelling is important in research of the con-ditions at signalised intersections and the evaluation of services for pedestrians. The characteristics of pedestri-an traffic flow at signalised intersections were investi-gated in this study against the background of pedestrian heterogeneity using videos of pedestrians crossing three signalised intersections in Chongqing recorded in a field survey. The pedestrian walking speeds were manually ex-tracted from the videos and used as the data basis for dis-tinguishing pedestrian heterogeneity. The walking speed data of three types (young, middle-aged, and elderly) of pedestrians at different pedestrian flows were obtained by using a microsimulation software. Based on this, a pe-destrian traffic flow model for mixed-type pedestrians at signalised intersections was established and verified by actual cases. In comparison with the HCM model, the model outperforms the HCM model overall in practical applications, indicating its strong applicability and reli-ability.

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22

IORDANOVA, Violina, Hassane ABOUAÏSSA, and Daniel JOLLY. "BOND-GRAPHS TRAFFIC FLOW MODELLING AND FEEDBACK CONTROL." IFAC Proceedings Volumes 39, no. 3 (2006): 345–50. http://dx.doi.org/10.3182/20060517-3-fr-2903.00186.

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23

McCartney, Mark, and Malachy Carey. "Modelling Traffic Flow: Solving and Interpreting Differential Equations." Teaching Mathematics and its Applications: An International Journal of the IMA 18, no. 3 (September 1, 1999): 115–21. http://dx.doi.org/10.1093/teamat/18.3.115.

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24

McCartney, M. "Modelling traffic flow; interpreting roots and applying summations." Teaching Mathematics and its Applications 19, no. 1 (March 1, 2000): 21–29. http://dx.doi.org/10.1093/teamat/19.1.21.

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25

WANG, RUILI, and H. J. RUSKIN. "MODELLING TRAFFIC FLOW AT MULTI-LANE URBAN ROUNDABOUTS." International Journal of Modern Physics C 17, no. 05 (May 2006): 693–710. http://dx.doi.org/10.1142/s0129183106008777.

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This paper proposes Multi-stream Minimum Acceptable Space (MMAS) Cellular Automata (CA) models to study unsignalised multi-lane (two- or three-lane) urban roundabouts. Through detailed space considerations, using Cellular Automata (CA) and the Multi-stream Minimum Acceptable Space method, heterogeneity and inconsistency of driver behavior and interactions in cross traffic at entrances of roundabouts are simulated by incorporation of four different categories of driver behavior (i.e., conservative, moderate, urgent and radical), together with reassignment of categories with given probabilities at each time step. The method is able to reproduce many features of urban traffic, for which gap-acceptance models are not robust. Multi-lane roundabout models, in particular for two-lane roundabouts, are developed with different vehicle lane-allocation patterns. Various properties of multi-lane roundabout operations have been explored including throughput, turning rates, critical arrival rates and congestion. The operations of two- and three-lane roundabouts are compared in terms of throughputs. Vehicle movements in this paper relate to left-side driving, such as found in Ireland, New Zealand and the UK. However, results are generally applicable to the countries where the give-way rule is applied.

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26

Smirnova, M. N., A. Bogdanova, Zuojin Zhu, and N. N. Smirnov. "Traffic flow sensitivity to parameters in viscoelastic modelling." Transportmetrica B: Transport Dynamics 5, no. 1 (April 11, 2016): 111–27. http://dx.doi.org/10.1080/21680566.2016.1142402.

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27

Mohan, Ranju, and Gitakrishnan Ramadurai. "Heterogeneous Traffic Flow Modelling Using Macroscopic Continuum Model." Procedia - Social and Behavioral Sciences 104 (December 2013): 402–11. http://dx.doi.org/10.1016/j.sbspro.2013.11.133.

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28

Nakrachi, Abdelaziz, Said Hayat, and Dumitru Popescu. "An energy concept for macroscopic traffic flow modelling." European Transport Research Review 4, no. 2 (January 28, 2012): 57–66. http://dx.doi.org/10.1007/s12544-012-0070-0.

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29

Faza, Ahmad, and Friska Natalia. "Modelling of Traffic Flow on West Jakarta Highways." International Journal of Engineering and Technology 10, no. 3 (June 30, 2018): 658–66. http://dx.doi.org/10.21817/ijet/2018/v10i3/181003002.

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30

Savrasovs, Mihails. "Traffic Flow Simulation on Discrete Rate Approach Base." Transport and Telecommunication Journal 13, no. 2 (January 1, 2012): 167–73. http://dx.doi.org/10.2478/v10244-012-0014-8.

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Traffic Flow Simulation on Discrete Rate Approach Base The classical scientific literature dedicated to transport modelling has emphasised three levels of detail on which traffic models could be created. These levels are: microlevel, mesolevel and macroscopic level. Microscopic and macroscopic modelling are well known and widely used. The term ‘mesoscopic modelling’ has been interpreted by different scientists in different ways. In general, mesoscopic traffic flow models are understood to be models where traffic flow is described with a high level of detail, but at the same time flow behaviour and flow interactions are presented with a low level of description. The previously proposed new simulation approach (called ‘mesoscopic simulation’) was applied to traffic flow simulation. All the described models were implemented using Microsoft Excel and VBA. However, the practical application concerns that to construct more sophisticated models Microsoft Excel and VBA could not be used, because of programming complexity. The main goal of this paper is to present examples of the application of the discrete rate approach of ExtendSim simulation software for traffic flow simulation. A literature survey has shown that the discrete rate approach is mainly used in logistics, but not in the area of transport area. So the tasks of this paper are to present the main techniques of model implementation using a discrete rate approach and to apply this approach to traffic flow simulation.

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31

Billones, Robert Kerwin C., Argel A. Bandala, Laurence A. Gan Lim, Edwin Sybingco, Alexis M. Fillone, and Elmer P. Dadios. "Microscopic Road Traffic Scene Analysis Using Computer Vision and Traffic Flow Modelling." Journal of Advanced Computational Intelligence and Intelligent Informatics 22, no. 5 (September 20, 2018): 704–10. http://dx.doi.org/10.20965/jaciii.2018.p0704.

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This paper presents the development of a vision-based system for microscopic road traffic scene analysis and understanding using computer vision and computational intelligence techniques. The traffic flow model is calibrated using the information obtained from the road-side cameras. It aims to demonstrate an understanding of different levels of traffic scene analysis from simple detection, tracking, and classification of traffic agents to a higher level of vehicular and pedestrian dynamics, traffic congestion build-up, and multi-agent interactions. The study used a video dataset suitable for analysis of a T-intersection. Vehicle detection and tracking have 88.84% accuracy and 88.20% precision. The system can classify private cars, public utility vehicles, buses, and motorcycles. Vehicular flow of every detected vehicles from origin to destination are also monitored for traffic volume estimation, and volume distribution analysis. Lastly, a microscopic traffic model for a T-intersection was developed to simulate a traffic response based on actual road scenarios.

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32

Moutari, S., M. Herty, A. Klein, M. Oeser, B. Steinauer, and V. Schleper. "Modelling road traffic accidents using macroscopic second-order models of traffic flow." IMA Journal of Applied Mathematics 78, no. 5 (July 17, 2012): 1087–108. http://dx.doi.org/10.1093/imamat/hxs012.

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33

Babojelić, Karlo, and Luka Novacko. "Modelling of Driver and Pedestrian Behaviour – A Historical Review." Promet - Traffic&Transportation 32, no. 5 (October 5, 2020): 727–45. http://dx.doi.org/10.7307/ptt.v32i5.3524.

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Driver and pedestrian behaviour significantly affect the safety and the flow of traffic at the microscopic and macroscopic levels. The driver behaviour models describe the driver decisions made in different traffic flow conditions. Modelling the pedestrian behaviour plays an essential role in the analysis of pedestrian flows in the areas such as public transit terminals, pedestrian zones, evacuations, etc. Driver behaviour models, integrated into simulation tools, can be divided into car-following models and lane-changing models. The simulation tools are used to replicate traffic flows and infer certain regularities. Particular model parameters must be appropriately calibrated to approximate the realistic traffic flow conditions. This paper describes the existing car-following models, lane-changing models, and pedestrian behaviour models. Further, it underlines the importance of calibrating the parameters of microsimulation models to replicate realistic traffic flow conditions and sets the guidelines for future research related to the development of new models and the improvement of the existing ones.

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34

Junevičius, Raimundas, Marijonas Bogdevičius, and Ádám Török. "MODELLING OF INTERNAL COMBUSTION ENGINES’ EMISSION THROUGH THE USE OF TRAFFIC FLOW MATHEMATICAL MODELS." TRANSPORT 26, no. 3 (October 5, 2011): 271–78. http://dx.doi.org/10.3846/16484142.2011.621978.

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Road traffic flows on a straight road segment are modelled in this article. The mathematical model of traffic flows has been constructed by using the method of lumped parameters. CO2, CO, CH, NOx, PM regression equations of internal combustion engines’ (ICE) emission has been developed. The accuracy of regression equations is 0.98÷0.99. The article presents assumptions for constructing the mathematical model, description of the mathematical model and gives simulation results. Traffic flow parameters, such as traffic flow concentration and traffic flow speed are presented as modelling results. ICE emission depending on the concentration and traffic flow speed are presented as well.

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35

Shaharuddin, Raihanah Adawiyah, and Md Yushalify Misro. "Controlling Traffic Congestion in Urbanised City: A Framework Using Agent-Based Modelling and Simulation Approach." ISPRS International Journal of Geo-Information 12, no. 6 (May 31, 2023): 226. http://dx.doi.org/10.3390/ijgi12060226.

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Urbanised city transportation simulation needs a wide range of factors to reflect the influence of certain real-life events accurately. The vehicle composition and the timing of the traffic light signal scheduling play an important role in controlling the traffic flow and facilitate road users, particularly in densely populated urban cities. Since road capacity in urban cities changes throughout the day, an optimal traffic light signal duration might be different. Hence, in this paper, the effect of vehicle composition and traffic light phases on traffic flow during peak and off-peak hours in Georgetown, Penang, one of the highly populated cities in Malaysia, is investigated. Through Agent-Based Modelling (ABM), this complex system is simulated by integrating the driver’s behaviour into the model using the GIS and Agent-Based Modelling Architecture (GAMA) simulation platform. The result of predicted traffic flow varies significantly depending on the vehicle composition while the duration of the traffic signal timing has little impact on traffic flow during peak hours. However, during off-peak hour, it is suggested that 20 s duration of green light provides the highest flow compared to 30 s and 40 s duration of green light. This concludes that the planning for traffic light phasing should consider multiple factors since the vehicle composition and traffic light timing for an effective traffic flow varies according to the volume of road users.

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36

Bie, Yuwei, Tony Z. Qiu, Can Zhang, and Cunbao Zhang. "Introducing Weather Factor Modelling into Macro Traffic State Prediction." Journal of Advanced Transportation 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/4879170.

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Adverse weather has significant impacts on road conditions and traffic dynamics. It is observed that adverse weather as a set of exogenous factors lowers the free flow speed, shifts critical density, decreases flow capacity, and makes the freeway more prone to congestion. This paper proposes a weather factor model to be plugged into a macroscopic traffic prediction model, so that under bad weather traffic variables can be more accurately and reasonably estimated and predicted for traffic control use. To be specific, weather-specific fundamental diagrams are built by introducing weather factors to free flow speed, capacity, and critical density. The weather factors are modelled by selected weather measurements. Weather factor parameters are trained by recent historical weather and traffic data and then can be put into real-time macro traffic prediction and control. The traffic prediction model in the case study is METANET model, in which fundamental diagram parameters are one source of input. The weather-specific prediction error and conventional prediction error are compared. Real data collected by loop detectors on Whitemud Drive, Edmonton, Canada, is used for parameter calibration and prediction error evaluation. The results show that the proposed weather models reasonably improved the accuracy of macro traffic state prediction model compared to conventional model.

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Kutlimuratov, Kudrat, Shaukat Khakimov, Akmal Mukhitdinov, and Rustam Samatov. "Modelling traffic flow emissions at signalized intersection with PTV vissim." E3S Web of Conferences 264 (2021): 02051. http://dx.doi.org/10.1051/e3sconf/202126402051.

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The effect of roadway intersection design is strictly linked to a reduction in traffic congestion, fuel consumption and emissions in an urban area. This paper presents a comparative result of the typical four-legged intersection and roundabout operational performance for effective management. Accordingly, a computer model for estimation traffic emissions for two kinds of intersections is created. This study presents a detailed analysis and modelling traffic flow emissions using PTV vissim software and methodology with reasonable solutions to plan a road intersection.

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38

Jacyna, Marianna, Jolanta Żak, and Piotr Gołębiowski. "USE OF QUEUEING THEORY FOR THE ANALYSIS OF TRANSPORT PROCESSES." Logistics and Transport, no. 41 (2019): 101. http://dx.doi.org/10.26411/83-1734-2015-1-41-12-19.

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This article focuses on the application of queueing theory for the analysis of transport processes with regard to rail traffic. Selected aspects of queueing theory application for the analysis and rail traffic flow assessment were presented. A literature review regarding process modelling in rail transport using mass service theory models was performed. In order to study rail traffic flow, the application Java Modelling Tools- JSIMgraph was used. The train movement process was analysed with regard to traffic flow. The study was conducted on the basis of selected stretches of railway lines, numbers 2 (central long-distance in Warsaw) and 448 (central suburban in Warsaw).

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39

Wiewióra, Mikołaj, and Łukasz Drąg. "Modelling of car exhaust emission on the basis of data obtained from microscopic traffic flow model." AUTOBUSY – Technika, Eksploatacja, Systemy Transportowe 19, no. 6 (June 30, 2018): 786–89. http://dx.doi.org/10.24136/atest.2018.175.

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In the paper the procedure for car exhaust emission calculation along the road network has been presented. Input parameters for an emission model were obtained from the microscopic traffic flow model. Traffic simulations have been performed in Vissim software. To analyse emission in a road sections whole network has been discretized into fixed length segments. The examples of traffic flow emission modelling for selected lanes at intersection where the traffic flow is controlled by traffic lights are also presented.

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40

Zhou, Shaobo, Xiaodong Zang, Junheng Yang, Wanying Chen, Jiahao Li, and Shuyi Chen. "Modelling the Coupling Relationship between Urban Road Spatial Structure and Traffic Flow." Sustainability 15, no. 14 (July 17, 2023): 11142. http://dx.doi.org/10.3390/su151411142.

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In order to promote the sustainable development of urban traffic systems, improve the accuracy of traffic system analysis in the urban planning stage and reduce the possibility of traffic congestion in the operation stage of road networks, the coupling relationship and evolution mechanism between urban road spatial structure and traffic flow were studied, and a model of the relationship between the metrics was established in this study based on real road network and traffic flow data. First, the road spatial structure model of the study area was established from the perspective of road space, and the spatial syntax method was applied to verify the rationality of the spatial structure of the road network. Secondly, the initial OD matrix was determined by OD backpropagation based on the measured traffic flow data. Thirdly, the coupling rule between the spatial structure and the traffic flow of the road network was explored by loading the increment in the OD matrix to the initial OD matrix step by step based on a simulation experiment. Finally, the relationship between the degree of integration of the spatial syntactic feature parameter and the saturation of the traffic flow feature parameter was modelled on the basis of experimental results and verified by an example. This research shows that the spatial structure of urban roads has a significant impact on the characterisation of the traffic flow distribution of road networks, and a strong correlation can be found between the integration degree and saturation degree. An optimal fit, which can be used as a reference for the design of road spatial structure, was explored in this research.

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41

Diveev, A. I., A. D. Kochkin, K. A. Pupkov, and E. A. Sofronova. "Traffic Flow Modelling Approach Based on the Controlled Networks." IFAC Proceedings Volumes 45, no. 24 (September 2012): 309–14. http://dx.doi.org/10.3182/20120912-3-bg-2031.00065.

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42

Herty, Michael, S. Moutari, and M. Rascle. "Optimization criteria for modelling intersections of vehicular traffic flow." Networks & Heterogeneous Media 1, no. 2 (2006): 275–94. http://dx.doi.org/10.3934/nhm.2006.1.275.

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43

Tordeux, Antoine, Michel Roussignol, Jean-Patrick Lebacque, and Sylvain Lassarre. "A stochastic jump process applied to traffic flow modelling." Transportmetrica A: Transport Science 10, no. 4 (March 6, 2013): 350–75. http://dx.doi.org/10.1080/23249935.2013.769648.

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Hoogendoorn, S. P., and P. H. L. Bovy. "State-of-the-art of vehicular traffic flow modelling." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 215, no. 4 (June 2001): 283–303. http://dx.doi.org/10.1177/095965180121500402.

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Li, Tong. "Modelling traffic flow with a time-dependent fundamental diagram." Mathematical Methods in the Applied Sciences 27, no. 5 (March 1, 2004): 583–601. http://dx.doi.org/10.1002/mma.470.

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Mohan, Ranju, and Gitakrishnan Ramadurai. "State-of-the art of macroscopic traffic flow modelling." International Journal of Advances in Engineering Sciences and Applied Mathematics 5, no. 2-3 (August 15, 2013): 158–76. http://dx.doi.org/10.1007/s12572-013-0087-1.

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Savrasovs, Mihails, Irina Pticina, Valery Zemlyanikin, and Ioannis Karakikes. "Demand Data Modelling for Microscopic Traffic Simulation." Transport and Telecommunication Journal 19, no. 4 (December 1, 2018): 364–71. http://dx.doi.org/10.2478/ttj-2018-0031.

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Abstract The current paper aim is to present the technique of demand data modelling for microscopic simulation of the traffic flows. Traffic microscopic simulation is a powerful decision supporting tool, which could be applied for a wide range of tasks. In a past microscopic traffic simulation was used to test local changes in transport infrastructure, but the growth of computers performance allows now to simulate wide-scale fragments of the traffic network and to apply more advanced traffic flow simulation approaches, like an example dynamic assignment (DA). The results, obtained in the frame of this research are part of the project completed for one of the shopping malls (Riga, Latvia). The goal of the project was to evaluate different development scenarios of the transport network to raise the accessibility of the shopping mall. The number of practical issues in the frame of this project pushed to develop a new technique to model the demand data for the simulation model. As a traffic flow simulation tool, the PTV VISSIM simulation software was applied. The developed model was based on dynamic assignment approach. To complete the simulation the demand data was represented in two forms: 1) OD matrix for regular traffic in the transport network; 2) trip-chain file for a description of the pass-by and targeted trips.

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Zhang, Honghai, Yan Xu, Lei Yang, and Hao Liu. "Macroscopic Model and Simulation Analysis of Air Traffic Flow in Airport Terminal Area." Discrete Dynamics in Nature and Society 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/741654.

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We focus on the spatiotemporal characteristics and their evolvement law of the air traffic flow in airport terminal area to provide scientific basis for optimizing flight control processes and alleviating severe air traffic conditions. Methods in this work combine mathematical derivation and simulation analysis. Based on cell transmission model the macroscopic models of arrival and departure air traffic flow in terminal area are established. Meanwhile, the interrelationship and influential factors of the three characteristic parameters as traffic flux, density, and velocity are presented. Then according to such models, the macro emergence of traffic flow evolution is emulated with the NetLogo simulation platform, and the correlativity of basic traffic flow parameters is deduced and verified by means of sensitivity analysis. The results suggest that there are remarkable relations among the three characteristic parameters of the air traffic flow in terminal area. Moreover, such relationships evolve distinctly with the flight procedures, control separations, and ATC strategies.

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Simeunović, Milja M., Vuk Z. Bogdanović, Milan M. Simeunović, Pavle M. Pitka, Zoran M. Papić, and Dane M. Drašković. "The Model of the Optimal Number of Public Transport Vehicles in Mixed Traffic Flow Conditions: A Case Study." Discrete Dynamics in Nature and Society 2021 (August 18, 2021): 1–19. http://dx.doi.org/10.1155/2021/5276323.

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Bus passenger transport is very important for sustainable urban mobility, and due to the characteristics of the street network, it is usually realized in the conditions of mixed traffic flow. Disturbances and sudden changes of traffic flow parameters occurring in the street network in a mixed traffic flow affect the disruptions in schedule and travel time of all vehicles in the traffic flow, including public transport (PT) vehicles. In order to keep to the planned schedule in the peak hours of PT lines carried out in the conditions of mixed traffic flow, the operators introduce new vehicles or reduce the vehicles’ dwell time at terminuses, which is often impossible to do. The use of a larger number of public transport vehicles increases the fuel consumption, pollutants’ emission, and the operating costs. In this paper, a network optimization model was developed for defining the influence of the change of traffic flow parameters in a mixed traffic flow on travel time of PT vehicles. The model takes into consideration uncertain time unevenness of the change of traffic flow parameters, which enables determining the optimization of travel time and defining the necessary number of public transport vehicles for the purpose of keeping to the planned schedule. In order to develop the transport model, counting and analysis of the characteristics of traffic flow at 61 intersections on the city territory were carried out. The model was tested on bus line number 4 of PT in Novi Sad. The model showed that it is possible to achieve certain savings regarding the number of vehicles with the unchanged headway, that is, the unchanged level of service which is offered to the users. With the application of the model in real traffic conditions, significant savings, as well as operating and external costs’ reduction, can be achieved, which contributes to the sustainability of public bus transport in urban environments.

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Jafaripournimchahi, Ammar, Yingfeng Cai, Hai Wang, Lu Sun, and Jiancheng Weng. "Integrated-Hybrid Framework for Connected and Autonomous Vehicles Microscopic Traffic Flow Modelling." Journal of Advanced Transportation 2022 (April 26, 2022): 1–16. http://dx.doi.org/10.1155/2022/2253697.

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In this study, a novel traffic flow modeling framework is proposed considering the impact of driving system and vehicle mechanical behavior as two different units on the traffic flow. To precisely model the behavior of Connected and Autonomous (CA) vehicles, three submodels are proposed as a novel microscopic traffic flow framework, named Integrated-Hybrid (IH) model. Focusing on the realization of the car following behavior of CA vehicles, the driving system (vehicle control system) and the vehicle mechanical system are modeled separately and linked by throttle and brake actuators model. The IH model constitutes the key part of the Full Velocity Difference (FVD) model considering the mechanical capability of vehicles and dynamic collision avoidance strategies to ensure the safety of following distance between two consecutive vehicles. Linear stability conditions are derived for each model and developing methodology for each submodel is discussed. Our simulations revealed that the IH model successfully generates velocity and acceleration profiles during car following maneuvers and throttle angle/brake information in connected vehicles environment can effectively improve traffic flow stability. The vehicles’ departure and arrival process while passing through a signal-lane with a traffic light considering the anticipation driving behavior and throttle angle/brake information of direct leading vehicle was explored. Our numerical results demonstrated that the IH model can capture the velocity fluctuations, delay times, and kinematic waves efficiently in traffic flow.

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