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Z. Phys. Chem. 224 (2010) 153–181 . DOI 10.1524.zpch.2010.6097 © by Oldenbourg Wissenschaftsverlag, München Dynamics in Clays - Combining Neutron Scattering and Microscopic Simulation By Natalie Malikova*, Emmanuelle Dubois, Virginie Marry, Benjamin Rotenberg, and Pierre Turq Laboratoire Léon Brillouin, UMR CEA-CNRS 12, CEA Saclay, Gif-sur-Yvette, 91191 France (Received May 4, 2009; accepted August 10, 2009) Clays . QENS . Microscopic Simulation Mobility of ions and water in clays is at the heart of their remarkable properties of water retention and ion

Urban Public Transport System's Reliability Estimation Using Microscopic Simulation

In the article the procedure of the reliability measures estimation for one route of the public transport network on the basis of a traffic flow modelling is suggested. A definition of UPTS reliability is based on the analysis of the Travel Time Reliability, Arrival Time Reliability and Probability of arriving to the stops with delay no more than m minutes. The approach is applied to the real task of the reliability estimation for Riga city public transport route. The microscopic model of transport network fragment is used for it.


Modern urban highways are under the influence of increased traffic demand and cannot fulfill the desired level of service anymore. In most of the cases there is no space available for any infrastructure building. Solutions from the domain of intelligent transport systems are used, such as ramp metering. To cope with the significant daily changes of the traffic demand, various approaches with autonomic properties like self-learning are applied for ramp metering. One of these approaches is reinforced learning. In this paper the Q-Learning algorithm is applied to learn the local ramp metering control law in a simulation environment, implemented in a VISSIM microscopic simulator. The approach proposed is tested in simulations with emphasis on the mainstream speed and travel time, using a typical on-ramp configuration.


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.


The article presents an analysis of the impact of transport on heavy urban traffic on Wharf Kwiatkowski using program PTV Vissim. The data for analysis were taken from the Road and Greenery in Gdynia from program PTV Visum. Attention has been focused on vehicle traffic in the afternoon the top of its intensity. Model of Kwiatkowskiego Wharf, made entirely in the PTV VISSIM, was used for microscopic simulation of traffic. With its help, it was possible to find and analyze the behavior of each autonomous vehicle and interactions on the Web. For the analysis was used as a program of traffic lights currency at these junctions. The analysis results of simulation in the PTV VISSIM are related to the movement of the two structures. The first assumes that the route will move cars and trucks, taking into account their share in the network based on the intensity of traffic during peak hours of the afternoon, the second consisted only of cars. The results presented are based on measuring the time of travel and delays on specific relationships and the average length of queues at selected inlets. The results of analysis and simulation tests were subjected to statistical analysis.

References Kühne, R. D., Rödiger, M. B. (1991). Macroscopic simulation model for freeway traffic with jams and stop-start waves. In Proceedings of the Winter Simulation Conference, 8-11 December (pp. 762-770). USA Phoenix, AZ: ACM Press. Yatskiv, I., Yurshevich, E., Savrasov, M. (2007). Investigation of Riga Transport Node Capacity on the Basis of Microscopic Simulation, In Proceedings of the 21 st European Conference on Modelling and Simulation (ECMS 2007), Prague, Czech Republic, 4-6 June (pp. 584-589). Prague, Czech Republic: Curran Associates, Inc. Esser, J

References 1. Barcelo, J., Codina, E., Casas, J., Ferrer, J. L., Garcia, D. (2005). Microscopic Traffic Simulation: a Tool for the Design, Analysis and Evaluation of Intelligent Transportation Systems. Journal of Intelligent and Robotic Systems: Theory and Applications , 41, 173-203. 2. Barlow, R. and Proschan, F. (1996). Mathematical Theory of Reliability . Philadelphia: Society for Industrial and Applied Mathematics. 3. Ben-Akiva, M., Cuneo, D., Hasan, M., Jha, M., Yang, Q. (2003). Evaluation of Freeway Control Using a Microscopic Simulation Laboratory

Microscopic Traffic Simulation Models. 2003 TRB Annual Meeting, January 12-16., 2003. 7. Margreiter, M., Spangler, M., Zeh, T. and Carstensen, C. (2015) Bluetooth-Measured Travel Times for Dynamic Re-Routing. In: Proceedings of the 3rd Annual International Conference ACE 2015, Volume 2, Global Science and Technology Forum, Singapore, pp. 447. 8. Park, B. and Won, J. (2006) Microscopic Simulation Model Calibration and Validation Handbook, University of Virginia, Charlottesville, Virginia Transportation Research Council, Charlottesville, available at: http

. Kesting, D. Helbing. Delays, inaccuracies and anticipation in microscopic traffic models. Physica A 2006 (360), 71 - 88. [9] M. Treiber, A. Hennecke, D. Helbing. Congested traffic states in empirical observations and microscopic simulations. Physical review E 2000 (62), 1805 - 1824. [10] M. Treiber, D. Helbing. Realistische Mikrosimulation von Straßenverkehr mit einem einfachen Modell. 2002, Dresden. [11] O. Derbel, T. Peter, B. Mourllion, M. Basset. Generalized velocity-density model based on microscopic traffic simulation. Transport 2015 (33), No. 2, 489 - 501. DOI

better understanding of ALINEA via model-free control. International Journal of Control, Vol. 90, Iss. 5, 2017, pp. 1018-1026. [11] ABUAMER, I.M. & CELIKOGLU, H.B.: Local Ramp Metering Strategy ALINEA: Microscopic Simulation Based Evaluation Study on Istanbul Freeways. 19th Euro Working Group on Transportation Meeting (EWGT2016), Vol. 22, 2017, pp. 598-606. [12] SRNKA, T.: Control of the Vehicles Flow in the “Ramp Metering” Application (in Slovak). MSc. thesis, No. 28260220172022, KRIS EF UNIZA Žilina, 2017.