Abstract
One of methods used to find better light signalization plans for urban regions is a traffic flow numerical simulation. In this paper we present solution of two main issues the user of traffic flow simulation tool encounters while simulating traffic continuously registered in ITS by counting detectors, namely: (a) origination-destination routes setting, (b) calibration of the driver model. We consider two methods for origination-destination matrix estimation. The first is classical Spiess gradient method and the second one is the equilibrium method of Casseta which is suitable to congested scenarios. Resulting origination destination matrices from both methods are input to the traffic simulator to generate traffic between nodes in the city. The traffic generated in the simulator in this manner is used to calibrate the average driver model, to achieve as good recovery of vehicle counts on detectors as possible. As a simulation tool we use an open source ArsNumerica Execution Environment running on top of SUMO simulator. The driver model that is used is stochastic Krauss model. Calibration is done for one of the most congested areas in the city of Wrocław in the morning peak.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Spiess, H.: A Gradient Approach for the O-D Matrix Adjustment Problem, EMME/2 Support Center, Switzerland (1990)
Cascetta, E.: Transportation Systems Analysis. Model and Applications. Springer Optimisations and ITS Applications, 2nd edn. Springer, Heidelberg (2009)
Krauss, S.: Microscopic modeling of traffic flow: investigation of collision free vehicle dynamics. DLR, Ph.D. thesis (1998)
Bazan, M., et al.: Intelligent transportation system auditing using micro-simulation. Arch. Transp. Syst. Telemat. 8(4), 3–8 (2015)
Bazan, M., et al.: Green wave optimisation. Arch. Transp. Syst. Telemat. 9(3), 3–8 (2016)
Bazan, M., et al.: Two methods of calculation of the origination destination matrix of an urban area, Raport W04/P-007/15, Wrocław University of Technology (2015)
Treiber, M., Kersting, A.: Trafic Flow Dynamics, Data, Models and Simulation. Springer, Heidelberg (2013)
Toledo, T., et al.: Network model calibration studiem. In: Traffic Simulation and Data: Validation methods and Applications, pp. 141–162. CRC Press, Boca Raton (2015)
Antoniou, C., et al.: Towards a generic benchmarking platform for origin–destination flows estimation/updating algorithms: design, demonstration and validation. Transp. Res. Part C 66, 79–98 (2016)
Tavana, H.: Internally consistent estimation of dynamic network origin–destination flows from intelligent transportation systems data using bi-level optimization. Ph.D. thesis, University of Texas, Austin (2001)
Acknowledgement
The work presented in this paper was partially financed from Grant 0401/0230/16.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Bazan, M., Janiczek, T., Madej, Ł. (2017). Equilibrium Method for Origination Destination Matrix Estimation Exploited to Urban Traffic Simulation Calibration. In: Mikulski, J. (eds) Smart Solutions in Today’s Transport. TST 2017. Communications in Computer and Information Science, vol 715. Springer, Cham. https://doi.org/10.1007/978-3-319-66251-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-66251-0_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-66250-3
Online ISBN: 978-3-319-66251-0
eBook Packages: Computer ScienceComputer Science (R0)