Summary
This contribution reports a recently recorded data-set that helps to understand the car-following process better. Since the empirical basis of most traffic flow models can be called weak, these findings may help to design better models. They demonstrate, that the process of car-following seems to have a very interestic stochastic dynamics. Especially, and different from most of the existing models the data show clearly that car following cannot be described by a noisy fixed point dynamics. This is because the acceleration of the cars is smooth and roughly constant for a certain time, with fast changes to a new value at so called action points.
Furthermore, the data can be used for calibration and validation purposes of the various models. This has been done with very interesting results indicating that all the models tested behave very similar and cannot describe the data better than with 15 % difference between models and data.
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References
G. S. Gurusinghe, T. Nakatsuji, Y. Azuta, P. Ranjitkar, and Y. Tanaboriboon. Multiple car following data using real time kinematic global positioning system. Transportation Research Records, 2003.
Institute for Transport Research. Clearinghouse for traffic data. http://www.clearingstelle-verkehr.de, accessed Aug. 2004.
I. Lubashevsky, M. Hajimahmoodzadeh, Albert Katsnelson, and P. Wagner. Noise-induced phase transitions in systems of elements with motivated behavior, this volume.
S. Kalenkov, I. A. Lubashevsky, R. Mahnke, and P. Wagner. Long-lived states in synchronized flow: empirical prompt and dynamical trap model. Physical Review E, 66:016117, 2002.
M. Krbalek and D. Helbing. Determination of interaction potentials in freeway traffic from steady-state statistics. Physica A, 333:370–378, 2004. condmat/0301484.
M. J. Cassidy. Driver memory: motorist selection and retention of individualized headways in highway traffic. Transportation Research A, 32:129–137, 1998.
W. H. Press, S. A. Teukolsky, W. A. Vetterling, and B. P. Flannery. Numerical Recipes in C, volume 2nd edition. Cambridge University Press, 2002.
E. P. Todosiev and L. C. Barbosa. Traffic Engineering, 34:17–20, 1963/64.
Rainer Wiedemann. Simulation des Straßenverkehrsflußes. Technical report, Institut für Verkehrswesen, Universität Karlsruhe, 1974. Heft 8 der Schriftenreihe des IfV, in German.
H.-T. Fritzsche. A model for traffic simulation. Transportation Engineering And Control, (5):317–321, 1994.
M. W. Szeto and D. C. Gazis. Application of kalman filtering to the surveillance and control of traffic systems. Transportation Science, 6:419–439, 1972.
E. Brockfeld, R. D. Kühne, A. Skabardonis, and P. Wagner. Towards a benchmarking of microscopic traffic flow models. Transportation Research Records, 1852:124–129, 2003.
E. Brockfeld, R. D. Kühne, and P. Wagner. Calibration and validation of microscopic traffic flow models. Transportation Research Records, 1876, 2004.
E. Brockfeld and P. Wagner. Testing microscopic traffic flow models, this volume.
G. F. Newell. A simplified car-following theory: A lower order model. Transportation Research B, 36:195–205, 2002.
K. Nagel and M. Schreckenberg. A cellular automaton model for freeway traffic. J. Physique I, 2:2221, 1992.
M. Treiber, A. Hennecke, and D. Helbing. Derivation, properties, and simulation of a gas-kinetic-based, non-local traffic model. Physical Review E, 59:239–253, 1999.
P. G. Gipps. A behavioural car following model for computer simulation. Transportation Research B, 15:105–111, 1981.
S. Krauß, P. Wagner, and C. Gawron. Metastable states in a microscopic model of traffic flow. Physical Review E, 55:5597–5605, 1997.
Werner Horbelt. Maximum likelihood estimation in dynamical systems. PhD thesis, Albert-Ludwigs-Universität Freiburg im Breisgau, Germany, 2001.
I. Lubashevsky, P. Wagner, and R. Mahnke. A bounded rational driver model. Euro. Phys. J. B, 32:243–247, 2003.
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© 2005 Springer-Verlag Berlin Heidelberg
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Wagner, P. (2005). Empirical Description of Car-Following. In: Hoogendoorn, S.P., Luding, S., Bovy, P.H.L., Schreckenberg, M., Wolf, D.E. (eds) Traffic and Granular Flow ’03. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28091-X_2
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DOI: https://doi.org/10.1007/3-540-28091-X_2
Publisher Name: Springer, Berlin, Heidelberg
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