Abstract
Nowadays detailed and reliable information about current and future traffic states is a crucial requirement not only for each modern traffic control centre, but also for driver accessible traffic information applications. In this work the novel traffic information system OLSIM is presented that is based on three components. The first is a highly realistic traffic flow model with which all vehicles in a large scale network are simulated. The second component consists of efficient data processing and forecast algorithms that form heuristics from a large database that is fed every minute by traffic data of 4,000 inductive loop detectors across the road network. The third is a graphical user interface which can be accessed at www.autobahn.nrw.de . More than 200,000 users each day indicate the importance of such a system.
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References
Wahle, J., Chrobok, R., Pottmeier, A., Schreckenberg, M.: A Microscopic Simulator for Freeway Traffic. Network and Spatial Economics 2, 371–386 (2002)
Nagel, K., Schreckenberg, M.: A cellular automaton model for freeway traffic. J. Physique I. 2, 2221–2229 (1992)
Barlovic, R., Santen, L., Schadschneider, A., Schreckenberg, M.: Metastable states in cellular automata for traffic flow. Eur. Phys. J. B 5, 793–800 (1998)
Helbing, D.: Empirical traffic data and their implications for traffic modelling. Phys. Rev. E 28, R25–R28 (1996)
Hafstein, S.F., Chrobok, R., Pottmeier, A., Wahle, J., Schreckenberg, M.: Cellular Automaton Modeling of the Autobahn Traffic in North Rhine-Westphalia. In: Troch, I., Breitenecker, F. (eds.) Proc. of the 4th MATHMOD, Vienna, Austria, pp. 1322–1331 (2003)
Helbing, D., Herrmann, H.J., Schreckenberg, M., Wolf, D.E. (eds.): Traffic and Granular Flow 1999. Springer, Heidelberg (2000)
George, H.P.: Measurement and Evaluation of Traffic Congestion. Bureau of Highway Traffic, Yale University, pp. 43–68 (1961)
Miller, A.: A queuing model for road traffic flow. J. of the Royal Stat. Soc. B1, 23, University Tech. Rep. PB 246, Columbus, USA, pp. 69–75 (1961)
Highway Capacity Manual. HRB Spec. Rep. 87. U.S. Department of Commerce, Bureau of Public Road, Washington, D.C (1965)
Edie, L.C., Foot, R.S.: Traffic flow in tunnels. Proc. HRB 37, 334–344 (1958)
Pfefer, R.C.: New safety and service guides for sight distances. Transportation Engineering Journal of American Society of Civil Engineers 102, 683–697 (1976)
Knospe, W.: Synchronized traffic: Microscopic modeling and empirical observations. Ph.D. Thesis, University Duisburg-Essen, Germany (2002)
Nagel, K., Wolf, D.E., Wagner, P., Simon, P.: Two-lane traffic rules for cellular automata: A systematic approach. Phys. Rev. E 58, 1425–1437 (1998)
Ahmed, S.A.: Stochastic Processes in Freeway Traffic. Transp. 19-21, 306–310 (1983)
Wild, D.: Short-term forecasting based on a transformation and classification of traffic volume time series. Int. J. of Forecasting 13, 63–72 (1997)
van Iseghem, S., Danech-Pajouh, M.: Forecasting Traffic One or Two Days in Advance - An Intermodal Approach. Recherche Transports Securite 65, 79–97 (1999)
Dougherty, M.S., Cobbett, M.R.: Short-term inter-urban traffic forecasts using neural networks. Int. J. of Forecasting 13, 21–31 (1997)
Dia, H.: An object-oriented Neural Network Approach to Short-Term traffic forecasting. Euro. J. Op. Res. 131, 253–261 (2001)
Whittaker, J., Garside, S., Lindveld, K.: Tracking and Predicting a Network Traffic Process. Int. J. of Forecasting 13, 51–61 (1997)
Nair, A.S., Liu, J.-C., Rilett, L., Gupta, S.: Non-Linear Analysis of Traffic Flow. In: Stone, B., Conroy, P., Broggi, A. (eds.) Proc. of the 4th International IEEE Conference on Intelligent Transportation Systems, Oakland, USA, pp. 683–687 (2001)
Kirby, H.R., Watson, S.M., Dougherty, M.S.: Should we use neural networks or statistical models for short-term mororway traffic forecasting? Int. J. of Forecasting 13, 43–50 (1997)
Danech-Pajouh, M., Aron, M.: ATHENA: a method for short-term inter-urban motorway traffic forecasting. Recherche Transports Sécurité - English issue 6, 11–16 (1991)
Chrobok, R., Kaumann, O., Wahle, J., Schreckenberg, M.: Different methods of traffic forecast based on real data. Euro. J. Op. Res. 155, 558–568 (2004)
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Weber, D., Chrobok, R., Hafstein, S., Mazur, F., Pottmeier, A., Schreckenberg, M. (2006). OLSIM: Inter-urban Traffic Information. In: Böhme, T., Larios Rosillo, V.M., Unger, H., Unger, H. (eds) Innovative Internet Community Systems. IICS 2004. Lecture Notes in Computer Science, vol 3473. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553762_27
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DOI: https://doi.org/10.1007/11553762_27
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