Abstract
In this paper, we propose an automatic race track generating system based on difficulty evaluation and feature turns detection for providing users skill-matched contents. Given a start point, a goal point, and a difficulty expectation chart, our system ranks all candidate race tracks according to the similarity with respect to the given difficulty curve. Then, user can choose a satisfied track and export it into a racing car simulator to play.
The system automatically creates the racing line for the input race track. Then, the line is used to segment turns in the race track, and the corresponding ideal maximum speed variation is exploited to evaluate the difficulty by our proposed Turnscore formula. Also, the corresponding curvature chart of the racing line is encoded as a string and the characterized regular expression for feature turns is being matched in the string for identifying feature turns.
As the experimental results show, the feature turns detection is of high accuracy and the difficulty evaluation is reliable so that our system is effective to provide skill-matched race tracks for users.
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 subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Open Street Map (June 2001), http://www.openstreetmap.org/
Allianz Sponsoring Media Center (June 2005), http://sponsoring.allianz.com/en/
Wymann, B.: TORCS Robot Tutorial (February 24, 2005), http://www.berniw.org/
F1 Tracks for TORCS (June 2011), http://apr-free.info/joomla/
Google Map (June 2011), http://maps.google.com.tw/
Hannan, J.: Interview to jeff hannan (2001), http://www.generation5.org/content/2001/hannan.asp
Lecchi, S.: Artificial intelligence in racing games. In: 2009 IEEE Symposium on Computational Intelligence and Games, CIG 2009, p.1 (2009)
Riedmiller, M., Braun, H.: A direct adaptive method for faster backpropagation learning: the RPROP algorithm. In: 1993 IEEE International Conference on Neural Networks, vol. 1, pp. 586–591 (1993)
Tollenaere, T.: SuperSAB: fast adaptive bacl propagation with good scaling properties. Neural Networks 3(5) (1990)
Schiffmann, W., Joost, M., Werner, R.: Optimization of the Backpropagation Algorithm for Training Multilayer Perceptrons (1994)
Stern, D., Candela, J.Q., Herbrich, R., Graepel, T.: Playing machines: Machine learning applications in computer games. Microsoft Research Cambridge (2008)
TORCS Team. TORCS (The Open Racing Car Simulator) Official Site. Latest Version: TORCS 1.3.1 (May 2, 2010), http://torcs.sourceforge.net/
Coulom, R.: Reinforcement Learning Using Neural Networks, with Applications to Motor Control. PhD thesis, Institut National Polytechnique de Grenoble (2002)
Braghin, F., Cheli, F., Melzi, S., Sabbioni, E.: Race driver model. Computers and Structures 86(13-14), 1503–1516 (2008)
Cardamone, L., Loiacono, D., Lanzi, P.L., Bardelli, A.P.: Searching for the Optimal Racing Line Using Genetic Algorithms. In: 2010 IEEE Symposium on Computational Intelligence and Games (CIG), pp. 388–394 (August 2010)
Rubin, F.: Enumerating all simple paths in a graph. IEEE Transactions on Circuits and Systems 25, 641–642 (1978)
Gran Turismo 5 (2010), http://en.wikipedia.org/wiki/Gran_Turismo_5
Chen, G., Esch, G., Wonka, P., Muller, P., Zhang, E.: Interactive Procedural Street Modeling. ACM Transactions on Graphics 27(3), 103:1–103:10 (2008)
Galin, E., Peytavie, A., Marechal, N., Guerin, E.: Procedural Generation of Roads. Proceedings of Eurographics 29(2), 429–438 (2010)
The Official Formula One Website, http://www.formula1.com/
The Official APIGA Website, http://www.apiga.com.tw/
Soper, H.E., Young, A.W., Cave, B.M., Lee, A., Pearson, K.: On the distribution of the correlation coefficient in small samples. Appendix II to the papers of “Student” and R. A. Fisher. Biometrika 11(4), 328–413 (1917)
Jarvelin, K., Kekalainen, J.: Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems (TOIS) 20, 422–446 (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, TY., Hsu, HW., Tai, WK., Chang, CC. (2012). An Automatic Race Track Generating System. In: Nijholt, A., Romão, T., Reidsma, D. (eds) Advances in Computer Entertainment. ACE 2012. Lecture Notes in Computer Science, vol 7624. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34292-9_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-34292-9_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34291-2
Online ISBN: 978-3-642-34292-9
eBook Packages: Computer ScienceComputer Science (R0)