Abstract
We propose the use of evidential combination operators for advanced driver assistance systems (ADAS) for vehicles. More specifically, we elaborate on how three different operators, one precise and two imprecise, can be used for the purpose of entrapment prediction, i.e., to estimate when the relative positions and speeds of the surrounding vehicles can potentially become dangerous. We motivate the use of the imprecise operators by their ability to model uncertainty in the underlying sensor information and we provide an example that demonstrates the differences between the operators.
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References
Brannstrom, M., Sandblom, F., Hammarstrand, L.: A probabilistic framework for decision-making in collision avoidance systems. IEEE Transactions on Intelligent Transportation Systems 14(2), 637–648 (2013)
Dempster, A.P.: A generalization of bayesian inference. Journal of the Royal Statistical Society 30(2), 205–247 (1969)
Arnborg, S.: Robust Bayesianism: Imprecise and paradoxical reasoning. In: Proceedings of the 7th International Conference on Information fusion (2004)
Arnborg, S.: Robust Bayesianism: Relation to evidence theory. Journal of Advances in Information Fusion 1(1), 63–74 (2006)
Karlsson, A., Johansson, R., Andler, S.F.: Characterization and empirical evaluation of bayesian and credal combination operators. Journal of Advances in Information Fusion 6(2), 150–166 (2011)
Levi, I.: The Enterprise of Knowledge: An Essay on Knowledge, Credal Probability, and Chance. MIT Press (1983)
Walley, P.: Towards a unified theory of imprecise probability. International Journal of Approximate Reasoning 24, 125–148 (2000)
Walley, P.: Statistical Reasoning with Imprecise Probabilities. Chapman and Hall (1991)
Berger, J.O.: An overview of robust Bayesian analysis. Test 3, 5–124 (1994)
Couso, I., Moral, S., Walley, P.: A survey of concepts of independence for imprecise probabilities. Risk Decision and Policy 5, 165–181 (2000)
Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press (1976)
Smets, P.: Analyzing the combination of conflicting belief functions. Information Fusion 8, 387–412 (2007)
Irpino, A., Tontodonato, V.: Cluster reduced interval data using Hausdorff distance. Computational Statistics 21, 241–288 (2006)
Helldin, T., Falkman, G., Riveiro, M., Davidsson, S.: Presenting system uncertainty in automotive uis for supporting trust calibration in autonomous driving. In: Proceedings of the 5th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. AutomotiveUI 2013, pp. 210–217. ACM, New York (2013)
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Karlsson, A., Dahlbom, A., Zhong, H. (2014). Evidential Combination Operators for Entrapment Prediction in Advanced Driver Assistance Systems. In: Andreasen, T., Christiansen, H., Cubero, JC., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2014. Lecture Notes in Computer Science(), vol 8502. Springer, Cham. https://doi.org/10.1007/978-3-319-08326-1_20
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DOI: https://doi.org/10.1007/978-3-319-08326-1_20
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08325-4
Online ISBN: 978-3-319-08326-1
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