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F. Thomas, A. Weninger-Vycudil, P. Simanek:
"Automated Segmentation of Pavement Measurements Based on Bayesian Ideas: Experiences from Austria";
in: "6th International Conference on Managing Pavements", herausgegeben von: TRB, Queensland Government (Dep. of Main Roads), Austroads; ICMP, Queensland, Australia, 2004, (eingeladen), Paper-Nr. 136, 9 S.

Road surface condition measurements are in Austria periodically obtained for all the federal roads. These measurements refer to 50m long road sections and form the basis for an evaluation of the current state of the road network as well as the subsequent analysis of maintenance strategies and their funding requirements. In order to systematically utilize the information contained in these measurement series, homogeneous sections have to be identified for longitudinal and transversal unevenness as well as skid resistance. For that purpose a recently published segmentation algorithm has been implemented as a standalone computer program that is capable of processing huge amounts of data in batch mode. This software takes a measurement series as input and identifies the borders of homogeneous sections by evaluating the statistical properties of the measurement series under study. A variety of quantities representing the homogeneous sections is calculated and can be exported in widely understood file formats for further processing. While the program is able to execute fully automatically, the user has the option to control all aspects of the implemented algorithm and might alter any suggested segmentation using the graphical interface of the application. About 10,000km of Austrian federal roads of category B have been successfully processed using this computer program, and homogeneous sections based respectively on measurements of the International Roughness Index, rut depth, and skid resistance have been identified and stored in the Austrian Pavement Management System. The program is available through the web page http://www.istu.tuwien.ac.at

http://aleph.ub.tuwien.ac.at/F?base=tuw01&func=find-c&ccl_term=AC04967136