Optimization methods of the pavement management system of Budapest

    Kornel Almassy   Affiliation
    ; Gábor Pusztai Affiliation
    ; László Gáspár   Affiliation
    ; János Lógó   Affiliation


A modern Pavement Management System (PMS) should be essential for maintenance a metropolitan urban road network. Municipality of Budapest has developed own management system for their road pavement operation. To an efficient outcome the newest methods are used for the data collecting with the most innovated geo-informatics solutions, which are help us in our multi criteria decision making process. We present a degradation model which useful for the prediction of the roughness, yielding surface condition of the pavement in the future. After the whole data evaluation we give accurate information about the general characterization of the permanent road network conditions. Our paper shows that in all modern asset management system based on multi criteria decision making processes, which contain single or multi objective optimization methods. The PMS based on the available-technical and financial data and its optimization process provides a pavement renovation offer for each road in Budapest transportation network and finally the paper presents how can we ranking the invention list from our optimization process.

Keyword : Pavement Management System (PMS), geo-database, data collecting, evaluation, multi criteria optimization, intervention, renovation cost

How to Cite
Almassy, K., Pusztai, G., Gáspár, L., & Lógó, J. (2019). Optimization methods of the pavement management system of Budapest. Journal of Civil Engineering and Management, 25(8), 798-804.
Published in Issue
Oct 1, 2019
Abstract Views
PDF Downloads
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Almássy, G., & Németh, M. (2014). Roughness measurement process according to RODIS pointcloud. Asphalt Magazine, 2, 31-39.

Almássy, K., Dávid, Á., & Pusztai, G. (2018). Results of the capital’s pavement management system. Útügyi Lapok, 11.

Ambrus, K. (2015). Development of the pavement management system in Budapest. Budapest: Budapest Roads.

Bakó, A., Gáspár, L., & Kovács, D. (2012). Burkolatgazdálkodási modellek a fővárosi főutakhoz. Közlekedéstudományi Szemle, 62(6), 38-49 (in Hungarian).

BKK Közút Zrt. (2015). Project report on adapting the PMS model of KTI to the system of BKK Közút, and defining directions for improvement.

Chang, J.-R., Su, Y.-S., Huang, T.-C., Kang, S.-C., & Hsieh, S.-H. (2009). Measurement of the International Roughness Index (IRI) using an autonomous robot (P3-AT). In 26th International Symposium on Automation and Robotics in Construction (pp. 325-331). Austin, Texas, USA.

Chen, L., & Bai, Q. (2019). Optimization in decision making in infrastructure asset management: A review. Applied Sciences, 9(7), 1380.

Gáspár, L. (2003). Útgazdálkodás. Budapest: Akadémiai Kiadó (in Hungarian).

Gáspár, L. (2017). Management aspects of road pavement rehabilitation. Gradevinar, 69, 31-40.

Hillier, F. S., & Lieberman, G. J. (2005). Introduction to operations research (8th ed.). New York: Elizabeth A. Jones.

Lefsky, M. A., Cohen, W., Acker, S., Parker, G. G., Spies, T., & Harding, D. (1999). Lidar remote sensing of the canopy structure and biophysical properties of douglas-fir western hemlock forests. Remote Sensing of Environment, 70(3), 339-361.

Lógó, J. (1988). Design of bar structures by multicriteria optimization (Doctoral Thesis). Technical University of Budapest.

Lógó, J., & Kaliszky, S. (2003). Application of multicriteria optimization in layout optimization of structures. In Proceedings of the International Conference on Metal Structures (ICMS-03) (pp. 271-276). Rotterdam, Holland.

Lógó, J., & Vásárhelyi, A. (1988). Pareto optima of reinforced concrete frames. Periodica Polytechnica – Civil Engineering, 32(1-2), 87-96.

Lógó, J., Kacianauskas, R., Bernau, H., & Vásárhelyi, A. (1989). Mnogokriterialnaja optimizacija zselezobetonnyh ram. Litovskij Mehaniceskij Sbornik, 31, 33-42 (in Russian).

Markó, G., Primusz, P., & Péterfalvi, J. (2013). Measuring the bearing capacity of forest roads with an improved Benkelman beam apparatus. Acta Silvatica et Lignaria Hungarica, 9(1), 97-109.

Markó, G., Primusz, P., Péterfalvi, J., & Tóth, C. (2015). Effect of pavement stiffness on the shape of deflection bowl. Acta Silvatica et Lignaria Hungarica, 11(1), 39-54.

Németh, M., & Pusztai, G. (2016). Data collecting and condition evaluation in Budapest’s roads. Asphalt Magazine, 1, 47-54.

Rusu, L., Taut, D. A. S., & Jecan, S. (2015). An integrated solution for pavement management and monitoring systems. Procedia Economics and Finance, 27, 14-21.

Sun, Z., Xu, Y., Hoegner, L., & Stilla, U. (2018). Classification of MLS point clouds in urban scenes using detrened geometric features from Supervoxel-based local contexts. Annuals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 4(2), 271-278.

Vittilo, N. (2013). Pavement management system overview. Retrieved from

Vosselman, G., & Maas, H.-G. (2010). Airborne and terrestrial laser scanning. CRC Press.