RESEARCH PAPER
Urban Traffic Detectors Data Mining for Determination of Variations in Traffic Volumes
1
Department of Transport and Logistics, The Institute of Technology and Business in Ceske Budejovice, Czech Republic
Submission date: 2020-10-22
Final revision date: 2020-11-25
Acceptance date: 2020-12-11
Publication date: 2021-01-11
Corresponding author
Ladislav Bartuska
Department of Transport and Logistics, The Institute of Technology and Business in Ceske Budejovice, Okruzni 517/10, 37001, Ceske Budejovice, Czech Republic
Department of Transport and Logistics, The Institute of Technology and Business in Ceske Budejovice, Okruzni 517/10, 37001, Ceske Budejovice, Czech Republic
The Archives of Automotive Engineering – Archiwum Motoryzacji 2020;90(4):15-31
KEYWORDS
TOPICS
ABSTRACT
This paper analyses road traffic volumes in the urban environment for the purpose of traffic planning and creation of traffic models. For modelling traffic in a certain area, the initial information about transport demand and distribution in given area is required. The demand for transport is further re-distributed to the transport network and measured against the current road traffic volumes / intensity of traffic. Traffic volumes over time are characterized by various periodic and non-periodic influences (variations). By studying these variations, the tools can be specified for making the final estimate of traffic volumes for a specific time period, a specific type of road or specific vehicle category, and for improving the traffic models for a specific area. In this paper, the authors study time variations in traffic volumes using the data obtained from vehicle detectors for monitoring traffic located on roads in the city of Ceske Budejovice, the Czech Republic.
REFERENCES (30)
1.
Afolabi OJ., Oluwaji OA., Onifade TA.: Transportation Factors in the Distribution of Agricultural Produce to Urban Center in Nigeria, LOGI – Scientific Journal on Transport and Logistics, 2018, 9(1), 1–10, DOI: 10.2478/logi-2018-0001.
2.
Aunet B.: Wisconsin’s approach to variation in traffic data. North American Travel Monitoring Exhibition and Conference 2000, Wisconsin.
3.
Caban J., Droździel P., Krzywonos L., Rybicka IK., Šarkan B., Vrábel J. Statistical Analyses of Selected Maintenance Parameters of Vehicles of Road Transport Companies. Advances in Science and Technology Research Journal. 2019, 13(1), 1–13, DOI: 10.12913/22998624/92106.
4.
Cheung SY., Coleri S., Dundar B., Ganesh S., Tan CW., Varaiya PP.: Traffic measurement and vehicle classification with a single magnetic sensor. Transportation Research Record: Journal of the Transportation Research Board. 2005, 1917, 173–181, DOI: 10.1177/0361198105191700119.
5.
Chrobok R., Kaumann O., Wahle J., Schreckenberg M.: Different methods of traffic forecast based on real data. European Journal of Operational Research. 2004, 155(3), 558–568, DOI: 10.1016/j.ejor.2003.08.005.
6.
Fedorko G., Heinz D., Molnár V., Brenner T.: Use of mathematical models and computer software for analysis of traffic noise. Open Engineering. 2020, 10(1), 129–139, DOI: 10.1515/eng-2020-0021.
7.
Flaherty J.: Cluster analysis of Arizona automatic traffic recorder data. The Science of the Total Environment. 1993, 1410, 93–99.
8.
Gasparik J., Stopka O., Peceny L.: Quality evaluation in regional passenger rail transport. Nase More. 2015, 62(3), 114–118, DOI: 10.17818/NM/2015/SI5.
9.
Gorzelanczyk P., Jurkovic M., Kalina T., Sosedova J., Luptak V.: Influence of motorization development on civilization diseases. Transport Problems. 2020, 15(3), 53–66, DOI: 10.21307/tp-2020-033.
10.
Hilbers H., Van Eck JR., Snellen D: Behalve de dagelijkse files, over betrouwbaarheid van reistijd (in Dutch). NAI uitgevers, 2004, Ruimtelijk Planbureau, The Netherlands.
11.
Kampf R., Stopka O., Kubasakova I., Zitricky V.: Macroeconomic Evaluation of Projects Regarding the Traffic Constructions and Equipment. Procedia Engineering. 2016, 161, 1538–1544, DOI: 10.1016/j.proeng.2016.08.623.
12.
Keay K., Simmonds I.: The association of rainfall and other weather variables with road traffic volume in Melbourne, Australia. Accident Analysis and Prevention. 2005, 37, 109–124, DOI: 10.1016/j.aap.2004.07.005.
13.
Li MT., Zhao F., Chow LF.: Assignment of seasonal factor categories to urban coverage count stations using a fuzzy decision tree. Journal of Transportation Engineering. 2006, 132(8), 654–662, DOI: 10.1061/(ASCE)0733-947X(2006)132:8(654).
14.
Lizbetin J., Stopka O.: Proposal of a Roundabout Solution within a Particular Traffic Operation. Open Engineering, 2016, 6(1), 441-445, DOI: 10.1515/eng-2016-0066.
15.
Maghrour ZM., Török Á.: Distribution of traffic speed in different traffic conditions: An empirical study in Budapest. Transport. 2020, 35(1), 68–86, DOI: 10.3846/transport.2019.11725.
16.
Martolos J., Bartoš L.: Possibilities of determining traffic volumes based on short-term traffic surveys. Journal of Traffic Engineering. 2016, (in Czech).
17.
Myšková R., Hitka M., Lorincová S., Balážová Ž.: Regional motivation differences of service sector employees in urban and rural areas in Slovakia. Scientific Papers of the University of Pardubice, Series D: Faculty of Economics and Administration. 2016, 23(37), 118–130.
18.
Paľo J., Caban J., Kiktová M., Černický Ľ.: The comparison of automatic traffic counting and manual traffic counting. IOP Conference Series: Materials Science and Engineering. 2019, 710, 1–8, DOI: 10.1088/1757-899X/710/1/012041.
19.
Schmidt G.: Hochrechnungsfactoren für Kurzzeitzählungen auf Innerortstrassen (in German). Strassenverkehrstechnik, 1996, 40(11), 546-556.
20.
Sharma S., Lingras P., Hassan MU., Murthy NAS.: Road classification according to the driver population. Transportation Research Record. 1986, 1090, 61–69.
21.
Skřivánek Kubíková S., Kalašová A., Čulík K., Palúch J.: Comparison of Traffic Flow Characteristics of Signal Controlled Intersection and Turbo Roundabout. The Archives of Automotive Engineering – Archiwum Motoryzacji. 2020, 88(2), 19–36, DOI: 10.14669/AM.VOL88.ART2.
22.
Song Y., Wang J., Ge Y., Xu C.: An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: Cases with different types of spatial data. GIScience and Remote Sensing. 2020, 57(5), 593–610, DOI: 10.1080/15481603.2020.1760434.
23.
Stathopoulos A., Karlaftis MG.: Temporal and spatial variations of real-time data in urban areas. Transportation Research Record. 2001, 1768, 135–140, DOI: 10.3141/1768-16.
24.
Stopka O., Sarkan B., Chovancova M., Kapustina LM.: Determination of the appropriate vehicle operating in particular urban traffic conditions. Communications Scientific Letters of University of Zilina. 2017, 19(2), 18–22.
25.
Tang L., Wang Y., Zhang X.: Identifying recurring bottlenecks on urban expressway using a fusion method based on loop detector data. Mathematical Problems in Engineering. 2019, 5861414, DOI: 10.1155/2019/5861414.
26.
Thomas T., Weijermars W., van Berkum E.: Variations in urban traffic volumes. European Journal of Transport and Infrastructure Research. 2008, 8(3), 251–263, DOI: 10.18757/ejtir.2008.8.3.3350.
27.
Tišljarić L., Carić T., Abramović B., Fratrović T.: Traffic state estimation and classification on citywide scale using speed transition matrices. Sustainability. 2020, 12(18), 1–16, DOI: 10.3390/su12187278.
28.
Török Á., Szalay Z., Uti G., Verebélyi B.: Rerepresenting autonomated vehicles in a macroscopic transportation model. Periodica Polytechnica Transport Engineering. 2020, 48(3), 269–275, DOI: 10.3311/PPtr.13989.
29.
Wen R., Yan W.: Vessel Crowd Movement Pattern Mining for Maritime Traffic Management. LOGI – Scientific Journal on Transport and Logistics. 2019, 10(2), 105–115. DOI: 10.2478/logi-2019-0020.
30.
Zitrický V., Gašparík J., Pečený L.: The methodology of rating quality standards in the regional passenger transport. Transport Problems. 2015, 10, 59–72, DOI: 10.21307/tp-2015-062.
CITATIONS (2):
1.
Assessment of Traffic Noise Levels in the City of Pila
Piotr Gorzelańczyk, Kamil Sobczak, Lenka Ližbetinová
The Archives of Automotive Engineering – Archiwum Motoryzacji
Piotr Gorzelańczyk, Kamil Sobczak, Lenka Ližbetinová
The Archives of Automotive Engineering – Archiwum Motoryzacji
2.
The Experience Economy in the Systems of Urban and Regional Transport - from a Change of Location to Positive Emotional Impressions during Movements
Jozef Gnap, Grzegorz Dydkowski, Anna Urbanek
Communications - Scientific letters of the University of Zilina
Jozef Gnap, Grzegorz Dydkowski, Anna Urbanek
Communications - Scientific letters of the University of Zilina
Korzystamy z plików cookie (oraz innych podobnych technologii) i przetwarzamy unikalne identyfikatory oraz dane przeglądarki – w celu umożliwienia funkcjonowania naszej strony internetowej. Więcej informacji o tym jak przetwarzamy Twoje dane osobowe znajdziesz w
