Effects of pavement surface deformations on traffic flow
Abstract
Pavement surface deformations have a significant effect on speed profile of vehicles and traffic flow conditions. These deformations limit driving properties and increase vehicle operation and maintenance costs. Additionally, they cause many problems such as accidents, slower movement speeds, capacity loss and severe discomfort states. There are many factors having an effect on road capacities and they vary according to different road and traffic flow conditions. In this study, it is aimed to investigate and develop models to estimate shockwave and bottleneck forming, capacity loss and speed reduction, which occurred on examined road links caused by pavement deformations. For the prediction of road capacity, flow–density (q–k) relationship, bottleneck and shockwave analysis methods were used. In the scope this study, deformed road links were divided into three sections; Section A – before deformation zone, Section B – deformation zone, and Section C – after deformation zone. All three sections were investigated and empirical results were obtained. According to analysis results, it was found that pavement surface deformations have a negative effect on the level of road service capability. Obtained results also showed that there are significant reductions in capacity relatively by up to 44 and 26% would result from surface deformations on deformed lanes and non-deformed adjacent lanes.
Keyword : capacity loss, shockwave, bottleneck, pavement surface deformation, traffic flow
How to Cite
Aydin, M. M., & Topal, A. (2019). Effects of pavement surface deformations on traffic flow. Transport, 34(2), 204-214. https://doi.org/10.3846/transport.2019.8631
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Jiang, Y.; Li, S. 2002. Measuring and analyzing vehicle position and speed data at work zones using global positioning systems, ITE Journal 72(3): 48–53.
Kurata, S.; Nagatani, T. 2003. Spatio-temporal dynamics of jams in two-lane traffic flow with a blockage, Physica A: Statistical Mechanics and its Applications 318(3–4): 537–550. https://doi.org/10.1016/S0378-4371(02)01376-6
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Nejad, F. M.; Zakeri, H. 2011. A comparison of multi-resolution methods for detection and isolation of pavement distress, Expert Systems with Applications 38(3): 2857–2872. https://doi.org/10.1016/j.eswa.2010.08.079
Prentkovskis, O.; Tretjakovas, J.; Švedas, A.; Bieliatynskyi, A.; Daniūnas, A.; Krayushkina, K. 2012. The analysis of the deformation state of the double-wave guardrail mounted on bridges and viaducts of the motor roads in Lithuania and Ukraine, Journal of Civil Engineering and Management 18(5): 761–771. https://doi.org/10.3846/13923730.2012.731252
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Akgüngör, A. P.; Doğan, E. 2009. An artificial intelligent approach to traffic accident estimation: Model development and application, Transport 24(2): 135–142. https://doi.org/10.3846/1648-4142.2009.24.135-142
Aydın, M. M. 2012. Çok şeritli yollarda sürücü şerit seçim davranışlarının modellenmesi. Yüksek Lisans Tezi. Dokuz Eylül Universitesi, Fen Bilimleri Enstitüsü, Izmir, Turkey. 146 s. (in Turkish). Available from Internet: http://acikerisim.deu.edu.tr/xmlui/handle/12345/7778
Aydın, M. M.; Topal, A. 2016. Effect of road surface deformations on lateral lane utilization and longitudinal driving behaviours, Transport 31(2): 192–201. https://doi.org/10.3846/16484142.2016.1193049
Aydın, M. M.; Topal, A.; Tanyel, S. 2013. Çok şeritli yollarda yol yüzey bozukluklarının sürücü davranışları üzerindeki etkisinin incelenmesi, in TMMOB 10: Ulaştırma Kongresi, 25–27 Eylül 2013, İzmir, Turkey, 413–425 (in Turkish).
Aydın, M. M.; Yildirim, M. S.; Karpuz, O.; Ghasemlou, K. 2014. Modeling of driver lane choice behaviour with artificial neural networks (ANN) and linear regression (LR) analysis on deformed roads, Computer Science & Engineering: an International Journal 4(1): 47–57. https://doi.org/10.5121/cseij.2014.4105
Ben-Edigbe, J. 2005. Influence of Pavement Distress on Capacity Loss and Their Implications for PCE. PhD Thesis. University of Strathclyde, Glasgow, Scotland.
Ben-Edigbe, J. 2010. Assessment of speed-flow-density functions under adverse pavement condition, International Journal of Sustainable Development and Planning 5(3): 238–252. https://doi.org/10.2495/SDP-V5-N3-238-252
Ben-Edigbe, J. 2016. Computing flexible pavement distress zone travel time differentials on multilane highway, International Journal of Applied Engineering Research 11(14): 8340–8344.
Ben-Edigbe, J.; Ferguson, N. 2005. Extent of capacity loss resulting from pavement distress, Proceedings of the Institution of Civil Engineers – Transport 158(1): 27–32. https://doi.org/10.1680/tran.2005.158.1.27
Ben-Edigbe, J.; Ferguson, N. 2009. Qualitative road service reduction resulting from pavement distress, in Urban Transport XV: Urban Transport and the Environment, 22–24 June 2009, Bologna, Italy.
Ben-Edigbe, J.; Mashros, N. 2012. Extent of highway capacity loss resulting from road humps, International Journal of Engineering and Technology 4(2): 121–125. https://doi.org/10.7763/IJET.2012.V4.331
Ben-Edigbe, J.; Mashros, N.; Minhans, A. 2011. Exploration of trapezoidal flowrate contractions resulting from pavement distress, Journal of Emerging Trends in Engineering and Applied Sciences 2(2): 351–354.
Brown, S. F. 1995. Practical test procedures for mechanical properties of bituminous materials, Proceedings of the Institution of Civil Engineers – Transport 111(4): 289–297. https://doi.org/10.1680/itran.1995.28031
Chen, J.; Shi, Z.; Hu, Y.; Yu, L.; Fang, Y. 2013. An extended macroscopic model for traffic flow on a highway with slopes, International Journal of Modern Physics C 24(9): 1350061. https://doi.org/10.1142/S0129183113500617
Chen, J.; Peng, Z.; Fang, Y. 2014. Effects of car accidents on three-lane traffic flow, Mathematical Problems in Engineering 2014: 413852. https://doi.org/10.1155/2014/413852
Cho, S. 2013. Revisiting shock wave theory, Proceedings of the Institution of Civil Engineers – Transport 166(6): 354–361. https://doi.org/10.1680/tran.11.00032
Dell’Acqua, G.; De Luca, M.; Lamberti, R. 2011. Indirect skid resistance measurement for porous asphalt pavement management, Transportation Research Record: Journal of the Transportation Research Board 2205: 147–154. https://doi.org/10.3141/2205-19
Dell’Acqua, G.; De Luca, M.; Prato, C. G.; Prentkovskis, O.; Junevičius, R. 2016. The impact of vehicle movement on exploitation parameters of roads and runways: a short review of the special issue, Transport 31(2): 127–132. https://doi.org/10.3846/16484142.2016.1201912
Dell’Acqua, G.; Russo, F. 2011. Road performance evaluation using geometric consistency and pavement distress data, Transportation Research Record: Journal of the Transportation Research Board 2203: 194–202. https://doi.org/10.3141/2203-24
Gazis, D. C. 2002. Traffic Theory. Springer US. 259 p. https://doi.org/10.1007/b101918
Gerlough, D. L.; Huber, M. J. 1975. Traffic Flow Theory. Monograph. Special Report 165. Transportation Research Board (TRB), Washington, DC, US. 233 p. Available from Internet: http://onlinepubs.trb.org/onlinepubs/sr/sr165/165.pdf
Ghasemlou, K.; Aydın, M. M.; Yıldırım, M. S. 2016. An investigation on lane blockage effects at signalized intersections, Internatıonal Journal for Traffıc and Transport Engıneerıng 6(3): 289–302. https://doi.org/10.7708/ijtte.2016.6(3).05
Jiang, Y. 1999. Traffic Characteristics and Estimation of Traffic Delays and User Costs at Indiana Freeway Work Zones. Final Report FHWA/INDOT/SPR-2121. Indiana Department of Transportation (INDOT), US. Available from Internet: https://rosap.ntl.bts.gov/view/dot/5034
Jiang, Y.; Li, S. 2002. Measuring and analyzing vehicle position and speed data at work zones using global positioning systems, ITE Journal 72(3): 48–53.
Kurata, S.; Nagatani, T. 2003. Spatio-temporal dynamics of jams in two-lane traffic flow with a blockage, Physica A: Statistical Mechanics and its Applications 318(3–4): 537–550. https://doi.org/10.1016/S0378-4371(02)01376-6
Lee, H. D.; Kim, J. J. 2005. Development of a Manual Crack Quantification and Automated Crack Measurement System. Project No 457. Final Report. University of Iowa, US. 21 p. Available from Internet: http://publications.iowa.gov/2423/1/tr457.pdf
Lighthill, M. J.; Whitham, G. B. 1955a. On kinematic waves I. Flood movement in long rivers, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences 229(1178): 281–316. https://doi.org/10.1098/rspa.1955.0088
Lighthill, M. J.; Whitham, G. B. 1955b. On kinematic waves II. A theory of traffic flow on long crowded roads, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences 229(1178): 317–345. https://doi.org/10.1098/rspa.1955.0089
Minderhoud, M. M.; Botma, H.; Bovy, P. H. L. 1997. Assessment of roadway capacity estimation methods, Transportation Research Record: Journal of the Transportation Research Board 1572: 59–67. https://doi.org/10.3141/1572-08
Nejad, F. M.; Zakeri, H. 2011. A comparison of multi-resolution methods for detection and isolation of pavement distress, Expert Systems with Applications 38(3): 2857–2872. https://doi.org/10.1016/j.eswa.2010.08.079
Prentkovskis, O.; Tretjakovas, J.; Švedas, A.; Bieliatynskyi, A.; Daniūnas, A.; Krayushkina, K. 2012. The analysis of the deformation state of the double-wave guardrail mounted on bridges and viaducts of the motor roads in Lithuania and Ukraine, Journal of Civil Engineering and Management 18(5): 761–771. https://doi.org/10.3846/13923730.2012.731252
Prentkovskis, O.; Beljatynskij, A.; Juodvalkienė, E.; Prentkovskienė, R. 2010. A study of the deflections of metal road guardrail post, The Baltic Journal of Road and Bridge Engineering 5(2): 104–109. https://doi.org/10.3846/bjrbe.2010.15
Richards, P. I. 1956. Shockwaves on the highway, Operations Research 4(1): 42–51. https://doi.org/10.1287/opre.4.1.42
Strazdins, G.; Mednis, A.; Kanonirs, G.; Zviedris, R.; Selavo, L. 2011. Towards vehicular sensor networks with android smartphones for road surface monitoring, in The Second International Workshop on Networks of Cooperating Objects (CONET’11): Electronic Proceedings of CPSWeek’11, 11 April 2011, Chicago, US, 1–4.
TRRL. 1991. Towards Safer Roads in Developing Countries: a Guide for Planners and Engineers. Transport and Road Research Laboratory (TRRL), Crowthorne, UK. 220 p.
TRB. 2004. Automated Pavement Distress Collection Techniques. National Cooperative Highway Research Program (NCHRP) Synthesis 334. Transportation Research Board (TRB), Washington, DC, US. https://doi.org/10.17226/23348
TRB. 2010. Highway Capacity Manual. 5th edition. Transportation Research Board (TRB), Washington, DC, US. 1650 p.
Van Arem, B.; Van Der Vlist, M.J.M.; De Ruiter, J. C. C.; Muste, M.; Smulders, S. A. 1994. Design of the Procedures for Current Capacity Estimation and Travel Time and Congestion Monitoring. General European Road Data Information Exchange Network (GERDIEN). DRIVE-II Project No V2044, Deliverable No 9, Technical Annex 2 (Revised), Workpackage No. SP6.WP2 & SP6.WP3. 71 p. Available from Internet: http://publicaties.minienm.nl/documenten/design-of-the-procedures-for-current-capacity-estimation-and-tra
Walker, D.; Entine, L.; Kummer, S. 2002. Pavement surface evaluation and rating: asphalt Roads Paser Manual. Transportation Information Center, University of Wisconsin–Madison, US. 32 p.
Wang, K. C. P. 2000. Designs and implementations of automated systems for pavement surface distress survey, Journal of Infrastructure Systems 6(1): 24–32. https://doi.org/10.1061/(ASCE)1076-0342(2000)6:1(24)
Žilionienė, D.; De Luca, M.; Dell’Acqua, G. 2013. Evaluation of climatic factors based on the mechanistic-empirical pavement design guide, The Baltic Journal of Road and Bridge Engineering 8(3): 158–165. https://doi.org/10.3846/bjrbe.2013.20