The efficiency of urban transportation system is un-der the influence of weather conditions. It is necessary to incorporate these impacts into transport system analysis, in order to prepare adequate mitigation measures. Trans-port models are often used in different types of transport system analysis and forecasting of its future characteris-tics. This paper focuses on implementation of the impact of rain in transport modelling, particularly into a traffic assignment process as a part of a macroscopic transport model. This aspect of modelling is important because it can indicate parts of the network where this impact leads to a high volume/capacity ratio, which is a good input for defining mitigation measures. Commonly, transport models do not consider weather impacts in its standard procedures. The paper presents a methodology for cali-brating volume-delay function in order to improve traf-fic assignment modelling in case of rain. The impact of different rain categories on capacity and free-flow speed was quantified and implemented in the volume-delay function. Special attention is given to the calibration of the part of volume-delay function for over-saturated traf-fic conditions. Calibration methodology is applicable for different types of volume-delay functions and presents a solid approach to incorporate weather conditions into common engineering practice.
Pregnolato M, et al. Assessing urban strategies for re-ducing the impacts of extreme weather on infrastructure networks. Royal Society Open Science. 2007;3(5). doi: 10.1098/rsos.160023.
Ogryzek M, Adamska-Kmieć D, Klimach A. Sustain-able transport: An efficient transportation network-case study. Sustainability. 2020;12(19): 1–14. doi: 10.3390/su12198274.
Saneinejad S, Roorda MJ, Kennedy C. Modelling the im-pact of weather conditions on active transportation travel behaviour. Transportation Research Part D: Transport and Environment. 2012;17(2): 129–137. doi: 10.1016/j.trd.2011.09.005.
Schwanen T. Transport geography, climate change and space: opportunity for new thinking. Journal of Trans-port Geography. 2019;81(April): 102530. doi: 10.1016/j.jtrangeo.2019.102530.
Ivanović I, Jović J. Sensitivity of street network ca-pacity under the rain impact: Case study of Bel-grade. Transport. 2018;33(2): 470–477. doi: 10.3846/16484142.2017.1283532.
Kyte M, Khatib Z, Shannon P, Kitchener F. Effect of weather on free-flow speed. Journal of the Transpor-tation Research Board. 2001;1776(1): 60–68. doi: 10.3141/1776-08.
Tsapakis I, Cheng T, Bolbol A. Impact of weather con-ditions on macroscopic urban travel times. Journal of Transport Geography. 2013;28 204–211. doi: 10.1016/j.jtrangeo.2012.11.003.
Calvert SC, Snelder M. A methodology for road traffic resilience analysis and review of related concepts. Trans-portmetrica A: Transport Science. 2018;14(1–2): 130–154. doi: 10.1080/23249935.2017.1363315.
Quinn AD, et al. Adaptation becoming business as usual: A framework for climate-change-ready transport infra-structure. Infrastructures. 2018;3(2). doi: 10.3390/infra-structures3020010.
Tao S, Corcoran J, Rowe F, Hickman M. To travel or not to travel: ‘Weather’ is the question. Modelling the effect of local weather conditions on bus ridership. Trans-portation Research Part C: Emerging Technologies. 2018;86(November 2017): 147–167. doi: 10.1016/j.trc.2017.11.005.
Wei M, Corcoran J, Sigler T, Liu Y. Modeling the influence of weather on transit ridership: A case study from Brisbane, Australia. Transporta-tion Research Record. 2018;2672(8): 505–510. doi: 10.1177/0361198118777078.
Petrović D, Ivanović I, Đorić V, Jović J. Impact of weather conditions on travel demand – the most common research methods and applied models. Promet – Traf-fic&Transportation. 2020;32(5): 711–725. doi: 10.7307/ptt.v32i5.3499.
Malin F, Norros I, Innamaa S. Accident risk of road and weather conditions on different road types. Accident Analysis and Prevention. 2019;122(October 2018): 181–188. doi: 10.1016/j.aap.2018.10.014.
Theofilatos A, Yannis G. A review of the effect of traf-fic and weather characteristics on road safety. Acci-dent Analysis and Prevention. 2014;72: 244–256. doi: 10.1016/j.aap.2014.06.017.
Hooper E, Chapman L, Quinn A. The impact of precipi-tation on speed–flow relationships along a UK motorway corridor. Theoretical and Applied Climatology. 2013. doi: 10.1007/s00704-013-0999-5.
Kidando E, et al. Applying probabilistic model to quanti-fy influence of rainy weather on stochastic and dynamic transition of traffic conditions. Journal of Transportation Engineering, Part A: Systems. 2019;145(5).
Shang P, Li R, Liu Z, Li X. Inclement weather impacts on urban traffic conditions. CICTP2015; 2015. p. 2213–2227. doi: 10.1061/9780784479292.fm.
Zhang W, Li R, Shang P, Liu H. Impact analysis of rainfall on traffic flow characteristics in Beijing. International Journal of Intelligent Transportation Systems Research. 2019;17(2): 150–160. doi: 10.1007/s13177-018-0162-x.
Anda C, Erath A, Fourie PJ. Transport model-ling in the age of big data. International Journal of Urban Sciences. 2017;21(October): 19–42. doi: 10.1080/12265934.2017.1281150.
Jović J, Dorić V. Traffic and environmental street network modelling: Belgrade case study. Transport. 2010;25(2). doi: 10.3846/transport.2010.19.
Snelder M, Calvert S. Quantifying the impact of ad-verse weather conditions on road network perfor-mance. European Journal of Transport and Infrastruc-ture Research. 2016;16(1): 128–149. doi: 10.18757/ejtir.2016.16.1.3118.
Xu F, et al. Assessing the impact of rainfall on traffic operation of urban road network. Proceedings from the 13th COTA International Conference of Transportation Professionals (CICTP2013); 2013. p. 96, 82–89. doi: 10.1016/j.sbspro.2013.08.
Bureau of Public Roads. Traffic assignment manual for application with a large, high speed computer. Washing-ton, D.C.: U.S. Dept. of Commerce, Bureau of Public Roads, Office of Planning, Urban Planning Division; 1964.
Haider M, Spurr T. The design and development of large-scale traffic assignment models using geographic infor-mation systems. Transportation Research Board 85th An-nual Meeting, 22-26 Jan. 2006, DC Washington; 2006. p. 24.
Spiess H. Technical note – conical volume-delay func-tions. Transportation Science. 1990;24(2): 153–158. doi: 10.1287/trsc.24.2.153.
Akcelik R. Travel time functions for transport planning purposes: Davidson’s function, its time-dependent form and an alternative travel time function. Australian Road Research. 2000;21(December): 49–59.
Cheu RL, Lee DH, Xie C. An arterial speed estimation model fusing data from stationary and mobile sensors. Intelligent Transportation Systems, Proceedings. IEEE; 2001. p. 573–578. doi: 10.1109/ITSC.2001.948723.
Dowling R, Skabardonis A. Urban arterial speed-flow equations for travel demand models. A Transportation Research Board Conference, Innovations in Travel De-mand Modeling Conference, 21-23 May, Austin, Texas; 2008. p. 109–113.
Lu C, Zhao F, Hadi M. A travel time estimation meth-od for planning models considering signalized inter-sections. ICCTP Integrated Transportation Systems: Green, Intelligent, Reliable; 2010. p. 1993–2000. doi: 10.1061/41127(382)215.
Singh R, Dowling R. Improved speed-flow relation-ships: Application to transportation planning models. 7thTRB Conference on the Application of Transporta-tion Planning Methods. 1999. p. 340–349. http://docs.trb.org/00939750.pdf.
Tisato P. Suggestions for an improved Davidson travel time function. Australian Road Research. 1991;21(2): 85–110. http://arrbknowledge.com.
Lum KM, Fan HSL, Lam SH, Olszewski P. Speed-flow modeling of arterial roads in Singapore. Journal of Transportation Engineering. 1998;124(3): 213–222. doi: 10.1061/(ASCE)0733-947X(1998)124:3(213).
Neuhold R, Fellendorf M. Volume delay functions based on stochastic capacity. Journal of the Transpor-tation Research Board. 2014;2421(1): 93–102. doi: 10.3141/2421-11.
Agarwal M, Maze TH, Souleyrette R. Impacts of weath-er on urban freeway traffic flow characteristics and facility capacity. Proceedings of the 2005 Mid-Conti-nent Transportation Research Symposium; 2005. p. 14. http://www.ctre.iastate.edu/pubs/midcon2005/#weath-er.
Angel ML, Sando T, Chimba D, Kwigizile V. Effects of rain on traffic operations on Florida freeways. Trans-portation Research Record. 2014;2440(2440): 51–59. doi: 10.3141/2440-07.
Van Stralen W, Calvert S, Molin EJE. The influence of adverse weather conditions on the probability of con-gestion on Dutch motorways. European Journal of Transport & Infrastructure Research. 2015:15(4): 482–500. doi: 10.18757/ejtir.2015.15.4.3093.
Asamer J, Van Zuylen H. Saturation flow under adverse weather conditions. Journal of the Transportation Re-search Board. 2012;2258: 103–109. doi: 10.3141/2258-13.
Chodur J, Ostrowski K, Tracz M. Impact of saturation flow changes on performance of traffic lanes at signalised intersections. Procedia - Social and Behavioral Sciences, 6th International Symposium on Highway Capacity and Quality of Service; 2011. p. 600–611.
Sun H, Yang J, Wang L, Li L. Saturation flow rate and start-up lost time of dual-left lanes at signalized inter-section in rainy weather condition. Proceedings from the 13th COTA International Conference of Transportation Professionals (CICTP2013); 2013. p. 96, 270–279.
Smith BL, et al. An investigation into the impact of rain-fall on freeway traffic flow. Transportation Research Board 83rd Annual Meeting; 2004.
Jia Y, Du Y, Wu J. Impacts of rainfall weather on urban traffic in Beijing: Analysis and modeling. Transportation Research Board 94th Annual Meeting, 11-15 Jan. 2015, Washington DC, US; 2015. p. 14.
Pregnolato M, Ford A, Wilkinson SM, Dawson RJ. The impact of flooding on road transport: A depth-disrup-tion function. Transportation Research Part D: Trans-port and Environment. 2017;55: 67–81. doi: 10.1016/j.trd.2017.06.020.
Lam WHK, Tam ML, Cao X, Li X. Modeling the effects of rainfall intensity on traffic speed, flow, and density relationships for urban roads. Journal of Transporta-tion Engineering. 2013;139(7): 758–770. doi: 10.1061/(ASCE)TE.1943-5436.0000544.
Mitsakis E, Stamos I, Diakakis M, Salanova Grau JM. Impacts of high-intensity storms on urban transportation: Applying traffic flow control methodologies for quanti-fying the effects. International Journal of Environmental Science and Technology. 2014;11(8): 2145–2154.
Stamos I, Salanova Grau JM, Mitsakis E, Aifadopoulou G. Modeling effects of precipitation on vehicle speed: Floating car data approach. Transportation Research Re-cord. 2016;2551: 100–110. doi: 10.3141/2551-12.
Cambridge Systematics. Travel Demand Forecasting: Parameters and Techniques. Washington, D.C. NCHRP Report 716, 2013.
De Sousa JF, Rossi R. Computer-based modelling and optimization in transportation. Advances in Intelli-gent Systems and Computing. 2014;262: 293–306. doi: 10.1007/978-3-319-04630-3.
Horowitz A. Delay-volume relations for travel forecast-ing: Based on the 1985 highway capacity manual. Fed-eral Highway Administration U.S. Department of Trans-portation; 1991. https://www.fhwa.dot.gov/planning/tmip/publications/other_reports/delay_volume_relati.
Akcelik R. Travel time functions for transport planning purposes: Davidson’s function, its time dependent form and alternative travel time function. Australian Road Re-search. 1991;21(3): 49–59. http://arrbknowledge.com.
Highway capacity manual. Transportation Research Board; 2010.
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