Share:


Setting priority list for construction works of bicycle path segments based on Eckenrode rating and ARAS-F decision support method integrated in GIS

    Jurgis Zagorskas Affiliation
    ; Zenonas Turskis Affiliation

Abstract

Bicycling and walking are essential elements of sustainable transportation. These transportation modes effectively reduce the negative environmental impacts of transport and improve the quality of life. It is not only recognized by governments but also naturally become more prevalent in modern society. Nowadays research on bicycling and interest in related topics is dramatically increasing, but while researchers focus on modern technologies and collecting data from portable devices, there are quite a few studies on the effectiveness of investments in bicycle infrastructure, and even less discussed is a question how to set the priorities for construction works of the bicycle path network. To fill this gap this paper presents the universal method of ranking the priorities for development and renewal of bicycle pathway segments. The process is realized by hybrid Multi-Criteria Decision-Making (MCDM) Additive Ratio ASsessment with Fuzzy (ARAS-F) model, based on Eckenrode rating. Given criteria and their weights apply only to the specifics of this case study, and it need adaptation if used for other territories. Presented case study gives insight into the task of upgrading bicycle networks – how to overcome the inequalities, fragmentation and build missing links. Developed hybrid MCDM model integrated into Geographic Information System (GIS) allows quickly find rationally balanced solutions and develop bicycle network in efficient way.

Keyword : sustainable transportation, cycling, bicycle route, multi-criteria decision-making (MCDM), Eckenrode rating, additive ratio assessment with fuzzy (ARAS-F), criteria, value

How to Cite
Zagorskas, J., & Turskis, Z. (2020). Setting priority list for construction works of bicycle path segments based on Eckenrode rating and ARAS-F decision support method integrated in GIS. Transport, 35(2), 179-192. https://doi.org/10.3846/transport.2020.12478
Published in Issue
Apr 27, 2020
Abstract Views
836
PDF Downloads
347
Creative Commons License

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

References

Allen-Munley, C.; Daniel, J.; Dhar, S. 2004. Logistic model for rating urban bicycle route safety, Transportation Research Record: Journal of the Transportation Research Board 1878: 107–115. https://doi.org/10.3141/1878-13

Aziz, H. M. A.; Nagle, N. N.; Morton, A. M.; Hilliard, M. R.; White, D. A.; Stewart, R. N. 2018. Exploring the impact of walk–bike infrastructure, safety perception, and built-environment on active transportation mode choice: a random parameter model using New York City commuter data, Transportation 45(5): 1207–1229. https://doi.org/10.1007/s11116-017-9760-8

Bagočius, V.; Zavadskas, E. K.; Turskis, Z. 2014. Multi-person selection of the best wind turbine based on the multi-criteria integrated additive-multiplicative utility function, Journal of Civil Engineering and Management 20(4): 590–599. https://doi.org/10.3846/13923730.2014.932836

Bernardi, S.; La Paix-Puello, L.; Geurs, K. 2018. Modelling route choice of Dutch cyclists using smartphone data, Journal of Transport and Land Use 11(1): 883–900. https://doi.org/10.5198/jtlu.2018.1143

Chen, Y.; Yan, W.; Li, C.; Huang, Y.; Yang, L. 2018. Personalized optimal bicycle trip planning based on Q-learning algorithm, in 2018 IEEE Wireless Communications and Networking Conference (WCNC), 15–18 April 2018, Barcelona, Spain, 1–6. https://doi.org/10.1109/WCNC.2018.8377056

Convertino, M.; Muñoz-Carpena, R.; Chu-Agor, M. L.; Kiker, G. A.; Linkov, I. 2014. Untangling drivers of species distributions: global sensitivity and uncertainty analyses of MaxEnt, Environmental Modelling & Software 51: 296–309. https://doi.org/10.1016/j.envsoft.2013.10.001

Dahooie, J. H.; Zavadskas, E. K.; Abolhasani, M.; Vanaki, A.; Turskis, Z. 2018. A novel approach for evaluation of projects using an interval-valued fuzzy additive ratio assessment (ARAS) method: a case study of oil and gas well drilling projects, Symmetry 10(2): 45. https://doi.org/10.3390/sym10020045

Diez, J. M.; Lopez-Lambas, M. E.; Gonzalo, H.; Rojo, M.; Garcia-Martinez, A. 2018. Methodology for assessing the cost effectiveness of sustainable urban mobility plans (SUMPs). The case of the city of Burgos, Journal of Transport Geography 68: 22–30. https://doi.org/10.1016/j.jtrangeo.2018.02.006

Efimenko, D.; Bogumil, V.; Vlasov, V.; Demin, V.; Akhterov, A. 2018. Priority transfer management algorithm, based on interaction of the public transport dispatch systems information and traffic lights control, Transport and Telecommunication 19(4): 315–324. https://doi.org/10.2478/ttj-2018-0026

Ehrgott, M.; Wang, J. Y. T.; Raith, A.; Van Houtte, C. 2012. A biobjective cyclist route choice model, Transportation Research Part A: Policy and Practice 46(4): 652–663. https://doi.org/10.1016/j.tra.2011.11.015

Ghanayim, M.; Bekhor, S. 2018. Modelling bicycle route choice using data from a GPS-assisted household survey, European Journal of Transport and Infrastructure Research 18(2): 158–177. https://doi.org/10.18757/ejtir.2018.18.2.3228

Gil Solá, A.; Vilhelmson, B. 2018. Negotiating proximity in sustainable urban planning: a Swedish case, Sustainability 11(1): 31. https://doi.org/10.3390/su11010031

Gogas, M.; Papoutsis, K.; Nathanail, E. 2014. Optimization of decision-making in port logistics terminals: using analytic hierarchy process for the case of port of Thessaloniki, Transport and Telecommunication 15(4): 255–268. https://doi.org/10.2478/ttj-2014-0022

Gongora, D. A.; Baquero, J. J. D.; Franco, J. F.; Mura, I. 2018. Simulation to predict cyclists’ exposure to air pollution along bikeways, in 2018 Winter Simulation Conference (WSC), 9–12 December 2018, Gothenburg, Sweden, 2387–2398. https://doi.org/10.1109/WSC.2018.8632358

Gössling, S.; Humpe, A.; Litman, T.; Metzler, D. 2019. Effects of perceived traffic risks, noise, and exhaust smells on bicyclist behaviour: an economic evaluation, Sustainability 11(2): 408. https://doi.org/10.3390/su11020408

Gu, J.; Mohit, B.; Muennig, P. A. 2017. The cost-effectiveness of bike lanes in New York City, Injury Prevention 23(4): 239–243. https://doi.org/10.1136/injuryprev-2016-042057

Hashemi, H.; Mousavi, S. M.; Zavadskas, E. K.; Chalekaee, A.; Turskis, Z. 2018. A new group decision model based on grey-intuitionistic fuzzy-ELECTRE and VIKOR for contractor assessment problem, Sustainability 10(5): 1635. https://doi.org/10.3390/su10051635

Hashemkhani Zolfani, S.; Zavadskas, E. K.; Turskis, Z. 2013. Design of products with both international and local perspectives based on Yin-Yang balance theory and SWARA method, Economic Research – Ekonomska Istraživanja 26(2): 153–166. https://doi.org/10.1080/1331677X.2013.11517613

Hood, J.; Sall, E.; Charlton, B. 2011. A GPS-based bicycle route choice model for San Francisco, California, Transportation Letters: the International Journal of Transportation Research 3(1): 63–75. https://doi.org/10.3328/TL.2011.03.01.63-75

Jack, D.; Pantaleo, N.; Smith, C.; Yang, Q.; Thornburg, J.; Kinney, P.; Chillrud, S. 2018. Using spatially resolved pollution data to plan bicycle infrastructure, in ISEE Conference Abstracts 2018: 03.57. https://doi.org/10.1289/isesisee.2018.O01.03.57

Jereb, B.; Batkovič, T.; Herman, L.; Šipek, G.; Kovše, Š.; Gregorič, A.; Močnik, G. 2018. Exposure to black carbon during bicycle commuting – alternative route selection, Atmosphere 9(1): 21. https://doi.org/10.3390/atmos9010021

Kabak, M.; Erbaş, M.; Çetinkaya, C.; Özceylan, E. 2018. A GIS-based MCDM approach for the evaluation of bike-share stations, Journal of Cleaner Production 201: 49–60. https://doi.org/10.1016/j.jclepro.2018.08.033

Kang, L.; Fricker, J. D. 2018. Bicycle-route choice model incorporating distance and perceived risk, Journal of Urban Planning and Development 144(4): 04018041. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000485

Keshavarz Ghorabaee, M.; Zavadskas, E. K.; Turskis, Z.; Antuchevičienė, J. 2016. A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making, Economic Computation and Economic Cybernetics Studies and Research 50(3): 25–44.

Lawrence, B. M.; Oxley, J. A. 2019. You say one route, we observe four: using naturalistic observation to understand route-choices in cyclists, Safety Science 119: 207–213. https://doi.org/10.1016/j.ssci.2019.01.004

Lüdtke, N.; Panzeri, S.; Brown, M.; Broomhead, D. S.; Knowles, J.; Montemurro, M. A.; Kell, D. B. 2008. Information-theoretic sensitivity analysis: a general method for credit assignment in complex networks, Journal of The Royal Society Interface 5(19): 223–235. https://doi.org/10.1098/rsif.2007.1079

Luo, J.; Boriboonsomsin, K.; Barth, M. 2020. Consideration of exposure to traffic-related air pollution in bicycle route planning, Journal of Transport & Health 16: 100792. https://doi.org/10.1016/j.jth.2019.100792

Macmillan, A.; Connor, J.; Witten, K.; Kearns, R.; Rees, D.; Woodward, A. 2014. The societal costs and benefits of commuter bicycling: simulating the effects of specific policies using system dynamics modeling, Environmental Health Perspectives 122(4): 335–344. https://doi.org/10.1289/ehp.1307250

Majumdar, B. B.; Mitra, S. 2018. Analysis of bicycle route-related improvement strategies for two Indian cities using a stated preference survey, Transport Policy 63: 176–188. https://doi.org/10.1016/j.tranpol.2017.12.016

Medineckienė, M.; Zavadskas, E. K.; Björk, F.; Turskis, Z. 2015. Multi-criteria decision-making system for sustainable building assessment/certification, Archives of Civil and Mechanical Engineering 15(1): 11–18. https://doi.org/10.1016/j.acme.2014.09.001

Minet, L.; Stokes, J.; Scott, J.; Xu, J.; Weichenthal, S.; Hatzopoulou, M. 2018. Should traffic-related air pollution and noise be considered when designing urban bicycle networks?, Transportation Research Part D: Transport and Environment 65: 736–749. https://doi.org/10.1016/j.trd.2018.10.012

Muslihudin, M.; Susanti, T. S.; Maseleno, A. 2018. The priority of rural road development using fuzzy logic based simple additive weighting, International Journal of Pure and Applied Mathematics 118(8): 9–16.

Noureddine, M.; Ristic, M. 2019. Route planning for hazardous materials transportation: multicriteria decision making approach, Decision Making: Applications in Management and Engineering 2(1): 66–85.

Olariaga, O. D.; Moreno, L. P. 2019. Measurement of airport efficiency. The case of Colombia, Transport and Telecommunication 20(1): 40–51. https://doi.org/10.2478/ttj-2019-0004

Osaba, E.; Del Ser, J.; Bilbao, M. N.; Lopez-Garcia, P.; Nebro, A. J. 2018. Multi-objective design of time-constrained bike routes using bio-inspired meta-heuristics, Lecture Notes in Computer Science 10835: 197–210. https://doi.org/10.1007/978-3-319-91641-5_17

Otero, I.; Nieuwenhuijsen, M. J.; Rojas-Rueda, D. 2018. Health impacts of bike sharing systems in Europe, Environment International 115: 387–394. https://doi.org/10.1016/j.envint.2018.04.014

Palevičius, V.; Podviezko, A.; Sivilevičius, H.; Prentkovskis, O. 2018. Decision-aiding evaluation of public infrastructure for electric vehicles in cities and resorts of Lithuania, Sustainability 10(4): 904. https://doi.org/10.3390/su10040904

Pamučar, D.; Lukovac, V.; Božanić, D.; Komazec, N. 2018. Multi-criteria FUCOM-MAIRCA model for the evaluation of level crossings: case study in the Republic of Serbia, Operational Research in Engineering Sciences: Theory and Applications 1(1): 108–129.

Park, Y.; Akar, G. 2019. Why do bicyclists take detours? A multilevel regression model using smartphone GPS data, Journal of Transport Geography 74: 191–200. https://doi.org/10.1016/j.jtrangeo.2018.11.013

Petraška, A.; Čižiūnienė, K.; Jarašūnienė, A.; Maruschak, P.; Prentkovskis, O. 2017. Algorithm for the assessment of heavyweight and oversize cargo transportation routes, Journal of Business Economics and Management 18(6): 1098–1114. https://doi.org/10.3846/16111699.2017.1334229

Petraška, A.; Čižiūnienė, K.; Prentkovskis, O.; Jarašūnienė, A. 2018. Methodology of selection of heavy and oversized freight transportation system, Transport and Telecommunication 19(1): 45–58. https://doi.org/10.2478/ttj-2018-0005

Prentkovskis, O.; Erceg, Ž.; Stević, Ž.; Tanackov, I.; Vasiljević, M.; Gavranović, M. 2018. A new methodology for improving service quality measurement: Delphi-FUCOM-SERVQUAL model, Symmetry 10(12): 757. https://doi.org/10.3390/sym10120757

Pritchard, R. 2018. Revealed preference methods for studying bicycle route choice – a systematic review, International Journal of Environmental Research and Public Health 15(3): 470. https://doi.org/10.3390/ijerph15030470

Rossetti, T.; Guevara, C. A.; Galilea, P.; Hurtubia, R. 2018. Modeling safety as a perceptual latent variable to assess cycling infrastructure, Transportation Research Part A: Policy and Practice 111: 252–265. https://doi.org/10.1016/j.tra.2018.03.019

Ruzgys, A.; Volvačiovas, R.; Ignatavičius, Č.; Turskis, Z. 2014. Integrated evaluation of external wall insulation in residential buildings using SWARA-TODIM MCDM method, Journal of Civil Engineering and Management 20(1): 103–110. https://doi.org/10.3846/13923730.2013.843585

Saltelli, A.; Ratto, M.; Andres, T.; Campolongo, F.; Cariboni, J.; Gatelli, D.; Saisana, M.; Tarantola, S. 2008. Global Sensitivity Analysis. The Primer. John Wiley & Sons, Ltd. https://doi.org/10.1002/9780470725184

Servadio, J. L.; Convertino, M. 2018. Optimal information networks: application for data-driven integrated health in populations, Science Advances 4(2): e1701088. https://doi.org/10.1126/sciadv.1701088

Sharma, H. K.; Roy, J.; Kar, S.; Prentkovskis, O. 2018. Multi criteria evaluation framework for prioritizing Indian railway stations using modified rough AHP-MABAC method, Transport and Telecommunication 19(2): 113–127. https://doi.org/10.2478/ttj-2018-0010

Sivilevičius, H.; Zavadskas, E. K.; Turskis, Z. 2008. Quality attributes and complex assessment methodology of the asphalt mixing plant, Baltic Journal of Road & Bridge Engineering 3(3): 161–166.

Stević, Ž.; Pamučar, D.; Zavadskas, E. K,; Ćirović, G.; Prentkovskis, O. 2017. The selection of wagons for the internal transport of a logistics company: a novel approach based on rough BWM and rough SAW methods, Symmetry 9(11): 264. https://doi.org/10.3390/sym9110264

Stojić, G.; Mladenović, D.; Prentkovskis, O.; Vesković, S. 2018. A novel model for determining public service compensation in integrated public transport systems, Sustainability 10(9): 2969. https://doi.org/10.3390/su10092969

Šaparauskas, J.; Zavadskas, E. K.; Turskis, Z. 2011. Selection of facade’s alternatives of commercial and public buildings based on multiple criteria, International Journal of Strategic Property Management 15(2): 189–203. https://doi.org/10.3846/1648715X.2011.586532

Tanackov, I.; Prentkovskis, O.; Jevtić, Ž.; Stojić, G.; Ercegovac, P. 2019. A new method for Markovian adaptation of the non-Markovian queueing system using the hidden Markov model, Algorithms 12(7): 133. https://doi.org/10.3390/a12070133

Tsami, M.; Adamos, G.; Nathanail, E.; Budiloviča, E.; Jackiva, I.; Magginas, V. 2018. A decision tree approach for achieving high customer satisfaction at urban interchanges, Transport and Telecommunication 19(3): 194–202. https://doi.org/10.2478/ttj-2018-0016

Turskis, Z.; Dzitac, S.; Stankiuviene, A.; Šukys, R. 2019a. A fuzzy group decision-making model for determining the most influential persons in the sustainable prevention of accidents in the construction SMEs, International Journal of Computers Communications & Control 14(1): 90–106. https://doi.org/10.15837/ijccc.2019.1.3364

Turskis, Z., Goranin, N., Nurusheva, A., Boranbayev, S. 2019b. Information security risk assessment in critical infrastructure: a hybrid MCDM approach, Informatica 30(1): 187–211. https://doi.org/10.15388/Informatica.2019.203

Turskis, Z.; Juodagalvienė, B. 2016. A novel hybrid multi-criteria decision-making model to assess a stairs shape for dwelling houses, Journal of Civil Engineering and Management 22(8): 1078–1087. https://doi.org/10.3846/13923730.2016.1259179

Turskis, Z.; Lazauskas, M.; Zavadskas, E. K. 2012. Fuzzy multiple criteria assessment of construction site alternatives for non-hazardous waste incineration plant in Vilnius City, applying ARAS-F and AHP methods, Journal of Environmental Engineering and Landscape Management 20(2): 110–120. https://doi.org/10.3846/16486897.2011.645827

Turskis, Z.; Zavadskas, E. K. 2010a. A new fuzzy additive ratio assessment method (ARAS-F). Case study: the analysis of fuzzy multiple criteria in order to select the logistic centers location, Transport 25(4): 423–432. https://doi.org/10.3846/transport.2010.52

Turskis, Z.; Zavadskas, E. K. 2010b. A novel method for multiple criteria analysis: grey additive ratio assessment (ARAS-G) method, Informatica 21(4): 597–610.

Turskis, Z.; Zavadskas, E. K.; Antuchevičienė, J.; Kosareva, N. 2015. A hybrid model based on fuzzy AHP and fuzzy WASPAS for construction site selection, International Journal of Computers Communications & Control 10(6): 873–888. https://doi.org/10.15837/ijccc.2015.6.2078

Vasilienė-Vasiliauskienė, V.; Vasilis Vasiliauskas, A.; Golembovskij, R.; Meidutė-Kavaliauskienė, I.; Zavadskas, E. K.; Banaitis, A.; Govindan, K. 2019. Transportation systems’ impacts on the Vilnius housing market, Management Decision 57(2): 418–431. https://doi.org/10.1108/MD-01-2018-0117

Wagale, M.; Singh, A. P. 2019. The application of adaptive neuro-fuzzy inference system and fuzzy Delphi technique to assess socio-economic impacts of construction of rural roads, Transport and Telecommunication 20(4): 325–345. https://doi.org/10.2478/ttj-2019-0027

Wang, Y.; Yeo, G.-T. 2018. Intermodal route selection for cargo transportation from Korea to Central Asia by adopting fuzzy Delphi and fuzzy ELECTRE I methods, Maritime Policy & Management: the flagship journal of international shipping and port research 45(1): 3–18. https://doi.org/10.1080/03088839.2017.1319581

Wu, S. J.; Lun, L. W.; Chan, J.-Y.; Yang, L.; Wan, I.; Lin, H.-Y. 2018. Using mobile phones to crowd-source user flow data for assessing bike sharing site suitability, in 2018 IEEE Vehicular Networking Conference (VNC), 5–7 December 2018, Taipei, Taiwan, 1–2. https://doi.org/10.1109/VNC.2018.8628448

Zagorskas, J.; Zavadskas, E. K.; Turskis, Z.; Burinskienė, M.; Blumberga, A.; Blumberga, D. 2014. Thermal insulation alternatives of historic brick buildings in Baltic Sea Region, Energy and Buildings 78: 35–42. https://doi.org/10.1016/j.enbuild.2014.04.010

Zalakeviciute, R.; Buenaño, A.; Sannino, D.; Rybarczyk, Y. 2019. Urban air pollution mapping and traffic intensity: active transport application, in J. del Real Olvera (Ed.). Air Pollution: Monitoring, Quantification and Removal of Gases and Particles, 99–110. https://doi.org/10.5772/intechopen.79570

Zanjirani, D. M.; Hashemkhani Zolfani, S.; Prentkovskis, O. 2019. L.A.R.G. supplier selection based on integrating house of quality, Taguchi loss function and M.O.P.A., Economic Research – Ekonomska Istraživanja 32(1): 1944–1964. https://doi.org/10.1080/1331677X.2019.1635036

Zavadskas, E. K.; Nunić, Z.; Stjepanović, Ž.; Prentkovskis, O. 2018a. A novel rough range of value method (R-ROV) for selecting automatically guided vehicles (AGVs), Studies in Informatics and Control 27(4): 385–394. https://doi.org/10.24846/v27i4y201802

Zavadskas, E. K.; Stević, Ž.; Tanackov, I.; Prentkovskis, O. 2018b. A novel multicriteria approach – rough step-wise weight assessment ratio analysis method (R-SWARA) and its application in logistics, Studies in Informatics and Control 27(1): 97–106. https://doi.org/10.24846/v27i1y201810

Zavadskas, E. K.; Antuchevičienė, J.; Šaparauskas, J.; Turskis, Z. 2013a. MCDM methods WASPAS and MULTIMOORA: verification of robustness of methods when assessing alternative solutions, Economic Computation and Economic Cybernetics Studies and Research 47(2): 5–20.

Zavadskas, E. K.; Turskis, Z.; Volvačiovas, R.; Kildienė, S. 2013b. Multi-criteria assessment model of technologies, Studies in Informatics and Control 22(4): 249–258. https://doi.org/10.24846/v22i4y201301

Zavadskas, E. K.; Kaklauskas, A.; Turskis, Z.; Kalibatas, D. 2009. An approach to multi-attribute assessment of indoor environment before and after refurbishment of dwellings, Journal of Environmental Engineering and Landscape Management 17(1): 5–11. https://doi.org/10.3846/1648-6897.2009.17.5-11

Zavadskas, E. K.; Turskis, Z. 2010. A new additive ratio assessment (ARAS) method in multicriteria decision-making, Technological and Economic Development of Economy 16(2): 159–172. https://doi.org/10.3846/tede.2010.10

Zavadskas, E. K.; Turskis, Z.; Bagočius, V. 2015. Multi-criteria selection of a deep-water port in the Eastern Baltic Sea, Applied Soft Computing 26: 180–192. https://doi.org/10.1016/j.asoc.2014.09.019

Zavadskas, E. K.; Turskis, Z.; Vilutienė, T. 2010. Multiple criteria analysis of foundation instalment alternatives by applying additive ratio assessment (ARAS) method, Archives of Civil and Mechanical Engineering 10(3): 123–141. https://doi.org/10.1016/S1644-9665(12)60141-1

Zeng, J. 2018. Fostering path of ecological sustainable entrepreneurship within big data network system, International Entrepreneurship and Management Journal 14(1): 79–95. https://doi.org/10.1007/s11365-017-0466-3

Zhang, Y.; Mi, Z. 2018. Environmental benefits of bike sharing: a big data-based analysis, Applied Energy 220: 296–301. https://doi.org/10.1016/j.apenergy.2018.03.101

Zhang, Y.; Wen, H.; Qiu, F.; Wang, Z.; Abbas, H. 2019. iBike: intelligent public bicycle services assisted by data analytics, Future Generation Computer Systems 95: 187–197. https://doi.org/10.1016/j.future.2018.12.017