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Impact of Side Friction on Travel Time Reliability of Urban Public Transit

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Abstract

Travel time reliability is the key aspect that indicates the quality of urban public transit service. The studies on travel time reliability of the public transit system in Indian traffic conditions are few. Also, the impact of side friction elements on travel time reliability has not been considered in the previous studies. Hence, the present study aims to quantify the different types of side friction elements and analyse their impact on the travel time reliability of the public bus transit system. The field data consisting of side friction elements, traffic volume, and travel time of public bus transit have been collected and extracted at two different road sections (divided and undivided) in the Mysore city (Karnataka, India) during weekdays and weekends. The data are grouped into static and dynamic side frictions. An approach has been proposed to represent different types of side friction elements with a single index called the Side Friction Index (SFI) using relative weight analysis. Travel time reliability is represented using measures such as Buffer Time Index (BTI), Planning Time Index (PTI), Travel Time Index (TTI) and Reliable Buffer Index (RBI). The impact of side friction on travel time reliability was found to be sensitive to traffic volume, and hence the thresholds for different traffic volume levels have been determined using K-means clustering method. It was observed from relative weight analysis that the static side friction has a higher weightage (0.509 and 0.327 for the undivided road and divided road respectively) than the dynamic side friction elements in describing the variation of travel time. The impact of side friction on reliability measures at different traffic volume levels has been studied and found to have a non-linear (exponential) relationship. The impact of SFI has been observed to be higher on TTI and PTI in comparison with BTI. The study outcomes show that the impact of side friction on TTI and PTI is sensitive to traffic volume, especially at higher traffic volume level and impact of side friction on BTI is less, especially at medium traffic volume level. The inference from the study shows that the impact of side friction elements varies with respect to the type of road (divided and undivided), traffic volume levels, different days of week (weekday and weekend), and different time periods of day.

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References

  1. Nam D, Park D, Khamkongkhun A (2005) Estimation of value of travel time reliability. J Adv Transp 39(1):39–61

    Article  Google Scholar 

  2. Kumar BA, Prasath GH, Vanajakshi L (2019) Dynamic bus scheduling based on real-time demand and travel time. Int J Civ Eng 17(9):1481–1489

    Article  Google Scholar 

  3. Mazloumi E, Currie G, Rose G (2009) Using GPS data to gain insight into public transport travel time variability. J Transp Eng 136(7):623–631

    Article  Google Scholar 

  4. Ma Z, Ferreira L, Mesbah M, Zhu S (2016) Modeling distributions of travel time variability for bus operations. J Adv Transp 50(1):6–24

    Article  Google Scholar 

  5. Biswas S, Chandra S, Ghosh I (2017) Effects of on-street parking in urban context: a critical review. Transp Dev Econ 3(1):10. https://doi.org/10.1007/s40890-017-0040-2

    Article  Google Scholar 

  6. Johnson JW (2000) A heuristic method for estimating the relative weight of predictor variables in multiple regression. Multivar Behav Res 35(1):1–9

    Article  Google Scholar 

  7. Chen C, Skabardonis A, Varaiya P (2003) Travel-time reliability as a measure of service. Transp Res Rec 1855(1):74–79

    Article  Google Scholar 

  8. Lyman K, Bertini RL (2008) Using travel time reliability measures to improve regional transportation planning and operations. Transp Res Rec 2046(1):1

    Article  Google Scholar 

  9. Susilawati S, Taylor MA, Somenahalli SV (2010) Travel time reliability measurement for selected corridors in the Adelaide Metropolitan area. J East Asia Soc Transp Stud 8:86–102

    Google Scholar 

  10. Alvarez P, Hadi M (2012) Time-variant travel time distributions and reliability metrics and their utility in reliability assessments. Transp Res Rec 2315(1):81–88

    Article  Google Scholar 

  11. Bharti AK, Sekhar CR, Chandra S (2018) Travel time reliability as a level of service measure for urban and inter-urban corridors in India. Curr Sci 114(9):1913–1922

    Article  Google Scholar 

  12. Muneera CP, Karuppanagounder K (2020) Performance prediction model for urban dual carriageway using travel time-based indices. Transp Dev Econ 6(1):2. https://doi.org/10.1007/s40890-019-0090-8

    Article  Google Scholar 

  13. Taylor MA (1982) Travel time variability—the case of two public modes. Transp Sci 16(4):507–521

    Article  Google Scholar 

  14. Ji Y, Ma W, Zhang SY (2018) Empirical analysis of bus travel time reliability: a case study in Shanghai. Int J Ind Syst Eng 29(4):478–493

    Google Scholar 

  15. Chepuri A, Joshi S, Arkatkar S, Joshi G, Bhaskar A (2019) Development of new reliability measure for bus routes using trajectory data. Transp Lett 12:1–2

    Google Scholar 

  16. Chepuri A, Kumar C, Bhanegaonkar P, Arkatkar SS, Joshi G (2019) Travel time reliability analysis on selected bus route of Mysore using GPS data. Transp Dev Econ 5(2):13

    Article  Google Scholar 

  17. Salini S, George S, Ashalatha R (2016) Effect of side frictions on traffic characteristics of urban arterials. Transp Res Proc 17:636–643

    Google Scholar 

  18. Kladeftiras M, Antoniou C (2013) Simulation-based assessment of double-parking impacts on traffic and environmental conditions. Transp Res Rec 2390(1):121–130

    Article  Google Scholar 

  19. Rao AM, Velmurugan S, Lakshmi KM (2017) Evaluation of influence of roadside frictions on the capacity of roads in Delhi, India. Transp Res Proc 25:4771–4782

    Google Scholar 

  20. Pal S, Roy SK (2019) Impact of side friction on performance of rural highways in India. J Infrastruct Syst 25(2):04019006

    Article  Google Scholar 

  21. Behbahani H, Samet MJ, Gilani VNM, Amini A (2017) Determining of the parking manoeuvre and the taxi blockage adjustment factor for the saturation flow rate at the outlet legs of signalized intersections: case Study from Rasht City (Iran). In: IOP conference series: materials science and engineering, vol 245, No. 4, p 042017. IOP Publishing

  22. Saw K, Katti BK, Joshi GJ (2020) Urban corridor travel time estimation modelling using fuzzy logic technique: a case study of Indian Metropolitan City. In: Transportation research. Springer, Singapore, pp 475–490. https://doi.org/https://doi.org/10.1007/978-981-32-9042-6_38

  23. Chiguma MLM (2007) Analysis of side friction impact on urban road links: case study Dar-es-Salaam. Royal Institute of Technology Stockholm, Stockholm

    Google Scholar 

  24. Gulivindala P, Mehar A (2018) Analysis of side friction on urban arterials. Transp Telecommun J 19(1):21–30. https://doi.org/10.2478/ttj-2018-0003

    Article  Google Scholar 

  25. Pal S, Roy SK (2016) Impact of roadside friction on Travel Speed and LOS of rural highways in India. Transp Dev Econ 2(2):9

    Article  Google Scholar 

  26. Guo H, Wang W, Guo W (2012) Micro-simulation study on the effect of on-street parking on vehicular flow. In: 15th International IEEE conference on intelligent transportation systems, pp 1840–1845. https://doi.org/https://doi.org/10.1109/ITSC.2012.6338713

  27. Gao J, Ozbay K (2016) Modeling double parking impacts on urban street. In: Proceedings of the transportation research board 95th annual meeting. Washington, DC

  28. Congress, Indian Roads (1990) Guidelines for capacity of roads in rural area. IRC code of Practice, IRC 64:1990, New Delhi

  29. Guo H, Gao Z, Yang X, Zhao X, Wang W (2011) Modeling travel time under the influence of on-street parking. J Transp Eng 138(2):229–235

    Article  Google Scholar 

  30. Tonidandel S, LeBreton JM, RWA web (2015) A free, comprehensive, web-based, and user-friendly tool for relative weight analyses. J Bus Psychol 30(2):207–216

  31. U.S. Department of Transportation, Federal Highway Administration (FHWA) (2006) Travel time reliability: Making it there on time, all the time. U.S. Department of Transportation, Washington, DC. https://ops.fhwa.dot.gov/publications/tt_reliability/TTR_Report.htm

  32. Bargegol I, Amlashi AT, Gilani VNM (2016) Estimation the saturation flow rate at far-side and nearside legs of signalized intersections–case study: rasht city. Proc Eng 161:226–234

    Article  Google Scholar 

  33. Shirmohammadi H, Hadadi F, Saeedian M (2019) Clustering analysis of drivers based on behavioral characteristics regarding road safety. Int J Civ Eng 17(8):1327–1340

    Article  Google Scholar 

  34. Kehagias D, Salamanis A, Tzovaras D (2015) Speed pattern recognition technique for short-term traffic forecasting based on traffic dynamics. IET Intell Transp Syst 9(6):646–653

    Article  Google Scholar 

  35. Elsa Shaji H, Tangirala AK, Vanajakshi L (2018) Evaluation of clustering algorithms for the prediction of trends in bus travel time. Transp Res Rec 2672(45):242–252

    Article  Google Scholar 

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All the authors have participated in (a) conception and design, or analysis and interpretation of the data; (b) drafting the article or revising it critically for important intellectual content; and (c) approval of the final version.

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Correspondence to Raviraj H. Mulangi.

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Harsha, M.M., Mulangi, R.H. Impact of Side Friction on Travel Time Reliability of Urban Public Transit. Int J Civ Eng 19, 1221–1237 (2021). https://doi.org/10.1007/s40999-021-00622-y

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