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GIS-based ride-sharing and DRT in Tehran city

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Abstract

In this paper, due to the inefficiency of implemented ride-sharing (RS) and demand responsive transport (DRT) systems in recent decades, these two systems are integrated in order to design a spatial system to manage numbers of single-passenger vehicles and, also, efficiently use public fleet capacity. In the designed system, after preparing and pre-processing on data, in the RS stage, the proposed system searches for fellow travellers for private vehicle users with priority given firstly to the applicants owning a private vehicle. And then, in the DRT stage, the remaining applicants are formed into DRT fellow traveller groups in which each DRT fellow traveller group is assigned an appropriate public vehicle and a parking lot. The proposed system is implemented based on real commuting trips taken in Tehran. The effectiveness of the system is mainly evaluated by comparing the decrease of mileage, gas consumption, and total travel time per vehicle.

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References

  • Amey AM, Attanucci J, Mishalani R (2011) Real-time ridesharing: opportunities and challenges in using mobile phone technology to improve rideshare services. Transp Res Rec: J Transp Res Board 2217:103–110

    Article  Google Scholar 

  • Bruni ME, Guerriero F, Beraldi P (2014) Designing robust routes for demand-responsive transport systems. Transp Res Part E: Logist Transp Rev 70:1–16

    Article  Google Scholar 

  • Chan Nelson, Shaheen Susan (2012) Ride Sharing in North America: past, present and future. Transp Rev 32(1):93–112. doi:10.1080/01441647.2011.621557

    Article  Google Scholar 

  • Chaube V, Kavanaugh AL, Pérez-Quinones MA (2010) Leveraging social networks to embed trust in rideshare programs. In: Proceedings of the Hawaii international conference on system sciences (HICSS), pp 1–8

  • Diana M, Quadrifoglio L, Pronello C (2009) A methodology for comparing distances traveled by performance-equivalent fixed-route and demand responsive transit services. Transp Plan Technol 32(4):377–399. doi:10.1080/03081060903119618

    Article  Google Scholar 

  • Edwards D, Watkins K (2013) Comparing fixed-route and demand-responsive feeder transit systems in real-world settings. Transp Res Rec 2352:128–135. doi:10.3141/2352-15

    Article  Google Scholar 

  • Faroqi H, Niaraki AS (2015) Multi-objective optimization based collision avoidance algorithm for an intelligence marine navigation. J Appl Sci 15:911–916

    Article  Google Scholar 

  • Faroqi H, Saadi Mesgari M (2016) Performance comparison between the multi-colony and multi-pheromone ACO algorithms for solving the multi-objective routing problem in a public transportation network. J Navig 69(01):197–210

    Article  Google Scholar 

  • Furuhata M, Dessouky M, Ordonez F, Brunet ME, Wang X, Koenig S (2013) Ridesharing: the state-of-the-art and future directions. Transp Res Part B: Methodol 57:28–46

    Article  Google Scholar 

  • Ghoseiri K, Haghani A, Hamedi M (2011) Real-time rideshare matching problem. Mid-Atlantic Universities Transportation Center, Berkeley

    Google Scholar 

  • Ichoua S, Gendreau M, Potvin JY (2006) Exploiting knowledge about future demands for real-time vehicle dispatching. Transp Sci 40(2):211–225

    Article  Google Scholar 

  • Jacobson S, King D (2009) Fuel saving and ridesharing in the US: motivations, limitations, and opportunities. Transp Res Part D: Transp Environ 14(1):14–21. doi:10.1016/j.trd.2008.10.001

    Article  Google Scholar 

  • Kawasaki S, Higuchi M, Gamba J, Murakami H (2009) On modeling ubiquitous cloud: estimation of traffic. WSEAS Trans Math 8(9):530–540

    Google Scholar 

  • Kelly K (2007) Casual carpooling-enhanced. J Public Transp 10(4):6, 119–130. doi:10.5038/2375-0901.10.4.6

  • Kowshik RR, Reddy PD, Gard J, Jovanis PP, Kitamura R (1994) Real-time rideshare matching using GIS. In: Proceedings of the IVHS America, vol 1(9), p 1

  • Kritikou Y, Dimitrakopoulos G, Dimitrellou E, Demestichas P (2009) A management scheme for improving transportation efficiency and contributing to the enhancement of the social fabric. Telem Inform 26(4):375–390. doi:10.1016/j.tele.2008.10.002

    Article  Google Scholar 

  • Laws R, Enoch MP, Ison SG, Potter S (2009) Demand responsive transport: a review of schemes in England and Wales. J Public Transp 12(1):19–37. doi:10.5038/2375-0901.12.1.2

    Article  Google Scholar 

  • Li X, Quadrifoglio L (2011) Vehicle optimal zone design for feeder transit services. Public Transp 3(1):89–104. doi:10.1007/s12469-011-0040-2

    Article  Google Scholar 

  • McCormack E, Nyerges T (1998) What transportation modeling needs from a GIS: a conceptual framework. Transp Plan Technol 21(1–2):5–23. doi:10.1080/03081069708717599

    Article  Google Scholar 

  • Miller HJ, Shaw SL (2001) Geographic information systems for transportation: principles and applications. Oxford University Press on Demand, Oxford

    Google Scholar 

  • Seyedabrishami S, Hasanpour S (2012) Impact of carpooling on fuel saving in urban transportation: case study of Tehran. Proc-Soc Behav Sci 54:323–331

    Article  Google Scholar 

  • Steger C (2005) Improving modal choice and transport efficiency with the virtual ridesharing agency. In: Intelligent transportation systems, 2005. Proceedings. 2005 IEEE. IEEE, pp 994–999

  • TCTTS (2011) Tehran transportation and traffic. Tehran Comprehensive Transportation & Traffic Studies Co. 17-20

  • Thill JC (ed) (2000) Geographic information systems in transportation research. Pergamon, Oxford

    Google Scholar 

  • Tjokroamidjojo D, Kutanoglu E, Taylor GD (2006) Quantifying the value of advance load information in truckload trucking. Transp Res Part E: Logist Transp Rev 42(4):340–357

    Article  Google Scholar 

  • White P (2008) Public transport: its planning, management and operation. Routledge, London

    Google Scholar 

  • Wong KI, Han AF, Yuen CW (2014) On dynamic demand responsive transport services with degree of dynamism. Transportmetrica A: Transp Sci 10(1):55–73

    Article  Google Scholar 

  • Yoo J-B, Hong B-K (2008) Intelligent traffic control system based on ubiquitous technology. In: INFOS2008, 27–29 March 2008, Cairo-Egypt, pp 78–83

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Acknowledgments

This work was supported by an Inha University research grant.

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Authors and Affiliations

  1. GIS Department, Faculty of Geodesy and Geomatics Engineering, GIS Excellence Center, K. N. Toosi University of Technology, Tehran, Iran

    Hamed Faroqi & Abolghasem Sadeghi-Niaraki

  2. Department of Geoinformatic Engineering, Inha University, Incheon, South Korea

    Abolghasem Sadeghi-Niaraki

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  1. Hamed Faroqi
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  2. Abolghasem Sadeghi-Niaraki
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Correspondence to Hamed Faroqi.

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Faroqi, H., Sadeghi-Niaraki, A. GIS-based ride-sharing and DRT in Tehran city. Public Transp 8, 243–260 (2016). https://doi.org/10.1007/s12469-016-0130-2

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