IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i24p16519-d998707.html
   My bibliography  Save this article

Identifying Different Sources of the Benefit: Simulation of DRT Operation in the Heartland and Hinterland Regions

Author

Listed:
  • Hyunmyung Kim

    (Studio Galilei Inc., A-2106, Sinsu-ro 767, Suji-gu, Yongin-si 16827, Gyeonggi-do, Republic of Korea
    Department of Transportation Engineering, Myongji University, Yongin-si 17058, Gyeonggi-do, Republic of Korea)

  • Jaeheon Choi

    (Studio Galilei Inc., A-2106, Sinsu-ro 767, Suji-gu, Yongin-si 16827, Gyeonggi-do, Republic of Korea)

  • Sungjin Cho

    (Korea Maritime Institute (KMI), Haeyang-ro 301-26, Yeongdo-gu, Busan 49111, Republic of Korea)

  • Feng Liu

    (Transportation Research Institute (IMOB), Martelarenlaan 42, 3500 Hasselt, Belgium)

  • Hyungmin Jin

    (Studio Galilei Inc., A-2106, Sinsu-ro 767, Suji-gu, Yongin-si 16827, Gyeonggi-do, Republic of Korea)

  • Suhwan Lim

    (Studio Galilei Inc., A-2106, Sinsu-ro 767, Suji-gu, Yongin-si 16827, Gyeonggi-do, Republic of Korea)

  • Dongjun Kim

    (Studio Galilei Inc., A-2106, Sinsu-ro 767, Suji-gu, Yongin-si 16827, Gyeonggi-do, Republic of Korea)

  • Jun Lee

    (Korea Railroad Research Institute, Uiwang-si 16105, Gyeonggi-do, Republic of Korea)

  • Chang-Hyeon Joh

    (Department of Geography, Kyung Hee University, Seoul 02447, Republic of Korea)

Abstract

DRT service, designed to be flexible in time and space, follows the contemporary trend of on-demand transit provision. However, this type of service often suffers from low profitability due to small demand and/or high operation costs. DRT service is a local business in nature. The existing research primarily focuses on DRT service for regions with low transit demand, but it does not take into account service operation for other types of regions. This study aims to fill in this gap and identify the sources of benefit from DRT operations in varied types of regions. To this end, the analysis compares the DRT operation performance between overpopulated heartland and underpopulated hinterland regions; in each region, the benefit is identified through the difference in key performance indices between the simulated DRT and actual bus operation. The data on the road network and bus operation in Daegu, Korea, in 2021 are used for the DRT simulation. The results show that the heartland DRT benefits more from the reduced vehicle kilometers, while the hinterland DRT gains mostly from the reduced waiting time. Given that both DRT types outperform existing bus services, it is revealed that the heartland DRT is more reliable than the hinterland DRT due to the nature of regional characteristics.

Suggested Citation

  • Hyunmyung Kim & Jaeheon Choi & Sungjin Cho & Feng Liu & Hyungmin Jin & Suhwan Lim & Dongjun Kim & Jun Lee & Chang-Hyeon Joh, 2022. "Identifying Different Sources of the Benefit: Simulation of DRT Operation in the Heartland and Hinterland Regions," Sustainability, MDPI, vol. 14(24), pages 1-20, December.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16519-:d:998707
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/24/16519/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/24/16519/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Coutinho, Felipe Mariz & van Oort, Niels & Christoforou, Zoi & Alonso-González, María J. & Cats, Oded & Hoogendoorn, Serge, 2020. "Impacts of replacing a fixed public transport line by a demand responsive transport system: Case study of a rural area in Amsterdam," Research in Transportation Economics, Elsevier, vol. 83(C).
    2. Sergei Dytckov & Jan A. Persson & Fabian Lorig & Paul Davidsson, 2022. "Potential Benefits of Demand Responsive Transport in Rural Areas: A Simulation Study in Lolland, Denmark," Sustainability, MDPI, vol. 14(6), pages 1-21, March.
    3. Militão, Aitan M. & Tirachini, Alejandro, 2021. "Optimal fleet size for a shared demand-responsive transport system with human-driven vs automated vehicles: A total cost minimization approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 52-80.
    4. Zahra Navidi & Nicole Ronald & Stephan Winter, 2018. "Comparison between ad-hoc demand responsive and conventional transit: a simulation study," Public Transport, Springer, vol. 10(1), pages 147-167, May.
    5. Currie, Graham & Fournier, Nicholas, 2020. "Why most DRT/Micro-Transits fail – What the survivors tell us about progress," Research in Transportation Economics, Elsevier, vol. 83(C).
    6. Jooyoung Kim, 2020. "Assessment of the DRT System Based on an Optimal Routing Strategy," Sustainability, MDPI, vol. 12(2), pages 1-9, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cavallaro, Federico & Nocera, Silvio, 2023. "Flexible-route integrated passenger–freight transport in rural areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 169(C).
    2. Sharif Azadeh, Shadi & van der Zee, J. & Wagenvoort, M., 2022. "Choice-driven service network design for an integrated fixed line and demand responsive mobility system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 166(C), pages 557-574.
    3. Sergei Dytckov & Jan A. Persson & Fabian Lorig & Paul Davidsson, 2022. "Potential Benefits of Demand Responsive Transport in Rural Areas: A Simulation Study in Lolland, Denmark," Sustainability, MDPI, vol. 14(6), pages 1-21, March.
    4. Peter Džupka & Radovan Dráb & Marek Gróf & Tomáš Štofa, 2024. "Exploring Willingness to Pay across Different Passenger Traits," Sustainability, MDPI, vol. 16(2), pages 1-16, January.
    5. MELIS, Lissa & SÖRENSEN, Kenneth, 2021. "The real-time on-demand bus routing problem: What is the cost of dynamic requests?," Working Papers 2021003, University of Antwerp, Faculty of Business and Economics.
    6. Raoul Rothfeld & Mengying Fu & Miloš Balać & Constantinos Antoniou, 2021. "Potential Urban Air Mobility Travel Time Savings: An Exploratory Analysis of Munich, Paris, and San Francisco," Sustainability, MDPI, vol. 13(4), pages 1-20, February.
    7. Hatzenbühler, Jonas & Jenelius, Erik & Gidófalvi, Gyözö & Cats, Oded, 2023. "Modular vehicle routing for combined passenger and freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    8. Jiayi Li & Zhaocheng He & Jiaming Zhong, 2022. "The Multi-Type Demands Oriented Framework for Flex-Route Transit Design," Sustainability, MDPI, vol. 14(15), pages 1-23, August.
    9. Ghimire, Subid & Bardaka, Eleni & Monast, Kai & Wang, Juan & Wright, Waugh, 2024. "Policy, management, and operation practices in U.S. microtransit systems," Transport Policy, Elsevier, vol. 145(C), pages 259-278.
    10. Berrada, Jaâfar & Poulhès, Alexis, 2021. "Economic and socioeconomic assessment of replacing conventional public transit with demand responsive transit services in low-to-medium density areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 317-334.
    11. Jara-Diaz, Sergio R. & Muñoz-Paulsen, Esteban, 2024. "Cable cars: From optimal design to optimal pricing," Research in Transportation Economics, Elsevier, vol. 103(C).
    12. Igor Taran & Asem Karsybayeva & Vitalii Naumov & Kenzhegul Murzabekova & Marzhan Chazhabayeva, 2023. "Fuzzy-Logic Approach to Estimating the Fleet Efficiency of a Road Transport Company: A Case Study of Agricultural Products Deliveries in Kazakhstan," Sustainability, MDPI, vol. 15(5), pages 1-14, February.
    13. Yixue Zhang & Steven Farber & Mischa Young, 2022. "Eliminating barriers to nighttime activity participation: the case of on-demand transit in Belleville, Canada," Transportation, Springer, vol. 49(5), pages 1385-1408, October.
    14. Peer, Stefanie & Müller, Johannes & Naqvi, Asjad & Straub, Markus, 2024. "Introducing shared, electric, autonomous vehicles (SAEVs) in sub-urban zones: Simulating the case of Vienna," Transport Policy, Elsevier, vol. 147(C), pages 232-243.
    15. He, Dongdong & Ceder, Avishai (Avi) & Zhang, Wenyi & Guan, Wei & Qi, Geqi, 2023. "Optimization of a rural bus service integrated with e-commerce deliveries guided by a new sustainable policy in China," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 172(C).
    16. Fan, Qiaochu & van Essen, J. Theresia & Correia, Gonçalo H.A., 2024. "A bi-level framework for heterogeneous fleet sizing of ride-hailing services considering an approximated mixed equilibrium between automated and non-automated traffic," European Journal of Operational Research, Elsevier, vol. 315(3), pages 879-898.
    17. Fielbaum, Andrés & Tirachini, Alejandro & Alonso-Mora, Javier, 2023. "Economies and diseconomies of scale in on-demand ridepooling systems," Economics of Transportation, Elsevier, vol. 34(C).
    18. Rich, Jeppe & Seshadri, Ravi & Jomeh, Ali Jamal & Clausen, Sofus Rasmus, 2023. "Fixed routing or demand-responsive? Agent-based modelling of autonomous first and last mile services in light-rail systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    19. Nejc Geržinič & Niels Oort & Sascha Hoogendoorn-Lanser & Oded Cats & Serge Hoogendoorn, 2023. "Potential of on-demand services for urban travel," Transportation, Springer, vol. 50(4), pages 1289-1321, August.
    20. Babak Mehran & Yongzhe Yang & Sushreeta Mishra, 2020. "Analytical models for comparing operational costs of regular bus and semi-flexible transit services," Public Transport, Springer, vol. 12(1), pages 147-169, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16519-:d:998707. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.