IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i17p6737-d401481.html
   My bibliography  Save this article

Concept of Mobile Application for Mobility as a Service Based on Autonomous Vehicles

Author

Listed:
  • Yinying He

    (Department of Transport Technology and Economics (KUKG), Faculty of Transportation Engineering and Vehicle Engineering (KJK), Budapest University of Technology and Economics (BME), 1111 Budapest, Hungary)

  • Csaba Csiszár

    (Department of Transport Technology and Economics (KUKG), Faculty of Transportation Engineering and Vehicle Engineering (KJK), Budapest University of Technology and Economics (BME), 1111 Budapest, Hungary)

Abstract

Mobility as a service (MaaS) is proposed to encourage travelers to choose sustainable mobility options and reduce use of individual car. In the future, mobility services based on autonomous vehicles (AVs) are also incorporated into MaaS. The objective of our work is to elaborate the concept of mobile application, aiding the MaaS based on AVs. We applied a system engineering process-oriented approach to determine the information system components, the functions as well as input and output data. Functions of back-end information system operation and front-end interface of application have been identified, as well as the information flows have been modeled. We highlighted the main differences between MaaS and MaaS based on AVs. We found that recording of event-based points and feedback management are regarded as pivot functions in this self-travel service. Our results facilitate the development of smartphone application for the MaaS based on AVs.

Suggested Citation

  • Yinying He & Csaba Csiszár, 2020. "Concept of Mobile Application for Mobility as a Service Based on Autonomous Vehicles," Sustainability, MDPI, vol. 12(17), pages 1-16, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:6737-:d:401481
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/17/6737/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/17/6737/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wong, Yale Z. & Hensher, David A. & Mulley, Corinne, 2020. "Mobility as a service (MaaS): Charting a future context," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 5-19.
    2. Khan, Nazmul Arefin & Habib, Muhammad Ahsanul & Jamal, Shaila, 2020. "Effects of smartphone application usage on mobility choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 932-947.
    3. Shen, Yu & Zhang, Hongmou & Zhao, Jinhua, 2018. "Integrating shared autonomous vehicle in public transportation system: A supply-side simulation of the first-mile service in Singapore," Transportation Research Part A: Policy and Practice, Elsevier, vol. 113(C), pages 125-136.
    4. Tian, Li-Jun & Sheu, Jiuh-Biing & Huang, Hai-Jun, 2019. "The morning commute problem with endogenous shared autonomous vehicle penetration and parking space constraint," Transportation Research Part B: Methodological, Elsevier, vol. 123(C), pages 258-278.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Panagiotis Georgakis & Adel Almohammad & Efthimios Bothos & Babis Magoutas & Kostantina Arnaoutaki & Gregoris Mentzas, 2020. "Heuristic-Based Journey Planner for Mobility as a Service (MaaS)," Sustainability, MDPI, vol. 12(23), pages 1-25, December.

    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. Tang, Zhe-Yi & Tian, Li-Jun & Wang, David Z.W., 2021. "Multi-modal morning commute with endogenous shared autonomous vehicle penetration considering parking space constraint," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 151(C).
    2. Fu, Zhexi & Chow, Joseph Y.J., 2022. "The pickup and delivery problem with synchronized en-route transfers for microtransit planning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    3. Markov, Iliya & Guglielmetti, Rafael & Laumanns, Marco & Fernández-Antolín, Anna & de Souza, Ravin, 2021. "Simulation-based design and analysis of on-demand mobility services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 170-205.
    4. Liu, Jianing & Wen, Xiao & Jian, Sisi, 2024. "Toward better equity: Analyzing travel patterns through a neural network approach in mobility-as-a-service," Transport Policy, Elsevier, vol. 153(C), pages 110-126.
    5. Lopez-Carreiro, Iria & Monzon, Andres & Lopez-Lambas, Maria E., 2021. "Comparison of the willingness to adopt MaaS in Madrid (Spain) and Randstad (The Netherlands) metropolitan areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 275-294.
    6. Zhang, Yufeng & Khani, Alireza, 2021. "Integrating transit systems with ride-sourcing services: A study on the system users’ stochastic equilibrium problem," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 95-123.
    7. He, Brian Yueshuai & Zhou, Jinkai & Ma, Ziyi & Wang, Ding & Sha, Di & Lee, Mina & Chow, Joseph Y.J. & Ozbay, Kaan, 2021. "A validated multi-agent simulation test bed to evaluate congestion pricing policies on population segments by time-of-day in New York City," Transport Policy, Elsevier, vol. 101(C), pages 145-161.
    8. Xi, Haoning & Aussel, Didier & Liu, Wei & Waller, S.Travis. & Rey, David, 2024. "Single-leader multi-follower games for the regulation of two-sided mobility-as-a-service markets," European Journal of Operational Research, Elsevier, vol. 317(3), pages 718-736.
    9. Sanjay Gupta & Kushagra Sinha, 2022. "Assessing the Factors Impacting Transport Usage of Mobility App Users in the National Capital Territory of Delhi, India," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    10. Manon Feys & Evy Rombaut & Lieselot Vanhaverbeke, 2020. "Experience and Acceptance of Autonomous Shuttles in the Brussels Capital Region," Sustainability, MDPI, vol. 12(20), pages 1-23, October.
    11. Wang, Senlei & Correia, Gonçalo Homem de Almeida & Lin, Hai Xiang, 2022. "Modeling the competition between multiple Automated Mobility on-Demand operators: An agent-based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    12. Xiaojuan Yu & Vincent A.C. van den Berg, 2024. "Human-driven vehicles’ cruising versus autonomous vehicles’ back- and-forth congestion: The effects on traveling, parking and congestion," Tinbergen Institute Discussion Papers 24-032/VIII, Tinbergen Institute.
    13. Nikitas, Alexandros & Cotet, Corneliu & Vitel, Alexandra-Elena & Nikitas, Nikolaos & Prato, Carlo, 2024. "Transport stakeholders’ perceptions of Mobility-as-a-Service: A Q-study of cultural shift proponents, policy advocates and technology supporters," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    14. Thierry Blayac & Maïté Stéphan, 2022. "Travel information provision and commuter behavior changes: Evidence from a french metropolis," Post-Print hal-03649092, HAL.
    15. 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.
    16. Ziakopoulos, Apostolos & Oikonomou, Maria G. & Vlahogianni, Eleni I. & Yannis, George, 2021. "Quantifying the implementation impacts of a point to point automated urban shuttle service in a large-scale network," Transport Policy, Elsevier, vol. 114(C), pages 233-244.
    17. Lo, Huai-Wei & Fang, Tzu-Yi & Lin, Sheng-Wei, 2024. "Integrating technological and strategic analysis: Evaluating the key determinants of transportation sustainability in taipei Mass Rapid Transit using the Rough-Fermatean DEMATEL approach," Socio-Economic Planning Sciences, Elsevier, vol. 94(C).
    18. Elnert Coenegrachts & Joris Beckers & Thierry Vanelslander & Ann Verhetsel, 2021. "Business Model Blueprints for the Shared Mobility Hub Network," Sustainability, MDPI, vol. 13(12), pages 1-24, June.
    19. Tiziana Campisi & Socrates Basbas & Anastasios Skoufas & Nurten Akgün & Dario Ticali & Giovanni Tesoriere, 2020. "The Impact of COVID-19 Pandemic on the Resilience of Sustainable Mobility in Sicily," Sustainability, MDPI, vol. 12(21), pages 1-24, October.
    20. Weixi Ren & Bo Yu & Yuren Chen & Kun Gao, 2022. "Divergent Effects of Factors on Crash Severity under Autonomous and Conventional Driving Modes Using a Hierarchical Bayesian Approach," IJERPH, MDPI, vol. 19(18), pages 1-22, September.

    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:12:y:2020:i:17:p:6737-:d:401481. 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.