IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i4p1912-d497109.html
   My bibliography  Save this article

Mobility Choices—An Instrument for Precise Automatized Travel Behavior Detection & Analysis

Author

Listed:
  • Thomas Feilhauer

    (FH Vorarlberg, University of Applied Sciences, 6850 Dornbirn, Austria)

  • Florian Braun

    (FH Vorarlberg, University of Applied Sciences, 6850 Dornbirn, Austria)

  • Katja Faller

    (FH Vorarlberg, University of Applied Sciences, 6850 Dornbirn, Austria)

  • David Hutter

    (FH Vorarlberg, University of Applied Sciences, 6850 Dornbirn, Austria)

  • Daniel Mathis

    (FH Vorarlberg, University of Applied Sciences, 6850 Dornbirn, Austria)

  • Johannes Neubauer

    (FH Vorarlberg, University of Applied Sciences, 6850 Dornbirn, Austria)

  • Jasmin Pogatschneg

    (FH Vorarlberg, University of Applied Sciences, 6850 Dornbirn, Austria)

  • Michelle Weber

    (FH Vorarlberg, University of Applied Sciences, 6850 Dornbirn, Austria)

Abstract

Within the Mobility Choices (MC) project we have developed an app that allows users to record their travel behavior and encourages them to try out new means of transportation that may better fit their preferences. Tracks explicitly released by the users are anonymized and can be analyzed by authorized institutions. For recorded tracks, the freely available app automatically determines the segments with their transportation mode; analyzes the track according to the criteria environment, health, costs, and time; and indicates alternative connections that better fit the criteria, which can individually be configured by the user. In the second step, the users can edit their tracks and release them for further analysis by authorized institutions. The system is complemented by a Web-based analysis program that helps authorized institutions carry out specific evaluations of traffic flows based on the released tracks of the app users. The automatic transportation mode detection of the system reaches an accuracy of 97%. This requires only minimal corrections by the user, which can easily be done directly in the app before releasing a track. All this enables significantly more accurate surveys of transport behavior than the usual time-consuming manual (non-automated) approaches, based on questionnaires.

Suggested Citation

  • Thomas Feilhauer & Florian Braun & Katja Faller & David Hutter & Daniel Mathis & Johannes Neubauer & Jasmin Pogatschneg & Michelle Weber, 2021. "Mobility Choices—An Instrument for Precise Automatized Travel Behavior Detection & Analysis," Sustainability, MDPI, vol. 13(4), pages 1-23, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:1912-:d:497109
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/4/1912/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/4/1912/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Beirão, Gabriela & Sarsfield Cabral, J.A., 2007. "Understanding attitudes towards public transport and private car: A qualitative study," Transport Policy, Elsevier, vol. 14(6), pages 478-489, November.
    2. Sallis, James F. & Frank, Lawrence D. & Saelens, Brian E. & Kraft, M. Katherine, 2004. "Active transportation and physical activity: opportunities for collaboration on transportation and public health research," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(4), pages 249-268, May.
    3. Brög, Werner & Erl, Erhard & Ker, Ian & Ryle, James & Wall, Rob, 2009. "Evaluation of voluntary travel behaviour change: Experiences from three continents," Transport Policy, Elsevier, vol. 16(6), pages 281-292, November.
    4. Patrick Bonnel & Etienne Hombourger & Ana-Maria Olteanu-Raimond & Zbigniew Smoreda, 2015. "Passive Mobile Phone Dataset to Construct Origin-destination Matrix: Potentials and Limitations," Post-Print halshs-01664219, HAL.
    5. Woods, Ruth & Masthoff, Judith, 2017. "A comparison of car driving, public transport and cycling experiences in three European cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 211-222.
    6. Evangelia Anagnostopoulou & Efthimios Bothos & Babis Magoutas & Johann Schrammel & Gregoris Mentzas, 2018. "Persuasive Technologies for Sustainable Mobility: State of the Art and Emerging Trends," Sustainability, MDPI, vol. 10(7), pages 1-22, June.
    7. Juan De Dios Ortúzar & Jimmy Armoogum & Jean‐Loup Madre & Françoise Potier, 2011. "Continuous Mobility Surveys: The State of Practice," Transport Reviews, Taylor & Francis Journals, vol. 31(3), pages 293-312.
    8. Dea van Lierop & Madhav G. Badami & Ahmed M. El-Geneidy, 2018. "What influences satisfaction and loyalty in public transport? A review of the literature," Transport Reviews, Taylor & Francis Journals, vol. 38(1), pages 52-72, January.
    9. Muhammad Shafique & Eiji Hato, 2015. "Use of acceleration data for transportation mode prediction," Transportation, Springer, vol. 42(1), pages 163-188, January.
    10. Isabelle Laplace & Nathalie Lenoir, 2017. "Beyond traditional value of time: passenger behavior for multimodal door-to-door travels in the age of information technologies," Post-Print hal-02009254, HAL.
    11. Tao Feng & Harry J.P. Timmermans, 2016. "Comparison of advanced imputation algorithms for detection of transportation mode and activity episode using GPS data," Transportation Planning and Technology, Taylor & Francis Journals, vol. 39(2), pages 180-194, March.
    12. Nathalie Lenoir & Isabelle Laplace, 2017. "Beyond traditional value-of-time: passenger behavior for multimodal door-to-door travels in the age of information technologies," Post-Print hal-01704461, HAL.
    13. Clauss, Thomas & Döppe, Sebastian, 2016. "Why do urban travelers select multimodal travel options: A repertory grid analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 93(C), pages 93-116.
    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. Dong-Gyun Ku & Jung-Sik Um & Young-Ji Byon & Joo-Young Kim & Seung-Jae Lee, 2021. "Changes in Passengers’ Travel Behavior Due to COVID-19," Sustainability, MDPI, vol. 13(14), pages 1-16, July.

    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. De Vos, Jonas, 2018. "Do people travel with their preferred travel mode? Analysing the extent of travel mode dissonance and its effect on travel satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 261-274.
    2. Nguyen-Phuoc, Duy Q. & Phuong Tran, Anh Thi & Nguyen, Tiep Van & Le, Phuong Thi & Su, Diep Ngoc, 2021. "Investigating the complexity of perceived service quality and perceived safety and security in building loyalty among bus passengers in Vietnam – A PLS-SEM approach," Transport Policy, Elsevier, vol. 101(C), pages 162-173.
    3. Juan de Oña, 2022. "Service quality, satisfaction and behavioral intentions towards public transport from the point of view of private vehicle users," Transportation, Springer, vol. 49(1), pages 237-269, February.
    4. Xiaoqi Feng & Zhiqiang Feng & Thomas Astell-Burt, 2017. "Perceived public transport infrastructure modifies the association between public transport use and mental health: Multilevel analyses from the United Kingdom," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-17, August.
    5. Shuli Luo & Sylvia Y He, 2021. "Using data mining to explore the spatial and temporal dynamics of perceptions of metro services in China: The case of Shenzhen," Environment and Planning B, , vol. 48(3), pages 449-466, March.
    6. Allen, Jaime & Muñoz, Juan Carlos & Rosell, Jordi, 2019. "Effect of a major network reform on bus transit satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 310-333.
    7. Dea Lierop & Ahmed El-Geneidy, 2018. "Is having a positive image of public transit associated with travel satisfaction and continued transit usage? An exploratory study of bus transit," Public Transport, Springer, vol. 10(2), pages 241-256, August.
    8. Ali Alamdar Moghaddam & Hamid Mirzahossein & Robert Guzik, 2022. "Comparing Inequality in Future Urban Transport Modes by Doughnut Economy Concept," Sustainability, MDPI, vol. 14(21), pages 1-24, November.
    9. Yanjun Qin & Haiyong Luo & Fang Zhao & Zhongliang Zhao & Mengling Jiang, 2018. "A traffic pattern detection algorithm based on multimodal sensing," International Journal of Distributed Sensor Networks, , vol. 14(10), pages 15501477188, October.
    10. Díez-Mesa, Francisco & de Oña, Rocio & de Oña, Juan, 2018. "Bayesian networks and structural equation modelling to develop service quality models: Metro of Seville case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 1-13.
    11. Chowdhury, Subeh & Ceder, Avishai (Avi), 2016. "Users’ willingness to ride an integrated public-transport service: A literature review," Transport Policy, Elsevier, vol. 48(C), pages 183-195.
    12. Audronė Minelgaitė & Renata Dagiliūtė & Genovaitė Liobikienė, 2020. "The Usage of Public Transport and Impact of Satisfaction in the European Union," Sustainability, MDPI, vol. 12(21), pages 1-13, November.
    13. Risdiyanto Risdiyanto & Ahmad Munawar & Muhammad Zudhy Irawan & Miftahul Fauziah & Prawira Fajarindra Belgiawan, 2022. "Why Do Students Choose Buses over Private Motorcycles and Motorcycle-Based Ride-Sourcing? A Hybrid Choice Approach," Sustainability, MDPI, vol. 14(9), pages 1-19, April.
    14. Hoffmann, Christin & Abraham, Charles & Skippon, Stephen M. & White, Mathew P., 2018. "Cognitive construction of travel modes among high-mileage car users and non-car users – A Repertory Grid analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 216-233.
    15. Nur Sabahiah Abdul Sukor & Surachai Airak & Sitti Asmah Hassan, 2021. "“More Than a Free Bus Ride”—Exploring Young Adults’ Perceptions of Free Bus Services Using a Qualitative Approach: A Case Study of Penang, Malaysia," Sustainability, MDPI, vol. 13(6), pages 1-18, March.
    16. De Vos, Jonas & Singleton, Patrick A., 2020. "Travel and cognitive dissonance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 525-536.
    17. Cass, Noel & Faulconbridge, James, 2016. "Commuting practices: New insights into modal shift from theories of social practice," Transport Policy, Elsevier, vol. 45(C), pages 1-14.
    18. Dacko, Scott G. & Spalteholz, Carolin, 2014. "Upgrading the city: Enabling intermodal travel behaviour," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 222-235.
    19. Xuan Phuong Nguyen, 2019. "The Bus Transportation Issue And People Satisfaction With Public Transport In Ho Chi Minh City ," Journal of Mechanical Engineering Research & Developments (JMERD), Zibeline International Publishing, vol. 42(1), pages 10-16, January.
    20. Alessandro Vitale & Giuseppe Guido & Daniele Rogano, 2016. "A smartphone based DSS platform for assessing transit service attributes," Public Transport, Springer, vol. 8(2), pages 315-340, 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:13:y:2021:i:4:p:1912-:d:497109. 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.