IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i6p5226-d1098241.html
   My bibliography  Save this article

The Effectiveness of an Intelligent Speed Assistance System with Real-Time Speeding Interventions for Truck Drivers: A Belgian Simulator Study

Author

Listed:
  • Bart De Vos

    (DriveSimSolutions, 2440 Geel, Belgium
    Transportation Research Institute (IMOB), School of Transportation Sciences, UHasselt–Hasselt University, 3500 Hasselt, Belgium)

  • Ariane Cuenen

    (Transportation Research Institute (IMOB), School of Transportation Sciences, UHasselt–Hasselt University, 3500 Hasselt, Belgium)

  • Veerle Ross

    (Transportation Research Institute (IMOB), School of Transportation Sciences, UHasselt–Hasselt University, 3500 Hasselt, Belgium
    FARESA, Evidence-Based Psychological Centre, 3500 Hasselt, Belgium)

  • Hélène Dirix

    (Transportation Research Institute (IMOB), School of Transportation Sciences, UHasselt–Hasselt University, 3500 Hasselt, Belgium)

  • Kris Brijs

    (Transportation Research Institute (IMOB), School of Transportation Sciences, UHasselt–Hasselt University, 3500 Hasselt, Belgium)

  • Tom Brijs

    (Transportation Research Institute (IMOB), School of Transportation Sciences, UHasselt–Hasselt University, 3500 Hasselt, Belgium)

Abstract

Speeding is one of the leading risk factors in road safety. Not only is it one of the leading causes of accidents, but it also has an extensive effect on the impact and consequences of accidents. This is especially the case for trucks, where the enforced speed limit is often dependent on local legislation and context rather than speed limit traffic signs. This study is part of the greater i-DREAMS project and aims to explore the effectiveness of an intelligent speed assistance system for truck drivers on different road types. To achieve this, a simulator experiment was performed with 34 professional truck drivers in Belgium. Participants first made a baseline drive, followed by two more drives, where they received visual information about the enforced speed limit but also visual and auditory warnings when exceeding the speed limit. The drives included different road environments with different speed limits. The results reveal a significant reduction in relevant parameters (i.e., average speed, minimum speed, maximum speed, and percentage of distance above the speed limit) when drivers received information and warnings about speeding while driving on a rural 1 × 1 road with a speed limit of 70 km/h (60 km/h for trucks). Further research is needed to validate this effect on other road types and under more-challenging conditions.

Suggested Citation

  • Bart De Vos & Ariane Cuenen & Veerle Ross & Hélène Dirix & Kris Brijs & Tom Brijs, 2023. "The Effectiveness of an Intelligent Speed Assistance System with Real-Time Speeding Interventions for Truck Drivers: A Belgian Simulator Study," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5226-:d:1098241
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/6/5226/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/6/5226/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sunstein, Cass R., 2017. "Nudges that fail," Behavioural Public Policy, Cambridge University Press, vol. 1(1), pages 4-25, May.
    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. Gary Bolton & Eugen Dimant & Ulrich Schmidt, 2018. "When a Nudge Backfires. Using Observation with Social and Economic Incentives to Promote Pro-Social Behavior," PPE Working Papers 0017, Philosophy, Politics and Economics, University of Pennsylvania.
    2. Alexander K. Koch & Dan Mønster & Julia Nafziger, 2023. "Nudging in complex environments," Economics Working Papers 2023-06, Department of Economics and Business Economics, Aarhus University.
    3. Linek, Maximilian & Traxler, Christian, 2021. "Framing and social information nudges at Wikipedia," Journal of Economic Behavior & Organization, Elsevier, vol. 188(C), pages 1269-1279.
    4. Diane Pelly & Orla Doyle, 2022. "Nudging in the workplace: increasing participation in employee EDI wellness events," Working Papers 202208, Geary Institute, University College Dublin.
    5. Dimant, Eugen & van Kleef, Gerben A. & Shalvi, Shaul, 2020. "Requiem for a Nudge: Framing effects in nudging honesty," Journal of Economic Behavior & Organization, Elsevier, vol. 172(C), pages 247-266.
    6. Enrico Rubaltelli & Lorella Lotto, 2021. "Nudging freelance professionals to increase their retirement pension fund contributions," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 16(2), pages 551-565, March.
    7. Bonilla-Mejía, Leonardo & Bottan, Nicolas L. & Ham, Andrés, 2019. "Information policies and higher education choices experimental evidence from Colombia," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 83(C).
    8. Carlos Andres Trujillo & Catalina Estrada-Mejia & Jose A Rosa, 2021. "Norm-focused nudges influence pro-environmental choices and moderate post-choice emotional responses," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-23, March.
    9. Meder, Björn & Fleischhut, Nadine & Osman, Magda, 2018. "Beyond the confines of choice architecture: A critical analysis," Journal of Economic Psychology, Elsevier, vol. 68(C), pages 36-44.
    10. Guilhem Lecouteux, 2022. "The Homer economicus narrative: from cognitive psychology to individual public policies," Working Papers hal-03791951, HAL.
    11. Sætra, Henrik Skaug, 2019. "When nudge comes to shove: Liberty and nudging in the era of big data," Technology in Society, Elsevier, vol. 59(C).
    12. Ennio Bilancini & Leonardo Boncinelli & Valerio Capraro & Roberto Di Paolo, 2020. "The effect of norm-based messages on reading and understanding COVID-19 pandemic response governmental rules," Journal of Behavioral Economics for Policy, Society for the Advancement of Behavioral Economics (SABE), vol. 4(S), pages 45-55, June.
    13. Tomas Folke & Giulia Bertoldo & Darlene D’Souza & Sonia Alì & Federica Stablum & Kai Ruggeri, 2021. "Boosting promotes advantageous risk-taking," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-10, December.
    14. Matija Franklin & Tomas Folke & Kai Ruggeri, 2019. "Optimising nudges and boosts for financial decisions under uncertainty," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-13, December.
    15. Benno Torgler, 2021. "Behavioral Taxation: Opportunities and Challenges," CREMA Working Paper Series 2021-25, Center for Research in Economics, Management and the Arts (CREMA).
    16. Goda, Gopi Shah & Levy, Matthew R. & Manchester, Colleen Flaherty & Sojourner, Aaron & Tasoff, Joshua, 2020. "Who is a passive saver under opt-in and auto-enrollment?," Journal of Economic Behavior & Organization, Elsevier, vol. 173(C), pages 301-321.
    17. Luca A. Panzone & Natasha Auch & Daniel John Zizzo, 2024. "Nudging the Food Basket Green: The Effects of Commitment and Badges on the Carbon Footprint of Food Shopping," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(1), pages 89-133, January.
    18. Diederich, Johannes & Goeschl, Timo & Waichman, Israel, 2023. "Self-nudging is more ethical, but less efficient than social nudging," Working Papers 0726, University of Heidelberg, Department of Economics.
    19. Kaiser, Micha & Bernauer, Manuela & Sunstein, Cass R. & Reisch, Lucia A., 2020. "The power of green defaults: the impact of regional variation of opt-out tariffs on green energy demand in Germany," Ecological Economics, Elsevier, vol. 174(C).
    20. Diederich, Johannes & Goeschl, Timo & Waichman, Israel, 2022. "Self-Nudging vs. Social Nudging in Social Dilemmas: An Experiment," Working Papers 0710, University of Heidelberg, Department of Economics.

    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:15:y:2023:i:6:p:5226-:d:1098241. 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.