Correction: What is the General Population’s Perception of Smart Motorways in the UK?
Abstract
Motorway users have various opinions about the types of smart motorways. Motorway utilization can be affected if road users have a negative perception of certain types of smart motorways, particularly on the topic of safety. There are three types of smart motorways that can be found in the UK. These are Controlled Smart Motorways (CSM), Dynamic Hard Shoulder (DHS), and All-Lane Running (ALR). This study focuses on the comparison of ALR and DHS smart motorways as ALR smart motorways are developed to replace and improve upon DHS smart motorways. The aim of this project is to understand how the general population perceives smart motorways in the UK. This aim will be achieved by answering a series of these research questions: (1) How does existing knowledge of smart motorways affect the perception of smart motorways; (2) How does age affect the perception of smart motorways; (3) How does car ownership affect the perception of smart motorways? Data were collected using an online survey disseminated to the UK adult population of vehicle and non-vehicle drivers via social media and advertisements. Descriptive statistics and cluster analysis were used to analyze the dataset and find similarity clusters. The primary research shows that ~57% of the survey respondents had never heard of or did not know the meaning of the 3 different types of smart motorways and only ~13% of respondents fully understand the different types. Car owners in both cluster analysis models show substantial variation in the results of the comfort / smart motorway choice variables. This research demonstrates that greater knowledge and awareness about smart motorways are required to improve the perception of smart motorways. It would seem that this is particularly true for all-lane running smart motorways which are both the newest and most physically different type of smart motorway with their removal of the hard shoulder.
Correction: Ethics approval has been updated and PDF was also updated.
Full text article
References
Sinharay, S. (2010). An overview of statistics in education. In International Encyclopedia of Education (pp. 1–11). Elsevier Ltd. https://doi.org/10.1016/B978-0-08-044894-7.01719-X
Creswell, J. W., & Plano-Clark, V. L. (2011). Choosing a Mixed Methods Design.pdf. In Designing and Conducting Mixed Methods Research (p.457). https://doi.org/10.18553/jmcp.2008.14.S6-B.21
Riffenburgh, R. H. (2012). Statistics in Medicine: Vol. 3rd ed. Academic Press.
Highways England. (2016). When to use a hard shoulder Smart motorways. www.highways.gov.uk/smartmotorways
Callaghan, N., Avery, T., & Mulville, M. (2017). “Smart” motorway innovation for achieving greater safety and hard shoulder management. Association of Researchers in Construction Management, ARCOM - 33rd Annual Conference 2017, Proceeding, 745–754. https://doi.org/10.21427/D7N50T
Kaur, P., Stoltzfus, J., & Yellapu, V. (2018). Descriptive statistics. International Journal of Academic Medicine, 4(1), 60–63. https://doi.org/10.4103/IJAM.IJAM_7_18
Jallow, H., Renukappa, S., & Alneyadi, A. (2019). The Concept of Smart Motorways. 2019 3rd International Conference on Smart Grid and Smart Cities (ICSGSC), 18–21. https://doi.org/10.1109/ICSGSC.2019.00-25
Statistics Solutions. (2020). Conduct and Interpret a Cluster Analysis. Regression [Online]. http://www.statisticssolutions.com
Department for Transport. (2020). Smart Motorway Safety - Evidence Stocktake and Action Plan. Department for Transport, January, 1–78. www.gov.uk/dftGeneralenquiries:https://forms.dft.gov.uk
IBM. (2021). Predictor Importance. https://www.ibm.com/docs/en/spss- modeler/18.1.0topic=SS3RA7_18.1.0/modeler_mainhelp_client_ddita/clementine/idh_common_predictor_importance.htm
National Highways. (2021). Dynamic Hard Shoulder enhancements. National Highways. /our-work/smart-motorways-evidence- stocktake/dynamic-hard-shoulder-enhancements/
Transport Committee. (2021). Rollout and safety of smart motorways Third Report of Session 2021–22. https://committees.parliament.uk/publications/7703/documents/80447/default/
Authors
Copyright (c) 2023 Luke Lynch, Dr. Elisavet Andrikopoulou, Dr. Nima Dadashzade
This work is licensed under a Creative Commons Attribution 4.0 International License.
- The Author shall grant to the Publisher and its agents the nonexclusive perpetual right and license to publish, archive, and make accessible the Work in whole or in part in all forms of media now or hereafter known under a Creative Commons Attribution 4.0 License or its equivalent, which, for the avoidance of doubt, allows others to copy, distribute, and transmit the Work under the following conditions:
- Attribution: other users must attribute the Work in the manner specified by the author as indicated on the journal Web site;
With the understanding that the above condition can be waived with permission from the Author and that where the Work or any of its elements is in the public domain under applicable law, that status is in no way affected by the license.
- The Author is able to enter into separate, additional contractual arrangements for the nonexclusive distribution of the journal's published version of the Work (e.g., post it to an institutional repository or publish it in a book), as long as there is provided in the document an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post online a pre-publication manuscript (but not the Publisher's final formatted PDF version of the Work) in institutional repositories or on their Websites prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (see The Effect of Open Access). Any such posting made before acceptance and publication of the Work shall be updated upon publication to include a reference to the Publisher-assigned DOI (Digital Object Identifier) and a link to the online abstract for the final published Work in the Journal.
- Upon Publisher's request, the Author agrees to furnish promptly to Publisher, at the Author's own expense, written evidence of the permissions, licenses, and consents for use of third-party material included within the Work, except as determined by Publisher to be covered by the principles of Fair Use.
- The Author represents and warrants that:
- The Work is the Author's original work;
- The Author has not transferred, and will not transfer, exclusive rights in the Work to any third party;
- The Work is not pending review or under consideration by another publisher;
- The Work has not previously been published;
- The Work contains no misrepresentation or infringement of the Work or property of other authors or third parties; and
- The Work contains no libel, invasion of privacy, or other unlawful matter.
- The Author agrees to indemnify and hold Publisher harmless from Author's breach of the representations and warranties contained in Paragraph 7 above, as well as any claim or proceeding relating to Publisher's use and publication of any content contained in the Work, including third-party content.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Article Details
Accepted 2023-03-30
Published 2023-12-18