Fotios, S. orcid.org/0000-0002-2410-7641 (2026) Using segmented regression to estimate the optimal illuminance for pedestrian reassurance. Lighting Research & Technology. 14771535261431190. ISSN: 1477-1535
Abstract
CIE 115:2010 gives guidance for the design of road lighting that feeds into the design standards of many nations. There is, however, an emerging awareness that the guidance in CIE 115:2010 needs amendment, and this is being targeted through rapid and long-term revisions. One aim of the rapid revision is to provide an empirical basis for the guidance, with that to be founded in what is already known rather than waiting for further research to be conducted. For P-class lighting, applied to situations where pedestrians are the target user, it has been suggested that pedestrian reassurance (the feeling of safety) is a suitable basis for establishing optimal lighting conditions. This article analyses the relationship between measures of pedestrian reassurance (after-dark evaluations and the difference between daylight and after-dark evaluations) and the conventional measures of lighting in the P class (mean, minimum and uniformity of horizontal illuminance) using the results from previous field studies investigating this. For these data, the day-dark difference provided a better association with illuminance than did after-dark ratings. For the day-dark difference, the association with mean illuminance was better than that with minimum illuminance or uniformity. Segmented regression suggested an optimum mean illuminance of 8.76 lx. To fit within the existing P classes, this could be rounded down to class P3 (mean illuminance = 7.5 lx).
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © The Chartered Institution of Building Services Engineers 2026. This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
| Dates: |
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| Institution: | The University of Sheffield |
| Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > School of Architecture and Landscape |
| Date Deposited: | 09 Apr 2026 08:07 |
| Last Modified: | 09 Apr 2026 11:45 |
| Status: | Published online |
| Publisher: | SAGE Publications |
| Refereed: | Yes |
| Identification Number: | 10.1177/14771535261431190 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:239851 |
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