Evaluation of Street Lighting Efficiency Using a Mobile Measurement System
Open accessAbstract
The issue concerns the initial stage of work on a method for performing a rapid assessment of the energy efficiency and illuminance of a street lighting installation. The proposed method is based on simultaneous measurement of illuminance from three lux meters placed on the roof of the vehicle. The data are acquired in road traffic, while the vehicle is driving. The proposed solution will allow in the future to quickly and reproducibly obtain data about the lighting parameters of the studied road section. The illumination values are localised using Global Navigation Satellite System (GNSS). Based on the collected measurement data, with the use of terrain maps, geographic information system (GIS) data and installation design documentation, it will be possible to determine in detail the parameters of energy efficiency indicators for a selected section of the street for the entire street according to the EN13201-5 standard. Preliminary tests were conducted on a section of about one kilometer of street illuminated in class C3. Detailed measurements reveal high variation of obtained energy indicators DP and DE for each road section. The reason for this condition is the variation of power, installation geometry and the presence of obstacles to light.
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In Europe, 1.3% of total energy consumption comes from roads.
“While according to Tomczuk et al. [65], in Europe, 1.3% of total energy consumption comes from roads.”
From Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey (2022) · cites this paper as Tomczuk et al. [65]
Two-thirds of existing lights do not meet the standard they should.
“Then two-thirds of the existing lights do not meet the standard that they should.”
From Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey (2022) · cites this paper as Tomczuk et al. [65]
Cites
Effect of lighting on frequency and severity of road accidents
Yannis, G., Kondyli, A., & Mitzalis, N. (2013) · Proceedings of the Institution of Civil Engineers - Transport · doi:10.1680/tran.11.00047 · Cited by 51 · see citing works
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Machine Learning Methods in Smart Lighting Toward Achieving User Comfort: A Survey
Putrada, A. G., Abdurohman, M., Perdana, D., & Nuha, H. H. (2022) · IEEE Access · doi:10.1109/access.2022.3169765 · Cited by 101 · see citing works
“While according to Tomczuk et al. [65], in Europe, 1.3% of total energy consumption comes from roads.”
MethodInfluential
- Authors
- Tomczuk, P., Chrzanowicz, M., Jaskowski, P., & Budzynski, M.
- Affiliations
- Warsaw University of Technology (PL)
- Faculty of Civil and Environmental Engineering, Gdansk University of Technology, 80-233 Gdansk, Poland
- Corresponding author
- Jaskowski, Piotr
- Venue
- Energies
- Publisher
- MDPI AG
- Published
- 2021-06-27
- Volume
- 14
- Issue
- 13
- Pages
- 3872
- ISSN
- 1996-1073 (ISSN-L)
- OpenAlex
- W3175127494
- Cited by
- 13
- References
- 1
- Citations by year
- 2026: 3 · 2025: 3 · 2023: 2 · 2022: 4 · 2021: 1
- FWCI
- 0.72
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Energies (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Impact of Light on Environment and Health
- Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Energy Efficiency and Management
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Keywords
- street lighting, energy efficiency, illuminance measurement, mobile measurement system, GNSS positioning, energy efficiency indicators, light pollution
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