1. Jin, H., Jin, S., Chen, L. et al. Research on the Lighting Performance of LED Street Lights With Different Colour Temperatures // IEEE Photonics Journal, 2015, Vol. 7, # 6, pp. 1–9. 2. Dursun, S., Terzi, U.K., Akar, O. et al. Comparative Analysis of Lighting Elements’ Effects on Electric System // European Journal of Technique (EJT), 2021, Vol. 11, #.2. 3. Onaygil, S., Guler, O., Erkin, E. Cost Analyses of LED Luminaires In Road Lighting // Light & Engineering, 2012, Vol. 20, #. 2, pp. 39–45. 4. Cengiz, M.S. The Relationship between Maintenance Factor and Lighting Level in Tunnel Lighting // Light & Engineering, 2019, Vol. 27, # 3, pp. 75–88. 5. Pracki, P. A proposal to classify road lighting energy efficiency // Lighting Research & Technology, 2011, Vol. 43, # 3, pp. 271–280. 6. Falchi, F., Cinzano, P., Elvidge, C.D., et. al. Limiting the impact of light pollution on human health, environment and stellar visibility // Journal of Environmental Management, 2011, Vol. 92, # 10, pp. 2714–2722. 7. Akgun, I., Ustaoglu, E. Multi–Methodological Design Framework for Roadway Illumination // Light & Engineering, 2022, Vol. 30, # 1, pp. 39–50. 8. International Dark Sky Association, “Visibility, Environmental and Astronomical Issues Associated with Blue Rich White Outdoor Lighting”, Technical Report, 2010. 9. CIE (Commission Internationale de l’Eclairage), “Road lighting as an accident countermeasure”, Vienna (Austria): CIE No. 093–1993, pp. 1–43, 1993. 10. Elvik, R. Meta-analysis of evaluation of public lighting as accident countermeasure // Transp. Res. Rec., 1995, 1485, pp. 112–123. 11. Wanvik, A. Effects of road lighting: an analysis based on Dutch accident statistics 1987–2006 / Dutch statistics report, 2006. 12. Sun, C., Lee, X., I. Moreno, I., et al. Design of LED Street Lighting Adapted for Free-Form Roads // IEEE Photonics Journal, 2017, Vol. 9, # 1, pp. 1–13. 13. Gan, F., Grabosky, P. Improved Street Lighting and Crime Reduction, the Promise of Crime Prevention / 2nd ed., 2000, ISBN0 642 24172 4; ISSN1326–6004 Canberra, Australian Institute of Criminology. 14. Guler, O., Onaygil, S. The effect of luminance uniformity on visibility level in road lighting // Lighting Research & Technology, Sep. 2003, Vol. 35, # 3, pp. 199–215. 15. Hirakawa, S., Karasawa, Y., T. Funaki, T., et al. Evaluation Index of Visibility in Tunnel Lighting // Journal of Light & Visual Environment, 2014, Vol. 38. 16. Painter, K.A., D.P. Farrington, D.P. Evaluating Situational Crime Prevention a Young People’s Survey // The British Journal of Criminology, London, Spring 2001, V. 41, # 2, pp. 266–284. 17. Robbins, C.J., Fotios, S. Road lighting and distraction whilst driving: Establishing the significant types of distraction roads // Lighting Research & Technology, 2020, APR8. 2020. 18. Ekriasa, A., Eloholma, M., Halonen, L. et al. Road lighting and headlights: Luminance measurements and automobile lighting simulations // Building and Environment, Elsevier, 2008, Vol. 43, # 4, pp. 530–536. 19. Nikunen, H. Correspondence: A proposed new LED road lighting concept // Lighting Research & Technology, 2014, Vol. 46, # 2, pp. 238–239. 20. Wandachowicz, K., Przybyla, M. The Measurements of the Parameters of Road Lighting- Theory and Practice // IEEE, 2018, VII. Lighting Conference of the Visegrad Countries (Lumen V4) Proceeding, 2018, pp. 1–5. 21. TS CEN/TR13201–1: Road Lighting, Selection of Road Lighting Classes /Turkish Standards Institute, 2006. 22. TS EN13201–2: Road Lighting, Performance Characteristics / Turkish Standards Institute, 2006. 23. Gaston, K.J., Gaston, S., Bennie, J., et al. Benefits and costs of artificial nighttime lighting of the environment // Environmental Reviews, 2014. 24. TS EN13201–3: Road Lighting, Calculation of Performance / Turkish Standards Institute, 2006. 25. Sutandi, A.C., Pinem, R. D.A. The application of road lighting standard towards sustainable transportation in large cities in Indonesia // Procedia Engineering, 2017, Vol. 171, pp. 1463–1471. 26. CIE115–2010: Lighting of roads for motor and pedestrian traffic / CIE, Vienna, 2010. 27. Iacomussi, P., Rossi, G., Soardo, P. Energy Saving and Environmental Compatibility in Road Lighting // Light & Engineering, 2012, Vol. 20, # 4, pp. 55–63. 28. TS EN13201–4: Road Lighting, Lighting Performance Measurement Methods / Turkish Standards Institute, 2006. 29. Lighting with Artificial Booklet 1 / Fördergemeinschaft Gutes Licht, 2008. 30. Thomson, W.D. Eye problems and visual display terminals – the facts and the fallacies // Ophthalmic Physiol. Opt., 1998 Mar., Vol. 18, # 2, pp. 111–119. 31. Buchner, A., Mayr, S., Brandt, M. The advantage of positive text background polarity is due to high display luminance // Ergonomics, 2009, Vol. 52, # 7, pp. 882–886. 32. Pedersen, L.A., Einarsson, S.S., Rikheim, F.A. User interfaces in dark mode during daytime-Improved productivity or just cool-looking / In Universal Access in Human-Computer Interaction, 2020, pp. 178–187. 33. Erickson, A., Kim, K., Bruder, G., et al. Effects of dark mode graphics on visual acuity and fatigue with virtual reality head-mounted displays // IEEE Conf. Virtual Reality 3D User Interfaces (VR), Mar. 2020, Atlanta, CA, USA. 34. Rempel, A.G., Mautiuk, R. Display considerations for improved night vision performance // Proc. of 19th Colour Image Conf.: Color Sci. Eng. Syst., Technol., 2011, Appl. (CIC), Atlanta, CA, USA, pp. 191–194. 35. Shieh, K.K. Effects of reflection and polarity on LCD viewing distance // International Journal of Ind. Ergonomics., 2000, Elsevier, Vol. 25, # 3, pp. 275–282. 36. Strbac-Hadzibegovic, N., Kostic, M. Modifications to the CIE115–2010 procedure for selecting lighting classes for roads // Lighting Research & Technology, May 2016, Vol. 48, # 3, pp. 340–351. 37. Na, N., Suk, H.J. Adaptive luminance contrast for enhancing reading performance and visual comfort on smartphone displays // 2014, Optical Engineering, Vol. 53, # 11, Art.no. 113102. 38. Lin, C.C., Huang, K.C. Effects of color combination and ambient illumination on visual perception time with TFT-LCD // Perceptual Motor Skills, 2009, Vol. 109, # 2, pp. 607–625. 39. Uttley, J., Fotios, S., Cheal, C. Effect of illuminance and spectrum on peripheral obstacle detection by pedestrians // Lighting Research & Technology, 2017, Vol. 49, # 2, pp. 211–227. 40. Yang, B., Wei, M. Road lighting: A pilot study investigating improvement of visual performance using light sources with a larger gamut area // Lighting Research & Technology, Nov. 2020, Vol. 52, # 7, pp. 895–905. 41. Scums, D.V., Eroshenko, B.V. Lumınous Intensıty and Lumınous Flux Standard Lamps Based on Cob LEDs // 2022, Light & Engineering, Vol. 30, # 1, pp. 24–28. 42. Sonmezocak, T., Akar, O., Terzi, U.K. Hıgh Performance Adaptıve Actıve Harmonıc Fılter Desıgn For Non- Lınear Led Loads // Light & Engineering, 2022, Vol. 30, # 1, pp. 29–38. 43. Ozturk, S.N., Onat, M., Celik, H.H. 3d Night Illumination of Aphrodisias Open-Air Museum with LED Technology // 2022, Light & Engineering, Vol. 30, #. 1, pp. 101–112. 44. Wang, A.H., Chen, M.T. Effects of polarity and luminance contrast on visual performance and VDT display quality // Int. J. Ind. Ergonom., 2000, Vol. 25, # 4, pp. 415–421. 45. Benedetto, S., Carbone, A., Drai-Zerbib, V. et al. Effects of luminance and illuminance on visual fatigue and arousal during digital reading // Comput. Hum. Behav., Elsevier, 2014, Vol. 41, pp. 112–119. 46. Ou, L.C., Sun, P.L., Huang, H.P., et al. Visual comfort as a function of lightness difference between text and background: A cross-age study using an LCD and a tablet computer // Color Res. Appl., 2015, Vol. 40, # 2, pp. 125–134. 47. Gowrisankaran, S., Nahar, N.K., Hayes, J.R. et al. Asthenopia and blink rate under visual and cognitive loads // Optometry Vis. Sci., 2012, Vol. 89, # 1, pp. 97–104. 48. N.K. Nahar, N.K., S. Gowrisankaran, S., J.R. Hayes, J.R., et al. Interactions of visual and cognitive stress // Optometry-J. Amer. Optometric Assoc., 2011, Vol. 82, # 11, pp. 689–696. 49. S. Fotios, S., T. Goodman, T. Proposed UK guidance for lighting in residential roads // Lighting Research & Technology, 2012, Vol. 44, # 1, pp. 69–83. 50. CIE Publication CIE140–2000: Road lighting calculations / ISBN:3–901–906–03–7. 51. M. Eloholma, M., J. Ketomäki, J., L. Halonen, L. Road lighting – luminance and visibility measurements / HUT Lighting Laboratory Report 29, 2001, ISBN:951–22–5736-X. 52. S. Atis, S., N. Ekren, N. Development of an outdoor lighting control system using expert system // Energy&Buildings, 2016, Vol. 130, pp. 773–786. 53. European standard EN13201–3: Road lighting – Part 3: Calculation of performance / Publication 270–2003, Ref. No. EN13201–3:2003 E. 54. Bhattacharya, S., Chakraborty, S., Ray, S. An Approach to Comparative simulation of Road Lighting and Estimation of Associated Quality Parameters // Light&Engineering, 2021, Vol. 29, # 1, pp. 77–87. 55. Gyurov, V. Panchev, H. Experimental Research on Light and Energy Parameters of Intelligent Street and Road Lighting Systems // 11th Electrical Engineering Faculty Conference (BulEF),1–4 Sep. 2019, IEEE Explore Digital Library. 56. Markvica, K., Richter, G., Lenz, G. Impact of urban street lighting on road users’ perception of public space and mobility behavior / Elsevier, Building and Environment, 2019, Vol. 154, pp. 32–43. 57. Bozorg, S., Tetri, E., Kosonen, I., et al. The Effect of Dimmed Road Lighting and Car Headlights on Visibility in Varying Road Surface Conditions // Leukos, 2018, Vol. 14, # 4, pp. 259–273. 58. Chenani, S.B., Vaaja, M.T., Kurkela, M., et al. Target detection Distances under different road lighting intensities // Transport Research Review: An Access Journal, June 2017, Vol. 9, #2, pp. 1–10, Springer Nature Journals. 59. Yoomak, S., Jettanasen, C., Ngaopitakkul, A., et al. Comparative study of lighting quality and power quality for LED and HPS luminaires in a roadway lighting system // Elsevier, Energy and Buildings, 2018, Vol. 159, pp. 542–557. 60. Xu, B., Yang, S., Lai, G., et al. Towards Autonomous Driving Technology: A Method to Enhance Visibility in Fog Based on Low-Position Road Lighting // Proceedings of 2018 IEEE3rd Optoelectronics Global Conference (OGC), pp. 205–208, Sep 2018. 61. Ogando-Martínez, A., Troncoso- Pastoriza, F., Granada-Álvarez, E., et al. Ellipsoid-based approximation method for the estimation of the actual reduced luminance coefficients of road surfaces for accurate lighting simulations // Elsevier, Sustainable Cities and Society, 2020. 62. Bellia, L., Cesarano, A., Minichiello, F., Sibilio, S. Setting up CCD photometer for lighting research and design // Building and Environment, 2002, Vol. 37, pp. 1099–1106. 63. Fryer, J.G., Brown, D.C. Lens distortion for closerange photogrammetry // Photogramm, Eng. Remote Sens., 1986, Vol. 52, pp. 51–58. 64. A.G. Rempel, A.G., R. Mautiuk, R. Display considerations for improved night vision performance // Proc. 19th Color Image Conf.: Color Sci. Eng. Syst., Technol., Appl. (CIC), Atlanta, CA, USA, 2011, pp. 191–194. 65. Vaaja, M.T., Maksimainen, M., Kurkela, M. Approaches for Mapping Night-Tıme Road Environment Lighting Conditions // ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. V‑1–2020, 2020 XXIV ISPRS Congress. 66. L. Karasaka, A. A.D. Beg, “Modeling of Different Geometrical Features with Terrestrial Laser Scanning Method”, Konya Faculty of Engineering and Natural Sciences, Map Engineering, Journal of Gemmatik, 6(1),54–60, 2021. 67. Kushwaha, S.K., Dayal, K.R., Raghavendra, S., et al. 3D Digital Documentation of a Cultural Heritage Site Using Terrestrial Laser Scanner – A Case Study / Applications of Geomatics in Civil Engineering, 2020, pp. 49–58. 68. Perc, M.N., Topolsek, D. Using the scanners and drone for comparison of point cloud accuracy at traffic accident analysis / Accident Analysis & Prevention, 135, 10539, 2020. 69. Chow, J., Lichti, D., Teskey, W. Accuracy assessment of the Faro Focus 3D and Leica HDS6100 panoramic type terrestrial laser scanner through point-based and plane-based user self-calibration // Proceedings of the FIG Working Week: Knowing to Manage the Territory, 2012. 70. Zhou, H., Pirinccioglu, F., Hsu, P. A new roadway lighting measurement system // Transp. Res. Part C Emerg. Technol., 2009, Vol. 17, pp. 274–284. 71. T. Kanzok, T., L. Linsen, L., P. Rosenthal, P. Onthe-fly luminance correction for rendering of inconsistently lit point clouds // J. WSCG, 2012, Vol. 20, pp. 161–169. 72. Cengiz, C., Puolakka, M., Halonen, L., et al. Combined eye-tracking and luminance measurements while driving on a rural road: Towards determining mesopic adaptation luminance // Lighting Research & Technology. September 26, 2013. 73. Hiscocks, P.D., Eng, P. Measuring luminance with a digital camera // Syscomp. Electron Des. Ltd., 2011, 686, pp. 1–25. 74. Wolska, A., D. Sawicki, D. Practical application of HDRI for discomfort glare assessment at indoor workplaces / Measurement, Elsevier, p.151, 107179, 2020. 75. M. Kurkula, M., Maksimainen, M., A. Julin, A., et al. Utilizing a Terrestrial Laser Scanner for 3D Luminance Measurement of Indoor Environments // Journal of Imaging, 2021, Vol 7, # 85, p. 85. 76. Kulawiak, M., Kulawiak, M., Lubniewski, Z. Integration, Processing and Dissemination of LiDAR Data in a 3D Web-GIS // ISPRS International Journal of Geo-Information, 2019, Vol 8, # 3, p. 144. 77. J.P. Virtanen, J.P., S. Daniel, S., T. Turppa, T., et al. Interactive dense point clouds in a game engine // ISPRS J. Photogramm, Remote Sens., 2020, #163, pp. 375–389. 78. Toschi, I., Ramos, M.M., Nocerino, E., et al. Oblique photogrammetry supporting 3D urban reconstruction of complex scenarios // Remote Sensing and Spatial Information Sciences, Vol XLII‑1-W1, pp. 519–526, Copernicus Publications, 2017. 79. Alba, M.I., Barazzetti, L., Scaioni, M., Rosina, E., Previtali, M. Mapping infrared data on terrestrial laser scanning 3D models of buildings // Remote Sens. 2011, # 3, pp. 1847–1870. 80. El-Makgary, S., Virtanen, J.P., Hyyppa, H. A Simple Semantic-Based Data Storage Layout for Querying Point Clouds // ISPRS International Journal of Geo-Information, Vol. 9, # 2, p 72, MDPI AG, 2020. 81. Van Genechten, B. Theory and Practice on Terrestrial Laser Scanning / Training Material Based on Practical Applications, 2008. 82. Vosselman, G., Maas, H-G. Airborne and Terrestrial Laser Scanning / CRC, 2010. 83. Micheletti, N., Chandler, J.H., Lane, S. Investigating the geomorphological potential of freely available and accessible structure-from-motion photogrammetry using a smartphone // Earth Surf. Proc. Landform, 2015, Vol. 40, # 4, pp. 473–486. 84. Sutandi, A., Caroline, P., Rory, D.A. The Application of Road Lighting Standard towards Sustainable Transportation in Large Cities in Indonesia // Procedia Engineering, 2017. 85. Zhang, J., Zhu, C., Li, X., et al. Characterizing the three-stage rutting behavior of asphalt pavement with semi-rigid base by using UMAT in ABAQUS // Construction and Building Materials, 2017, Vol. 140, pp. 496–507. 86. Kadela, M. Model of multiple-layer pavement structure-subsoil system // Bulletin of the Polish Academy of Sciences Technical Sciences, 2016, Vol. 64, # 4. 87. Imaninasab, R., Bakhshi, B., Shirini, B. Rutting performance of rubberized porous asphalt using Finite Element Method (FEM) // Construction and Building Materials, 2016, Vol. 106, pp. 382–391. 88. Chun, S., Kim, K., Greene, J. Evaluation of interlayer bonding condition on structural response characteristics of asphalt pavement using finite element analysis and full-scale field tests // Construction and Building Materials, 2015, Vol. 96, pp. 307–318. 89. Mulungye, R.M., Owende, P.M.O., Mellon, K. Finite element modelling of flexible pavements on soft soil subgrades // Materials and Design, 2007, Vol. 28, pp. 739–756. 90. Acharya, R., Han, J., Brennan, J.J. et al. Structural response of a low-fill box culvert under static and traffic loading // Journal of Performance of on Structured Facilities, 2016, Vol. 30, #1, 04014184. 91. Shafabakhsh, G.A., Family, A., Abad, B.P.H. Numerical analysis of concrete block pavements and comparison of its settlement with asphalt concrete pavements using finite element method // Engineering Journal, 2014, Vol. 18, #4, pp. 39–51. 92. Kocabey, S., Ekren, N. A new approach for examination of performance of interior lighting systems // Energy and Buildings, May 2014, Vol. 74, pp. 1–7. 93. Mangkut, R.A. Validation of DIALux 4.12 and DIALux evo 4.1 against the Analytical Test Cases of CIE171–2006 // Leukos, Vol. 12, # 3, pp. 139–150. 94. Van Bommel, W. Road lighting fundamentals / Technology and application. Cham, Switzerland, Springer, 334 p. 95. Bektas, Y., Dursun, M., Dindar, T., et al. Comparison of Classical Method and Computer Aided Method in Road Lighting Installations // 2nd International Vocational Science Symposium., IVSS2018. 96. Rusu, A.V., Lucache, D.D., Livint, G. Study Case for Illuminance Calculation for Footpaths // 2019 Electromechanical and Energy Systems (SIELMEN), Proceeding of 2019 International Conference, pp. 1–5. 97. Jetter, L., Lanh-Thanh, L., Hien-Thanh, L., et al. Low-Glare Freeform-Surfaced Street Light Luminaire Optimization to Meet Enhanced Road Lighting Standards // International Journal of Optics, Vol 2020, 12p., Hindawi Limited, 2020. 98. Schielke, T., Leudesdorff, M. Impact of lighting design on brand image for fashion retail stores // Lighting Research & Technology, 24 October 2015, Vol. 47, # 6, pp. 672–692. 99. Yoomak, S., Ngaopitakkul, A. The Study of Lighting Quality of LED and HPS Luminaires Based on Various Road Surface Properties // E3S Web of Conferences, 2018, Vol. 72, p. 01005, EDP Sciences, 2018. 100. Sıkora, R., Markıewıcz, P., Rozga, P. Active power losses and energy efficiency analysis of HPS lamps losses lamps with electromagnetic control gear and electronic ballast under the sinusoidal and nonsinusoidal condition // Bulletin of the Polish Academy of Sciences: Technical Science, 2021, Vol. 69 Issue 3, pp. 1–22. 101. Rustemli, S., Demir, Y. Comparative Analysis of Lighting Installations Used in Road Illumination // Light & Engineering, 2021, Vol. 29, # 6, pp. 86–94. 102. Duman, A.C., Guler, O. Techno-economic analysis of off-grid photovoltaic LED road lighting systems: A case study for northern, central and southern regions of Turkey // Building and Environment, 2019, Vol. 156, pp. 89–98. 103. Ayaz, R., Kaymaz, A.O., Nakir, I., Phusal, P. et al. Lıfe Cycle Cost Analysıs on M1 and M2 Road Class Lumınaıres Installed in Turkey // Light & Engineering, 2019, Vol. 27, # 1, pp. 61–70. 104. Medsker, L.R. The future of artificial neural networks could be bright // Computers/Control Engineering, 1997, Vol. 10, pp. 28–29. 105. Kalogirou, S.A. Applications of Artificial Neural Networks in Energy Systems a Review // Energy Conversion and Management, 1999, Vol. 40, # 10, pp. 1073–1087. 106. Jin, L.V. Summary of Artificial Neuron Model Research // Industrial Electronics Society, 33rd Annual Conference of the IEEE, 2007, pp. 5–8. 107. Amnatsan, S., Kuribayashi, D., Jayawardena, A.W. Application of Artificial Neural Networks and Wavelet Analysis in Prediction of Water Level in Nan River of Thailand // Proceeding of Annual Conference, 2010, Journal of Light &Visual Environment, Vol. 23. 108. Kayakuş, M., Uncu, I. An artificial intelligencebased photometric measurement software development and a new road lighting application // Lighting Research & Technology, Vol. 51, # 6, 2019. 109. Kazanasmaz, T., Günaydın, M., Binol, S. Artificial neural networks to predict daylight illuminance in office buildings // Building and Environment, 2009, Vol. 44, # 8, pp. 1751–1757. 110. Tran, D., Tan, Y.K. Sensor less illumination control of a networked LED lighting system using feedforward neural network // IEEE transactions on industrial electronics, 2013, Vol. 61, # 4, pp. 2113–2121. 111. M. Şahin, M., Y. Oğuz, Y.F. Büyüktümtürk, F. ANN-based Estimation of Time-dependent Energy Loss in Lighting Systems // Energy and Buildings, 2016, Vol. 116, pp. 455–467. 112. Kayakus, M., Uncu, I.S., Sagdıc, S. Measuring the Glow of the Indoor Basketball Hall with the Developed Artificial Neural Networks Based Software // European Journal of Science and Technology, August 2020, Vol. 19, pp. 770–777.
More