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OPTIMIZATION OF PLATE RECOGNITION SENSOR LOCATIONS: A CASE STUDY IN TURKEY

Yıl 2021, Cilt: 32 Sayı: 1, 147 - 163, 30.04.2021
https://doi.org/10.46465/endustrimuhendisligi.837181

Öz

With the advances in sensor and data transfer technologies, the usage areas of Automatic License Plate Recognition (ALPR) systems have been expanded in the public and private sectors. In public safety, ALPR systems are used to monitor and control traffic data at both individual and collective levels. To build an efficient sensor network, the locations of ALPR systems should be determined optimally. This study provides an approach to determine optimal locations of ALPR systems that maximize network coverage consisting of two measures: i) vehicle coverage and ii) road coverage. The former represents the daily average vehicle flow whereas the latter stands for the number of road-links covered. The relative importance of vehicle and road coverages are taken into consideration, and optimal solutions under various scenarios are presented. A close neighbor constraint is introduced to avoid inefficient distribution of ALPR systems on the network. A case study with numerical examples designed for two cities in Turkey is provided. The centralized and decentralized solutions are compared against the current state, and the results show that the network coverage increases substantially in the centralized case.

Kaynakça

  • Castillo, E., Menéndez, J. M. & Jiménez, P. (2008). Trip matrix and path flow reconstruction and estimation based on plate scanning and link observations. Transportation Research Part B: Methodological, 42(5), 455-481. Doi: https://doi.org/10.1016/j.trb.2007.09.004
  • Cerrone, C., Cerulli, R. & Gentili, M. (2015). Vehicle-id sensor location for route flow recognition: Models and algorithms. European Journal of Operational Research, 247(2), 618-629. Doi: https://doi.org/10.1016/j.ejor.2015.05.070
  • Coaffee, J. (2004). Rings of steel, rings of concrete and rings of confidence: designing out terrorism in central London pre and post September 11th. International Journal of Urban and Regional Research, 28(1), 201-211. Doi: https://doi.org/10.1111/j.0309-1317.2004.00511.x
  • Church, R. L. & Roberts, K. L. (1983). Generalized coverage models and public facility location. Papers of The Regional Science Association, 53(1), 117-135.
  • Church, R. & ReVelle, C. (1974). The maximal covering location problem. Papers of The Regional Science Association, 32(1), 101-118.
  • Current, J. R. & Schilling, D. A. (1990). Analysis of errors due to demand data aggregation in the set covering and maximal covering location problems. Geographical Analysis, 22(2), 116-126. Doi: https://doi.org/10.1111/j.1538-4632.1990.tb00199.x
  • Current, J. R., ReVelle, C. S. & Cohon, J. L. (1985). The maximum covering/shortest path problem: A multiobjective network design and routing formulation. European Journal of Operational Research, 21(2), 189-199. Doi: https://doi.org/10.1016/0377-2217(85)90030-X
  • Farahani, R. Z., Asgari, N., Heidari, N., Hosseininia, M. & Goh, M. (2012). Covering problems in facility location: A review. Computers & Industrial Engineering, 62(1), 368-407. Doi: https://doi.org/10.1016/j.cie.2011.08.020
  • Francis, R. L., McGinnis, L. F. & White, J. A. (1992). Facility layout and location: an analytical approach. Pearson College Division.
  • General Directorate of Highways. Traffic Volume Map (2016) http://www.kgm.gov.tr/SiteCollectionDocuments/KGMdocuments/Trafik/trafikhacimharitasi/2016HacimHaritalari/Hacim2016Devlet.pdf. Accessed 31 August 2018.
  • Gentili, M. & Mirchandani, P. (2011). Survey of models to locate sensors to estimate traffic flows. Transportation Research Record: Journal of the Transportation Research Board, (2243), 108-116. Doi: https://doi.org/10.3141/2243-13
  • Hakimi, S. L. (1964). Optimum locations of switching centers and the absolute centers and medians of a graph. Operations Research, 12(3), 450-459. Doi: https://doi.org/10.1287/opre.12.3.450
  • Murray, A. T. (2016). Maximal coverage location problem: impacts, significance, and evolution. International Regional Science Review, 39(1), 5-27. Doi: https://doi.org/10.1177/0160017615600222
  • Owen, S. H. & Daskin, M. S. (1998). Strategic facility location: A review. European Journal of Operational Research, 111(3), 423-447. Doi: https://doi.org/10.1016/S0377-2217(98)00186-6
  • Oztekin, A., Pajouh, F. M., Delen, D. & Swim, L. K. (2010). An RFID network design methodology for asset tracking in healthcare. Decision Support Systems, 49(1), 100-109. Doi: https://doi.org/10.1016/j.dss.2010.01.007
  • Sarıkaya, H. A., Aygüneş, H. & Kılıç, A. (2020). Determining the locations of the gendarmerie stations using the maximal covering method. Journal of Industrial Engineering, 31(1), 28-47.
  • Schilling, D. A., Jayaraman, V. & Barkhi, R. (1993). A review of covering problems in facility location. Location Science, 1, 25-55. Doi: https://doi.org/10.1016/j.cie.2011.08.020
  • Schilling, D. A., Revelle, C., Cohon, J. & Elzinga, D. J. (1980). Some models for fire protection locational decisions. European Journal of Operational Research, 5(1), 1-7. Doi: https://doi.org/10.1016/0377-2217(80)90067-3
  • Sousanis, J. (2011). World vehicle population tops 1 billion units. Wards Auto, 15. Retrieved from: https://www.wardsauto.com/news-analysis/world-vehicle-population-tops-1-billion-units.
  • United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. Law Enforcement Management and Administrative Statistics (LEMAS), 2007. ICPSR31161-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2011-07-07. https://doi.org/10.3886/ICPSR31161.v1
  • United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. Law Enforcement Management and Administrative Statistics (LEMAS), 2013. ICPSR36164-v2. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2015-09-22. https://doi.org/10.3886/ICPSR36164.v2
  • Voelcker, J. (2014). 1.2 Billion Vehicles On World’s Roads Now, 2 Billion By 2035: Report. Green Car Reports, July, 29. Retrieved from: https://www.greencarreports.com/news/1093560_1-2-billion-vehicles-on-worlds-roads-now-2-billion-by-2035-report
  • Yang, H. & Zhou, J. (1998). Optimal traffic counting locations for origin–destination matrix estimation. Transportation Research Part B: Methodological, 32(2), 109-126. Doi: https://doi.org/10.1016/S0191-2615(97)00016-7

OPTIMIZATION OF PLATE RECOGNITION SENSOR LOCATIONS: A CASE STUDY IN TURKEY

Yıl 2021, Cilt: 32 Sayı: 1, 147 - 163, 30.04.2021
https://doi.org/10.46465/endustrimuhendisligi.837181

Öz

With the advances in sensor and data transfer technologies, the usage areas of Automatic License Plate Recognition (ALPR) systems have been expanded in the public and private sectors. In public safety, ALPR systems are used to monitor and control traffic data at both individual and collective levels. To build an efficient sensor network, the locations of ALPR systems should be determined optimally. This study provides an approach to determine optimal locations of ALPR systems that maximize network coverage consisting of two measures: i) vehicle coverage and ii) road coverage. The former represents the daily average vehicle flow whereas the latter stands for the number of road-links covered. The relative importance of vehicle and road coverages are taken into consideration, and optimal solutions under various scenarios are presented. A close neighbor constraint is introduced to avoid inefficient distribution of ALPR systems on the network. A case study with numerical examples designed for two cities in Turkey is provided. The centralized and decentralized solutions are compared against the current state, and the results show that the network coverage increases substantially in the centralized case.

Kaynakça

  • Castillo, E., Menéndez, J. M. & Jiménez, P. (2008). Trip matrix and path flow reconstruction and estimation based on plate scanning and link observations. Transportation Research Part B: Methodological, 42(5), 455-481. Doi: https://doi.org/10.1016/j.trb.2007.09.004
  • Cerrone, C., Cerulli, R. & Gentili, M. (2015). Vehicle-id sensor location for route flow recognition: Models and algorithms. European Journal of Operational Research, 247(2), 618-629. Doi: https://doi.org/10.1016/j.ejor.2015.05.070
  • Coaffee, J. (2004). Rings of steel, rings of concrete and rings of confidence: designing out terrorism in central London pre and post September 11th. International Journal of Urban and Regional Research, 28(1), 201-211. Doi: https://doi.org/10.1111/j.0309-1317.2004.00511.x
  • Church, R. L. & Roberts, K. L. (1983). Generalized coverage models and public facility location. Papers of The Regional Science Association, 53(1), 117-135.
  • Church, R. & ReVelle, C. (1974). The maximal covering location problem. Papers of The Regional Science Association, 32(1), 101-118.
  • Current, J. R. & Schilling, D. A. (1990). Analysis of errors due to demand data aggregation in the set covering and maximal covering location problems. Geographical Analysis, 22(2), 116-126. Doi: https://doi.org/10.1111/j.1538-4632.1990.tb00199.x
  • Current, J. R., ReVelle, C. S. & Cohon, J. L. (1985). The maximum covering/shortest path problem: A multiobjective network design and routing formulation. European Journal of Operational Research, 21(2), 189-199. Doi: https://doi.org/10.1016/0377-2217(85)90030-X
  • Farahani, R. Z., Asgari, N., Heidari, N., Hosseininia, M. & Goh, M. (2012). Covering problems in facility location: A review. Computers & Industrial Engineering, 62(1), 368-407. Doi: https://doi.org/10.1016/j.cie.2011.08.020
  • Francis, R. L., McGinnis, L. F. & White, J. A. (1992). Facility layout and location: an analytical approach. Pearson College Division.
  • General Directorate of Highways. Traffic Volume Map (2016) http://www.kgm.gov.tr/SiteCollectionDocuments/KGMdocuments/Trafik/trafikhacimharitasi/2016HacimHaritalari/Hacim2016Devlet.pdf. Accessed 31 August 2018.
  • Gentili, M. & Mirchandani, P. (2011). Survey of models to locate sensors to estimate traffic flows. Transportation Research Record: Journal of the Transportation Research Board, (2243), 108-116. Doi: https://doi.org/10.3141/2243-13
  • Hakimi, S. L. (1964). Optimum locations of switching centers and the absolute centers and medians of a graph. Operations Research, 12(3), 450-459. Doi: https://doi.org/10.1287/opre.12.3.450
  • Murray, A. T. (2016). Maximal coverage location problem: impacts, significance, and evolution. International Regional Science Review, 39(1), 5-27. Doi: https://doi.org/10.1177/0160017615600222
  • Owen, S. H. & Daskin, M. S. (1998). Strategic facility location: A review. European Journal of Operational Research, 111(3), 423-447. Doi: https://doi.org/10.1016/S0377-2217(98)00186-6
  • Oztekin, A., Pajouh, F. M., Delen, D. & Swim, L. K. (2010). An RFID network design methodology for asset tracking in healthcare. Decision Support Systems, 49(1), 100-109. Doi: https://doi.org/10.1016/j.dss.2010.01.007
  • Sarıkaya, H. A., Aygüneş, H. & Kılıç, A. (2020). Determining the locations of the gendarmerie stations using the maximal covering method. Journal of Industrial Engineering, 31(1), 28-47.
  • Schilling, D. A., Jayaraman, V. & Barkhi, R. (1993). A review of covering problems in facility location. Location Science, 1, 25-55. Doi: https://doi.org/10.1016/j.cie.2011.08.020
  • Schilling, D. A., Revelle, C., Cohon, J. & Elzinga, D. J. (1980). Some models for fire protection locational decisions. European Journal of Operational Research, 5(1), 1-7. Doi: https://doi.org/10.1016/0377-2217(80)90067-3
  • Sousanis, J. (2011). World vehicle population tops 1 billion units. Wards Auto, 15. Retrieved from: https://www.wardsauto.com/news-analysis/world-vehicle-population-tops-1-billion-units.
  • United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. Law Enforcement Management and Administrative Statistics (LEMAS), 2007. ICPSR31161-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2011-07-07. https://doi.org/10.3886/ICPSR31161.v1
  • United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. Law Enforcement Management and Administrative Statistics (LEMAS), 2013. ICPSR36164-v2. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2015-09-22. https://doi.org/10.3886/ICPSR36164.v2
  • Voelcker, J. (2014). 1.2 Billion Vehicles On World’s Roads Now, 2 Billion By 2035: Report. Green Car Reports, July, 29. Retrieved from: https://www.greencarreports.com/news/1093560_1-2-billion-vehicles-on-worlds-roads-now-2-billion-by-2035-report
  • Yang, H. & Zhou, J. (1998). Optimal traffic counting locations for origin–destination matrix estimation. Transportation Research Part B: Methodological, 32(2), 109-126. Doi: https://doi.org/10.1016/S0191-2615(97)00016-7
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Endüstri Mühendisliği
Bölüm Araştırma Makaleleri
Yazarlar

Buğra Gör Bu kişi benim 0000-0002-4545-1150

Gülşah Karakaya 0000-0001-9061-103X

Yayımlanma Tarihi 30 Nisan 2021
Kabul Tarihi 21 Mart 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 32 Sayı: 1

Kaynak Göster

APA Gör, B., & Karakaya, G. (2021). OPTIMIZATION OF PLATE RECOGNITION SENSOR LOCATIONS: A CASE STUDY IN TURKEY. Endüstri Mühendisliği, 32(1), 147-163. https://doi.org/10.46465/endustrimuhendisligi.837181

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