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Karayolu trafik kazalarına yeni bir yaklaşım: Kaza analiz kesimleri modeli

Year 2017, Volume: 23 Issue: 6, 707 - 717, 15.12.2017

Abstract

Bu çalışmada kaza analizleri konusunda yapılan
araştırmaların geniş bir literatür taraması yapılarak kaza analiz kesimleri
adında yeni bir yaklaşım modeli geliştirilmiştir. Bu yaklaşımda, kaza analizi
yapılacak olan yolun geometrik ve trafik özellikleri dikkate alınarak yol
kesimi homojen özellikte kaza analiz kesimlerine bölünmüştür. Çalışma
bölgesinde meydana gelen trafik kazalarına etki eden faktörler ve bu
faktörlerin sebep olduğu kaza şiddetleri belirlenmiştir. Her bir analiz
kesimine ait geçmiş trafik kazaları belirli bir zaman periyodu için incelenmiş,
kaza şiddetlerine ve kazaya etki eden faktörlere ağırlık değerleri verilmiştir.
Gerçekleştirilen analizlerle her bir kaza analiz kesimi, kaza açısından önem
derecesine göre sıralanmıştır. Sonuç olarak, geliştirilen model verileri teorik
olarak üretilen kuramsal bir yol kesiminde test edilmiş, diğer kaza analiz
modelleriyle karşılaştırılmış ve güvenilir sonuçlar elde edilmiştir.

References

  • World Health Organization. “Global Plan for the Decade of Action for Road Safety 2011-2020”. Geneva, Switzerland, 2010.
  • Al-Haji G. Traffic Safety in Developing Countries- New Approaches in Technology Transfer by Using Distance Education Technique, MSc Thesis, Linköping University, Linköping, Sweden, 2001.
  • Smeed RJ. “Some statistics aspects of road safety research”. Journal of the Royal Statistical Society, Series A, (General), 112(1), 1-34, 1949.
  • Adams J. “Smeed’s Law: Some further thoughts”. Journal of Traffic Engineering and Control, 10(7), 70-73, 1987.
  • Oppe S. “Macroscopic models for traffic and traffic safety”. Accident Analysis and Prevention, 21(3), 225-232, 1989.
  • Koornstra MJ. “The evolution of road safety and mobility”. IATSS (International Association of Traffic and Safety Sciences) Research, 16(2), 129-148, 1992.
  • Navin F, Bergan A, Qi JA. “Fundamental Relationship for Roadway Safety: A Model for Global Comparisons”. Transportation Research Board, Transportation Research Record, Washington DC, USA, 1441, 1994.
  • Cheng W, Washington SP. “Experimental evaluation of hotspot identification methods”. Accident Analysis and Prevention, 37(5), 870-881, 2005.
  • Boroujerdian M, Saffarzadeh M, Abolhasannejad V. “Developing a model for prioritising high crash road segments”. Proceedings of the Institution of Civil Engineers-Transport, 163(1), 19-28, 2010.
  • Carey J. “Arizona Local Government Safety Project Analysis Model (Final Report 504)”. Phoenix, Arizona, USA, 2001.
  • Qin X, Ivan JN, Ravishanker N. “Selecting Exposure Measures in Crash Rate Prediction for Two-Lane Highway Segments”. Accident Analysis and Preventation, 36(2), 183-191, 2003.
  • Pulugurtha SS, Krishnakumar VK, Nambisan SS. “New Methods to Identify and Rank High Pedestrian Crash Zones: Anillustration”. Accident Analysis and Prevention, 39(4), 800-811, 2007.
  • Hallmark SL, Basavaraju R, Pawlovich M. “Evaluation of the IOWA DOT’s Safety Improvement Candidate List Process”. Iowa State University, Department of Transportation, Ames IA, USA, 2002.
  • McGuigan DRD. “Non-Junction accident rates and their use in “black-spot identification”. Traffic Engineering Control, 23(2), 60-65, 1982. United States Federal Highway Administration. “Highway Safety Improvement Program (HSIP) Manual. US. Department of Transportation”. Washington DC, USA, 1981.
  • Ma J, Kockelman K. “Crash frequency and severity modeling using clustered data from washington state”. Proceedings of the IEEE ITSC, IEEE Intelligent Transportation Systems Conference, Toronto, Canada, 17-20 September 2006.
  • Monsere CM, Bosa PG, Bertini RL. “Combining climate, crash, and highway data for improved ranking of speed and winter-weather related crash locations in oregon”. Journal of Transportation Engineering, 134(7), 287-296, 2008.
  • Stokes RW, Mutabazi MI. “Rate-Quality control method of identifying hazardous road locations”. Transportation Research Record, 1542, 44-48, 1996.
  • Sayed TAA. Highway Safety Expert System: A New Approach to Safety Programs. PhD Thesis, University of British Columbia, Vancouver, Canada, 1995.
  • Elvik R. “The predictive validity of empirical bayes estimates of road safety”. Accident Analysis and Prevention, 40(6), 1964-1969, 2008.
  • Hauer E. “On the estimation of the expected number of accidents”. Accident Analysis and Prevention, 18(1), 1-12, 1986.
  • Bureau of Transport Economics. “Evaluation of the Black Spot”. Australian Government Publishing Service, Canberra, Australia, 1995.
  • Hauer E, Harwood DW, Council FM, Griffith MS. “Estimating safety by the empirical Bayes method: A tutorial”. Transportation Research Record, Transportation Research Board, National Research Council, Washington, DC, USA, 1784, 2002.
  • Hilge JL, Witkowski JM. “Bayesian identification of hazardous locations”. Transportation Research Record, Transporation Research Board, National Research Council, Washington, DC, USA, 1185, 1988.
  • Murat YŞ, Şekerler A. “Trafik kaza verilerinin kümelenme analizi yöntemi ile modellenmesi”. İMO Teknik Dergi, 20(3), 4759-4777, 2009.
  • Karaşahin M, Terzi S. “Coğrafi bilgi sistemleri ile Isparta-Antalya-Burdur karayolunun kara nokta analizi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 9(3), 305-311, 2003.
  • Saplıoğlu M, Karaşahin M. “Coğrafi bilgi sistemi yardimi ile isparta ili kentiçi trafik kaza analizi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 12(3), 321-332, 2006.
  • Eminağa ZA. An Approach to Investigate Relationship Between Speed and Safety on Urban Arterials. MSc Thesis, Midle East Technical University, Ankara, Turkey, 2008.
  • Ünal SZ. An Optimizing Approach for Highway Safety Improvement Programs. MSc Thesis, Middle East Technical University, Ankara, Turkey, 2004.
  • Ozan C, Başkan Ö, Haldenbilen S, Derici E. “Trafik kazalarinin tehlike indeksi metodu ile analizi: denizli örneği”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 16(3), 325-333, 2010.
  • Atalay A, Tortum A, Gökdağ M. “Türkiye’de 1977-2006 yılları arasında meydana gelen aylık trafik kazalarının zamansal analizi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 18(3), 221-229, 2012.
  • Atalay A, Tortum A, Çodur YM. “Faktör analizi kullanilarak trafik kazalarinin modellenmesi”. Uluslararası Trafik ve Ulaşım Güvenliği Dergisi, 1(1), 35-54, 2014.
  • Çodur MY, Tortum A, Çodur M. “Genelleştirilmiş lineer regresyon ile erzurum kuzey çevre yolu kaza tahmin modeli”. Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 3(1), 79-84, 2013.
  • Çodur MY, Tortum A. “An artificial neural network model for highway accident prediction: A case study of Erzurum”. Turkey Promet-Traffic & Transportation, 27(3), 217-225, 2015.
  • Akgüngör AP, Doğan E. “Farklı yöntemler kullanılarak geliştirilen trafik kaza tahmin modelleri ve analizi”. International Journal Engineering Research & Development, 2(1), 16-21, 2010.
  • Akgüngör AP, Doğan E. “Smeed ve andreassen kaza modellerinin türkiye uygulaması: Farklı senaryo analizleri”. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 23(4), 821-827, 2008. Andreassen DC. “Linking deaths with vehicles and population”. Traffic Engineering & Control, 26(11), 547-549, 1985.
  • Irgat O, Guler H, Aslan A. "Traffic safety analysis using macroscopic modeling techniques a case study for Sakarya region". International Science and Technology Conference, Rome, Italy, 25-27 June 2013.
  • Sjolinder K. Kara Nokta El Kitabı. Karayolları Genel Müdürlüğü, Ankara, Türkiye, 2001.

A new approach for road traffic accidents: Crash analysis segments model

Year 2017, Volume: 23 Issue: 6, 707 - 717, 15.12.2017

Abstract

In
this study a comprehensive literature review was done on road traffic accident
studies and a new approach named crash analysis segments was developed. In this
approach, the case area was divided into homogenous analyses segments by
considering geometrical and traffic properties of the road segment. The traffic
accidents and the accidents factors with their crash severities were defined.
The weighted ratios were assigned to the crash factors and to the crash
severities after historical traffic accident records were gathered during a
defined period for each analysis segments. Each crash analyses segments were
ranked by considering their prioritisation after some analyses. Consequently,
the developed model was tested for a hypothetical road segment with a data set
generated theoretically and compared with the other crash analysis models and
reliable results were found.

References

  • World Health Organization. “Global Plan for the Decade of Action for Road Safety 2011-2020”. Geneva, Switzerland, 2010.
  • Al-Haji G. Traffic Safety in Developing Countries- New Approaches in Technology Transfer by Using Distance Education Technique, MSc Thesis, Linköping University, Linköping, Sweden, 2001.
  • Smeed RJ. “Some statistics aspects of road safety research”. Journal of the Royal Statistical Society, Series A, (General), 112(1), 1-34, 1949.
  • Adams J. “Smeed’s Law: Some further thoughts”. Journal of Traffic Engineering and Control, 10(7), 70-73, 1987.
  • Oppe S. “Macroscopic models for traffic and traffic safety”. Accident Analysis and Prevention, 21(3), 225-232, 1989.
  • Koornstra MJ. “The evolution of road safety and mobility”. IATSS (International Association of Traffic and Safety Sciences) Research, 16(2), 129-148, 1992.
  • Navin F, Bergan A, Qi JA. “Fundamental Relationship for Roadway Safety: A Model for Global Comparisons”. Transportation Research Board, Transportation Research Record, Washington DC, USA, 1441, 1994.
  • Cheng W, Washington SP. “Experimental evaluation of hotspot identification methods”. Accident Analysis and Prevention, 37(5), 870-881, 2005.
  • Boroujerdian M, Saffarzadeh M, Abolhasannejad V. “Developing a model for prioritising high crash road segments”. Proceedings of the Institution of Civil Engineers-Transport, 163(1), 19-28, 2010.
  • Carey J. “Arizona Local Government Safety Project Analysis Model (Final Report 504)”. Phoenix, Arizona, USA, 2001.
  • Qin X, Ivan JN, Ravishanker N. “Selecting Exposure Measures in Crash Rate Prediction for Two-Lane Highway Segments”. Accident Analysis and Preventation, 36(2), 183-191, 2003.
  • Pulugurtha SS, Krishnakumar VK, Nambisan SS. “New Methods to Identify and Rank High Pedestrian Crash Zones: Anillustration”. Accident Analysis and Prevention, 39(4), 800-811, 2007.
  • Hallmark SL, Basavaraju R, Pawlovich M. “Evaluation of the IOWA DOT’s Safety Improvement Candidate List Process”. Iowa State University, Department of Transportation, Ames IA, USA, 2002.
  • McGuigan DRD. “Non-Junction accident rates and their use in “black-spot identification”. Traffic Engineering Control, 23(2), 60-65, 1982. United States Federal Highway Administration. “Highway Safety Improvement Program (HSIP) Manual. US. Department of Transportation”. Washington DC, USA, 1981.
  • Ma J, Kockelman K. “Crash frequency and severity modeling using clustered data from washington state”. Proceedings of the IEEE ITSC, IEEE Intelligent Transportation Systems Conference, Toronto, Canada, 17-20 September 2006.
  • Monsere CM, Bosa PG, Bertini RL. “Combining climate, crash, and highway data for improved ranking of speed and winter-weather related crash locations in oregon”. Journal of Transportation Engineering, 134(7), 287-296, 2008.
  • Stokes RW, Mutabazi MI. “Rate-Quality control method of identifying hazardous road locations”. Transportation Research Record, 1542, 44-48, 1996.
  • Sayed TAA. Highway Safety Expert System: A New Approach to Safety Programs. PhD Thesis, University of British Columbia, Vancouver, Canada, 1995.
  • Elvik R. “The predictive validity of empirical bayes estimates of road safety”. Accident Analysis and Prevention, 40(6), 1964-1969, 2008.
  • Hauer E. “On the estimation of the expected number of accidents”. Accident Analysis and Prevention, 18(1), 1-12, 1986.
  • Bureau of Transport Economics. “Evaluation of the Black Spot”. Australian Government Publishing Service, Canberra, Australia, 1995.
  • Hauer E, Harwood DW, Council FM, Griffith MS. “Estimating safety by the empirical Bayes method: A tutorial”. Transportation Research Record, Transportation Research Board, National Research Council, Washington, DC, USA, 1784, 2002.
  • Hilge JL, Witkowski JM. “Bayesian identification of hazardous locations”. Transportation Research Record, Transporation Research Board, National Research Council, Washington, DC, USA, 1185, 1988.
  • Murat YŞ, Şekerler A. “Trafik kaza verilerinin kümelenme analizi yöntemi ile modellenmesi”. İMO Teknik Dergi, 20(3), 4759-4777, 2009.
  • Karaşahin M, Terzi S. “Coğrafi bilgi sistemleri ile Isparta-Antalya-Burdur karayolunun kara nokta analizi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 9(3), 305-311, 2003.
  • Saplıoğlu M, Karaşahin M. “Coğrafi bilgi sistemi yardimi ile isparta ili kentiçi trafik kaza analizi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 12(3), 321-332, 2006.
  • Eminağa ZA. An Approach to Investigate Relationship Between Speed and Safety on Urban Arterials. MSc Thesis, Midle East Technical University, Ankara, Turkey, 2008.
  • Ünal SZ. An Optimizing Approach for Highway Safety Improvement Programs. MSc Thesis, Middle East Technical University, Ankara, Turkey, 2004.
  • Ozan C, Başkan Ö, Haldenbilen S, Derici E. “Trafik kazalarinin tehlike indeksi metodu ile analizi: denizli örneği”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 16(3), 325-333, 2010.
  • Atalay A, Tortum A, Gökdağ M. “Türkiye’de 1977-2006 yılları arasında meydana gelen aylık trafik kazalarının zamansal analizi”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 18(3), 221-229, 2012.
  • Atalay A, Tortum A, Çodur YM. “Faktör analizi kullanilarak trafik kazalarinin modellenmesi”. Uluslararası Trafik ve Ulaşım Güvenliği Dergisi, 1(1), 35-54, 2014.
  • Çodur MY, Tortum A, Çodur M. “Genelleştirilmiş lineer regresyon ile erzurum kuzey çevre yolu kaza tahmin modeli”. Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 3(1), 79-84, 2013.
  • Çodur MY, Tortum A. “An artificial neural network model for highway accident prediction: A case study of Erzurum”. Turkey Promet-Traffic & Transportation, 27(3), 217-225, 2015.
  • Akgüngör AP, Doğan E. “Farklı yöntemler kullanılarak geliştirilen trafik kaza tahmin modelleri ve analizi”. International Journal Engineering Research & Development, 2(1), 16-21, 2010.
  • Akgüngör AP, Doğan E. “Smeed ve andreassen kaza modellerinin türkiye uygulaması: Farklı senaryo analizleri”. Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, 23(4), 821-827, 2008. Andreassen DC. “Linking deaths with vehicles and population”. Traffic Engineering & Control, 26(11), 547-549, 1985.
  • Irgat O, Guler H, Aslan A. "Traffic safety analysis using macroscopic modeling techniques a case study for Sakarya region". International Science and Technology Conference, Rome, Italy, 25-27 June 2013.
  • Sjolinder K. Kara Nokta El Kitabı. Karayolları Genel Müdürlüğü, Ankara, Türkiye, 2001.
There are 37 citations in total.

Details

Subjects Engineering
Journal Section Research Article
Authors

Hakan Güler 0000-0002-3528-7502

Publication Date December 15, 2017
Published in Issue Year 2017 Volume: 23 Issue: 6

Cite

APA Güler, H. (2017). Karayolu trafik kazalarına yeni bir yaklaşım: Kaza analiz kesimleri modeli. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 23(6), 707-717.
AMA Güler H. Karayolu trafik kazalarına yeni bir yaklaşım: Kaza analiz kesimleri modeli. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. December 2017;23(6):707-717.
Chicago Güler, Hakan. “Karayolu Trafik kazalarına Yeni Bir yaklaşım: Kaza Analiz Kesimleri Modeli”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 23, no. 6 (December 2017): 707-17.
EndNote Güler H (December 1, 2017) Karayolu trafik kazalarına yeni bir yaklaşım: Kaza analiz kesimleri modeli. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 23 6 707–717.
IEEE H. Güler, “Karayolu trafik kazalarına yeni bir yaklaşım: Kaza analiz kesimleri modeli”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 23, no. 6, pp. 707–717, 2017.
ISNAD Güler, Hakan. “Karayolu Trafik kazalarına Yeni Bir yaklaşım: Kaza Analiz Kesimleri Modeli”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 23/6 (December 2017), 707-717.
JAMA Güler H. Karayolu trafik kazalarına yeni bir yaklaşım: Kaza analiz kesimleri modeli. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2017;23:707–717.
MLA Güler, Hakan. “Karayolu Trafik kazalarına Yeni Bir yaklaşım: Kaza Analiz Kesimleri Modeli”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 23, no. 6, 2017, pp. 707-1.
Vancouver Güler H. Karayolu trafik kazalarına yeni bir yaklaşım: Kaza analiz kesimleri modeli. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2017;23(6):707-1.





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