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Trafik olaylarının çevresel etkileri: İstanbul O2 (TEM) otoyolu örneği

Yıl 2024, , 658 - 671, 31.07.2024
https://doi.org/10.61112/jiens.1488788

Öz

Karayolu kapasitesindeki olağandışı azalmalar veya talepteki beklenmedik artışlar (örneğin, araç arızaları ve trafik kazaları) trafik olayı olarak tanımlanmaktadır. Trafikte yaşanan gecikmelerin yaklaşık %25’i bu tür olaylardan kaynaklanmaktadır. Bu olaylar, kapasiteyi doğrudan (örneğin, şeritlerin kısmen veya tamamen kapanması) ya da dolaylı olarak (sürücülerin kazayı izlemek amacıyla yavaşlaması) etkileyerek, gecikmelerin ve seyahat sürelerinin uzamasına, yakıt tüketiminin artmasına ve çevreye zararlı gaz emisyonlarının artmasına neden olmaktadır. Bu çalışmanın amacı, trafik olaylarının çevresel etkilerini incelemektir. Bu bağlamda, İstanbul O2 (TEM) Otoyolu üzerinde meydana gelen bir trafik kazasının çevresel etkileri (CO, NOx, VOC ve yakıt tüketimi) VISSIM mikro ölçekli trafik benzetim programı kullanılarak analiz edilmiştir. Beklenildiği gibi, trafikte meydana gelen olayların karayolu işletmesi performans ölçütleri üzerinde olumsuz etkileri tespit edilmiştir. Ayrıca, benzetim programı kullanılarak gerçekleştirilen bu analize dayanarak trafik olaylarının çevresel etkilerini azaltmak için çeşitli önerilerde de bulunulmuştur.

Kaynakça

  • Saracoglu A, Ozen H (2022) Estimation of Traffic Incident Duration: A Comparative Study of Decision Tree Models. Arab J Sci Eng 45:8099–8110. https://doi.org/10.1007/s13369-020-04615-2
  • Cambridge Systematics Inc. (2005) An Initial Assessment of Freight Bottlenecks on Highways. https://www.fhwa.dot.gov/policy/otps/bottlenecks/.
  • Dia H, Gondwe W (2008) Evaluation of Incident Impacts on Integrated Motorway And Arterial Networks Using Traffic Simulation, 31st Australasian Transport Research Forum (ATRF), 563-575.
  • Akiva M B, Cuneo D, Hasan M, Jha M, Yang Q (2003) Evaluation of Freeway Control Using a Microscopic Simulation Laboratory. Transportation Research Part C 11:29–50.
  • Dia H, Cottman N (2006) Evaluation of Arterial Incident Management Impacts Using Traffic Simulation. IEE Proceedings - Intelligent Transport Systems 153(3):242-252.
  • Barceló J, Ferrer J, Casas Pla J R, Montero L, Perarnau J (2002) Microscopic simulation with AIMSUN for the assessment of incident management strategies. In E-safety congress & exhibition= E-safety congrès & exposition: IT solutions for safety and security in intelligent transport: solutions en faveur de la sécurité et de la síreté dans les transports intelligents: 16-18 september Lyon, France/ERTICO, ITS France (pp. 1-10).
  • Fries R (2007) Evaluating The Impacts of Accelerated Incident Clearance Tools and Strategies by Harnessing The Power of Microscopic Traffic Simulation. A Dissertation Presented to the Graduate School of Clemson University.
  • Tasic I (2012) Using Microsimulation to Evaluate Traffic Incident Responses for Traffic Operations Center Decision Making, Master of Science, Department of Civil and Environmental Engineering, The University of Utah.
  • Zhoua H, Tian Z (2012) Modeling Analysis of Incident and Roadway Clearance Time. Procedia - Social and Behavioral Sciences 43:349 – 355.
  • Saka AA, Jeihani M, James PA (2008) Estimation of Traffic Recovery Time for Different Flow Regimes on Freeways Final Report 2008. Department of Transportation and Urban Infrastructure Studies School of Engineering Morgan State University Baltimore.
  • Pulugurtha SS, Nambisan SS, Dangeti M, Kaseko M (2002) Simulating and analyzing incidents using CORSIM and VISSIM traffic simulation software. In Applications of Advanced Technologies in Transportation 811-818. http://dx.doi.org/10.1061/40632(245)102
  • Chien SIJ, Goulias DG, Yahalom S, Chowdhury SM (2002) Simulation‐based estimates of delays at freeway work zones. Journal of Advanced Transportation 36(2):131-156.
  • Karioti E, Basbas S, Mintsis E, Mintsis G, Taxiltaris C (2017) Traffic and environmental impacts of traffic incidents on Thessaloniki’s inner ring road. Transportation research procedia 24:288-295.
  • Tenekeci G (2019) Computation and Assessment of Environmental Emissions Resulting from Traffic Operations at Roundabouts. European Journal of Science and Technology Special Issue, 130-145, https://doi.org/10.31590/ejosat.637594
  • Šarić A, Sulejmanović S, Albinović S, Pozder M, Ljevo Ž (2023) The Role of Intersection Geometry in Urban Air Pollution Management. Sustainability 15, 5234. https://doi.org/10.3390/su15065234
  • Mądziel M, Campisi T, Jaworski A, Kuszewski H, Woś P (2021) Assessing Vehicle Emissions from a Multi-Lane to Turbo Roundabout Conversion Using a Microsimulation Tool. Energies, 14, 4399. https://doi.org/10.3390/en14154399
  • Song G, Yu L, Zhang Y (2012) Applicability of traffic microsimulation models in vehicle emissions estimates: case study of VISSIM. Transportation Research Record: Journal of the Transportation Research Board 2270:132-141.
  • Stevanovic A, Stevanovic J, Zhang K, Batterman S (2009) Optimizing Traffic Control to Reduce Fuel Consumption and Vehicular Emissions: Integrated Approach with VISSIM, CMEM, and VISGAOST. Transportation Research Record 2128(1):105-113. https://doi.org/10.3141/2128-11
  • Wang Y, Lv C, Nie Q, Liu H (2024) Analyzing the Impact of Road Accidents on Carbon Dioxide Emissions in Freeway Traffic: A Simulation and Statistical Modeling Approach. Sustainability 16, 2168. https://doi.org/10.3390/su16052168
  • Wondimu F M (2019) Modeling of Traffic Accident and Safety Assessment Using Vissim and Ssam Case Study: Kolfe-Keranio Sub city. M.Sc. Thesis, Addis Ababa Science and Technology University, Department of Civil and Architectural Engineering, Addis Ababa, Ethiopia.
  • Shi JQ, Cheng L (2012) Simulation and Analysis of Highway Traffic Accident Based on VISSIM. In Applied Mechanics and Materials 253–255:1682–1685. https://doi.org/10.4028/www.scientific.net/AMM.253-255.1682
  • PTV VISSIM Multimodal Traffic Simulation Software, https://www.ptvgroup.com/en/products/ptv-vissim Erişim 3 Temmuz 2024
  • Gomes G, May A, Horowitz R (2004) Calibration of VISSIM for a Congested Freeway. California PATH Research Report, UCB-ITS-PRR-2004-4.
  • US Department of Transportation (1996) Innovations in Transportation and Air Quality: Twelve Exemplary Projects. USDOT Publication FHWA-PD-96-016.
  • Hadi M, Xiao Y, Wang T (2013) Use of the HCM Freeway Facility Analysis and Microscopic Simulation Models as Part of Real-Time Management Decision Support Systems. Procs of 92nd Transportation Research Board Annual Meeting, Washington DC, USA, 13-17 Jan. 113
  • Berdica K, Andjic Z, Nicholson AJ (2003) Simulating Road Traffic Interruptions: Does it Matter What Model we Use?”, M.G.H, Bell, Y. Lida (Eds.), The Network Reliability of Transport, Elsevier Science, Oxford, UK, ss.353-368.
  • Gale C, Spiers J (2001) Urban Traffic Management and Control Report 4 (Network monitoring, modelling and management): Project summary and evaluation. MVA Report UTMC-04, Dept for Transport, London, UK.
  • Daganzo CF (1993) The cell transmission model: a dynamic representation of highway traffic consistent with the hydrodynamic theory. Transportation Research B 28B(4):269–287.
  • Ozbay K, Xiao W, Jaiswal G, Bartin B, Kachroo P, Gursoy M B (2009) Evaluation of incident management strategies and technologies using an integrated traffic/incident management simulation. World Review of Intermodal Transportation Research 2, no. 2 (2009): 155-186. https://doi.org/10.1504/WRITR.2009.023305
  • Gursoy MB, Xiao W, Duan Z, Ozbay K (2006) Delay Estimation for Traffic Flow Interrupted by Incidents. 86th Annual Transportation Research Conference, Washington D.C., 2006.
  • U.S Department of Transportation Federal Highway Administration Traffic Incident Management (2024) https://ops.fhwa.dot.gov/tim/ Erişim 9 Şubat 2024
  • Chang HL, Chang TP (2013) Prediction of freeway incident duration based on classification tree analysis. Journal of the Eastern Asia Society for Transportation Studies 10:1964-1977. https://doi.org/10.11175/easts.10.1964
  • Ozen H, Saracoglu A (2019) Multi-Step Approach to Improving Accuracy of Incident Duration Estimation: Case Study of Istanbul. Tehnički vjesnik 26(6):1777-1783. https://doi.org/10.17559/TV-20170104093330
  • Can O (2005) Development of a Control Strategy for Urban Traffic Management System of Istanbul. Doktora Tezi, Marmara Üniversitesi Fen Bilimleri Enstitüsü.
  • Ergün G, Avrenli K A, Harman M M, Pehlivan E (2006) Arterial Signal Coordination and Optimization: Methodology and Applications Handbook, Report Prepared for ISBAK Inc., Boğaziçi University, Department of Civil Engineering, Istanbul
  • Koç H (2010) Eşdüzey Kavşaklardan Katlı Kavşaklara Geçiş Örnekler ve Uygunluklarının Değerlendirilmesi. Yüksek Lisans Tezi, YTÜ Fen Bilimleri Enstitüsü, İstanbul.
  • Data model: Algorithms for car following/lane change behavior, https://support.ptvgroup.com/en-us/knowledgebase/article/KA-05301 Erişim 20 Mart 2024
  • Or S (2024) Realistic Traffic Simulation: Driving Behavior is Key. https://blog.ptvgroup.com/en/modelling-and-simulation-technology/realistic-traffic-simulation-driving-behavior-is-key/ Erişim 13 Nisan 2024
  • Dia H, Cottman N (2004) Evaluation of Incident Management Benefits Using Traffic Simulation. Presented at Workshop on Traffic Simulation (Bridging Theory and Practice), Customs House, Brisbane, Queensland, 5-6 August, 2004.
  • Menneni S, Sun C, Vortisch P (2008) Microsimulation calibration using speed-flow relationships. Transportation Research Board, 2088:1–9.
  • Hafram SM, Valeryb S, Hasimb AH (2023) Calibrating and Validation Microscopic Traffic Simulation Models VISSIM for Enhanced Highway Capacity Planning. IJE TRANSACTIONS B: Applications 36(08):1509-1519.
  • Rompis SYR, Habtemichael FG (2019) Calibration of Traffic Incident Simulation Models Using Field Data. International Journal of Sustainable Transportation Technology 2:(1):19-26.

Environmental effects of traffic incidents: example of Istanbul O2 (TEM) highway

Yıl 2024, , 658 - 671, 31.07.2024
https://doi.org/10.61112/jiens.1488788

Öz

Unusual decreases in road capacity or unexpected increases in demand (for example, vehicle breakdowns and traffic accidents) are defined as traffic incidents. Approximately 25% of traffic delays are caused by such incidents. These incidents affect capacity directly (for example, partial or complete lane closure) or indirectly (drivers slowing down to observe the accident), causing delays and travel times to increase, fuel consumption to increase, and environmentally harmful gas emissions to rise. The purpose of this study is to examine the environmental effects of traffic incidents. In this regard, the environmental effects (CO, NOx, VOC and fuel consumption) of a traffic accident that occurred on the Istanbul O2 (TEM) Highway were analysed using VISSIM microsimulation program. As expected, traffic incidents were found to have negative effects on highway operation performance measures. In addition, based on this analysis performed using the simulation model, various suggestions have also been made to reduce the environmental impacts of traffic incidents.

Kaynakça

  • Saracoglu A, Ozen H (2022) Estimation of Traffic Incident Duration: A Comparative Study of Decision Tree Models. Arab J Sci Eng 45:8099–8110. https://doi.org/10.1007/s13369-020-04615-2
  • Cambridge Systematics Inc. (2005) An Initial Assessment of Freight Bottlenecks on Highways. https://www.fhwa.dot.gov/policy/otps/bottlenecks/.
  • Dia H, Gondwe W (2008) Evaluation of Incident Impacts on Integrated Motorway And Arterial Networks Using Traffic Simulation, 31st Australasian Transport Research Forum (ATRF), 563-575.
  • Akiva M B, Cuneo D, Hasan M, Jha M, Yang Q (2003) Evaluation of Freeway Control Using a Microscopic Simulation Laboratory. Transportation Research Part C 11:29–50.
  • Dia H, Cottman N (2006) Evaluation of Arterial Incident Management Impacts Using Traffic Simulation. IEE Proceedings - Intelligent Transport Systems 153(3):242-252.
  • Barceló J, Ferrer J, Casas Pla J R, Montero L, Perarnau J (2002) Microscopic simulation with AIMSUN for the assessment of incident management strategies. In E-safety congress & exhibition= E-safety congrès & exposition: IT solutions for safety and security in intelligent transport: solutions en faveur de la sécurité et de la síreté dans les transports intelligents: 16-18 september Lyon, France/ERTICO, ITS France (pp. 1-10).
  • Fries R (2007) Evaluating The Impacts of Accelerated Incident Clearance Tools and Strategies by Harnessing The Power of Microscopic Traffic Simulation. A Dissertation Presented to the Graduate School of Clemson University.
  • Tasic I (2012) Using Microsimulation to Evaluate Traffic Incident Responses for Traffic Operations Center Decision Making, Master of Science, Department of Civil and Environmental Engineering, The University of Utah.
  • Zhoua H, Tian Z (2012) Modeling Analysis of Incident and Roadway Clearance Time. Procedia - Social and Behavioral Sciences 43:349 – 355.
  • Saka AA, Jeihani M, James PA (2008) Estimation of Traffic Recovery Time for Different Flow Regimes on Freeways Final Report 2008. Department of Transportation and Urban Infrastructure Studies School of Engineering Morgan State University Baltimore.
  • Pulugurtha SS, Nambisan SS, Dangeti M, Kaseko M (2002) Simulating and analyzing incidents using CORSIM and VISSIM traffic simulation software. In Applications of Advanced Technologies in Transportation 811-818. http://dx.doi.org/10.1061/40632(245)102
  • Chien SIJ, Goulias DG, Yahalom S, Chowdhury SM (2002) Simulation‐based estimates of delays at freeway work zones. Journal of Advanced Transportation 36(2):131-156.
  • Karioti E, Basbas S, Mintsis E, Mintsis G, Taxiltaris C (2017) Traffic and environmental impacts of traffic incidents on Thessaloniki’s inner ring road. Transportation research procedia 24:288-295.
  • Tenekeci G (2019) Computation and Assessment of Environmental Emissions Resulting from Traffic Operations at Roundabouts. European Journal of Science and Technology Special Issue, 130-145, https://doi.org/10.31590/ejosat.637594
  • Šarić A, Sulejmanović S, Albinović S, Pozder M, Ljevo Ž (2023) The Role of Intersection Geometry in Urban Air Pollution Management. Sustainability 15, 5234. https://doi.org/10.3390/su15065234
  • Mądziel M, Campisi T, Jaworski A, Kuszewski H, Woś P (2021) Assessing Vehicle Emissions from a Multi-Lane to Turbo Roundabout Conversion Using a Microsimulation Tool. Energies, 14, 4399. https://doi.org/10.3390/en14154399
  • Song G, Yu L, Zhang Y (2012) Applicability of traffic microsimulation models in vehicle emissions estimates: case study of VISSIM. Transportation Research Record: Journal of the Transportation Research Board 2270:132-141.
  • Stevanovic A, Stevanovic J, Zhang K, Batterman S (2009) Optimizing Traffic Control to Reduce Fuel Consumption and Vehicular Emissions: Integrated Approach with VISSIM, CMEM, and VISGAOST. Transportation Research Record 2128(1):105-113. https://doi.org/10.3141/2128-11
  • Wang Y, Lv C, Nie Q, Liu H (2024) Analyzing the Impact of Road Accidents on Carbon Dioxide Emissions in Freeway Traffic: A Simulation and Statistical Modeling Approach. Sustainability 16, 2168. https://doi.org/10.3390/su16052168
  • Wondimu F M (2019) Modeling of Traffic Accident and Safety Assessment Using Vissim and Ssam Case Study: Kolfe-Keranio Sub city. M.Sc. Thesis, Addis Ababa Science and Technology University, Department of Civil and Architectural Engineering, Addis Ababa, Ethiopia.
  • Shi JQ, Cheng L (2012) Simulation and Analysis of Highway Traffic Accident Based on VISSIM. In Applied Mechanics and Materials 253–255:1682–1685. https://doi.org/10.4028/www.scientific.net/AMM.253-255.1682
  • PTV VISSIM Multimodal Traffic Simulation Software, https://www.ptvgroup.com/en/products/ptv-vissim Erişim 3 Temmuz 2024
  • Gomes G, May A, Horowitz R (2004) Calibration of VISSIM for a Congested Freeway. California PATH Research Report, UCB-ITS-PRR-2004-4.
  • US Department of Transportation (1996) Innovations in Transportation and Air Quality: Twelve Exemplary Projects. USDOT Publication FHWA-PD-96-016.
  • Hadi M, Xiao Y, Wang T (2013) Use of the HCM Freeway Facility Analysis and Microscopic Simulation Models as Part of Real-Time Management Decision Support Systems. Procs of 92nd Transportation Research Board Annual Meeting, Washington DC, USA, 13-17 Jan. 113
  • Berdica K, Andjic Z, Nicholson AJ (2003) Simulating Road Traffic Interruptions: Does it Matter What Model we Use?”, M.G.H, Bell, Y. Lida (Eds.), The Network Reliability of Transport, Elsevier Science, Oxford, UK, ss.353-368.
  • Gale C, Spiers J (2001) Urban Traffic Management and Control Report 4 (Network monitoring, modelling and management): Project summary and evaluation. MVA Report UTMC-04, Dept for Transport, London, UK.
  • Daganzo CF (1993) The cell transmission model: a dynamic representation of highway traffic consistent with the hydrodynamic theory. Transportation Research B 28B(4):269–287.
  • Ozbay K, Xiao W, Jaiswal G, Bartin B, Kachroo P, Gursoy M B (2009) Evaluation of incident management strategies and technologies using an integrated traffic/incident management simulation. World Review of Intermodal Transportation Research 2, no. 2 (2009): 155-186. https://doi.org/10.1504/WRITR.2009.023305
  • Gursoy MB, Xiao W, Duan Z, Ozbay K (2006) Delay Estimation for Traffic Flow Interrupted by Incidents. 86th Annual Transportation Research Conference, Washington D.C., 2006.
  • U.S Department of Transportation Federal Highway Administration Traffic Incident Management (2024) https://ops.fhwa.dot.gov/tim/ Erişim 9 Şubat 2024
  • Chang HL, Chang TP (2013) Prediction of freeway incident duration based on classification tree analysis. Journal of the Eastern Asia Society for Transportation Studies 10:1964-1977. https://doi.org/10.11175/easts.10.1964
  • Ozen H, Saracoglu A (2019) Multi-Step Approach to Improving Accuracy of Incident Duration Estimation: Case Study of Istanbul. Tehnički vjesnik 26(6):1777-1783. https://doi.org/10.17559/TV-20170104093330
  • Can O (2005) Development of a Control Strategy for Urban Traffic Management System of Istanbul. Doktora Tezi, Marmara Üniversitesi Fen Bilimleri Enstitüsü.
  • Ergün G, Avrenli K A, Harman M M, Pehlivan E (2006) Arterial Signal Coordination and Optimization: Methodology and Applications Handbook, Report Prepared for ISBAK Inc., Boğaziçi University, Department of Civil Engineering, Istanbul
  • Koç H (2010) Eşdüzey Kavşaklardan Katlı Kavşaklara Geçiş Örnekler ve Uygunluklarının Değerlendirilmesi. Yüksek Lisans Tezi, YTÜ Fen Bilimleri Enstitüsü, İstanbul.
  • Data model: Algorithms for car following/lane change behavior, https://support.ptvgroup.com/en-us/knowledgebase/article/KA-05301 Erişim 20 Mart 2024
  • Or S (2024) Realistic Traffic Simulation: Driving Behavior is Key. https://blog.ptvgroup.com/en/modelling-and-simulation-technology/realistic-traffic-simulation-driving-behavior-is-key/ Erişim 13 Nisan 2024
  • Dia H, Cottman N (2004) Evaluation of Incident Management Benefits Using Traffic Simulation. Presented at Workshop on Traffic Simulation (Bridging Theory and Practice), Customs House, Brisbane, Queensland, 5-6 August, 2004.
  • Menneni S, Sun C, Vortisch P (2008) Microsimulation calibration using speed-flow relationships. Transportation Research Board, 2088:1–9.
  • Hafram SM, Valeryb S, Hasimb AH (2023) Calibrating and Validation Microscopic Traffic Simulation Models VISSIM for Enhanced Highway Capacity Planning. IJE TRANSACTIONS B: Applications 36(08):1509-1519.
  • Rompis SYR, Habtemichael FG (2019) Calibration of Traffic Incident Simulation Models Using Field Data. International Journal of Sustainable Transportation Technology 2:(1):19-26.
Toplam 42 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ulaşım ve Trafik, Ulaştırma Mühendisliği
Bölüm Araştırma Makaleleri
Yazarlar

Fatih Kerem Boz 0009-0007-1953-7237

Halit Özen 0000-0003-4031-7283

Yayımlanma Tarihi 31 Temmuz 2024
Gönderilme Tarihi 23 Mayıs 2024
Kabul Tarihi 22 Temmuz 2024
Yayımlandığı Sayı Yıl 2024

Kaynak Göster

APA Boz, F. K., & Özen, H. (2024). Trafik olaylarının çevresel etkileri: İstanbul O2 (TEM) otoyolu örneği. Journal of Innovative Engineering and Natural Science, 4(2), 658-671. https://doi.org/10.61112/jiens.1488788


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Journal of Innovative Engineering and Natural Science by İdris Karagöz is licensed under CC BY 4.0