Examination of the Impact of Intersection Geometries and Vehicle Volumes on CO2 Emissions

Muhammed Ali Çolak

Makale detayları

Examination of the Impact of Intersection Geometries and Vehicle Volumes on CO2 Emissions

Yazarlar:

Muhammed Ali Çolak

Yayıncı:

Igdir University

Ana Başlıklar:

Ulaşım ve Trafik | Ulaştırma Mühendisliği

Dergi:

Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.15 Issue 3, pp.986-999

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001356708

pISSN:

2536-4618

Anahtar kelimeler:

Özet:

 The increase in CO2 emissions from transportation is directly linked to population growth, technological advancements, the widespread adoption of personal vehicles, and the increasing number of motor vehicles, such as buses and trucks, used in public transportation and logistics sectors. Therefore, analyzing and improving urban traffic flow is crucial for reducing harmful emissions. In this study, the current situation of the traffic corridor, consisting of the seven busiest intersections in the center of Erzincan, was modeled using intersection counts and signalization data in the Aimsun environment. An analysis was conducted on 2303 alternative scenarios created by different combinations of geometric arrangements and vehicle volumes at the intersections. The CO2 emission values obtained from the analysis of a total of 2304 scenarios were modeled using Light Gradient Boosting Machine LightGBM, k-Nearest Neighbors k-NN, and Bayesian Ridge regression algorithms. The best CO2 emission prediction was achieved with the LightGBM. Feature importance analysis revealed that the current situation of Dörtyol Intersection had the most significant impact on CO2 emissions, while the reorganization of Terzibaba Intersection as an grade separated junction would help reduce CO2 emissions across the corridor.

 The increase in CO2 emissions from transportation is directly linked to population growth, technological advancements, the widespread adoption of personal vehicles, and the increasing number of motor vehicles, such as buses and trucks, used in public transportation and logistics sectors. Therefore, analyzing and improving urban traffic flow is crucial for reducing harmful emissions. In this study, the current situation of the traffic corridor, consisting of the seven busiest intersections in the center of Erzincan, was modeled using intersection counts and signalization data in the Aimsun environment. An analysis was conducted on 2303 alternative scenarios created by different combinations of geometric arrangements and vehicle volumes at the intersections. The CO2 emission values obtained from the analysis of a total of 2304 scenarios were modeled using Light Gradient Boosting Machine LightGBM, k-Nearest Neighbors k-NN, and Bayesian Ridge regression algorithms. The best CO2 emission prediction was achieved with the LightGBM. Feature importance analysis revealed that the current situation of Dörtyol Intersection had the most significant impact on CO2 emissions, while the reorganization of Terzibaba Intersection as an grade separated junction would help reduce CO2 emissions across the corridor.

 The increase in CO2 emissions from transportation is directly linked to population growth, technological advancements, the widespread adoption of personal vehicles, and the increasing number of motor vehicles, such as buses and trucks, used in public transportation and logistics sectors. Therefore, analyzing and improving urban traffic flow is crucial for reducing harmful emissions. In this study, the current situation of the traffic corridor, consisting of the seven busiest intersections in the center of Erzincan, was modeled using intersection counts and signalization data in the Aimsun environment. An analysis was conducted on 2303 alternative scenarios created by different combinations of geometric arrangements and vehicle volumes at the intersections. The CO2 emission values obtained from the analysis of a total of 2304 scenarios were modeled using Light Gradient Boosting Machine LightGBM, k-Nearest Neighbors k-NN, and Bayesian Ridge regression algorithms. The best CO2 emission prediction was achieved with the LightGBM. Feature importance analysis revealed that the current situation of Dörtyol Intersection had the most significant impact on CO2 emissions, while the reorganization of Terzibaba Intersection as an grade separated junction would help reduce CO2 emissions across the corridor.

 Ulaşımdan kaynaklanan CO₂ salınımındaki artış; nüfusun büyümesi, teknolojik gelişmeler, bireysel araç sahipliğinin yaygınlaşması ve toplu taşıma ile lojistik sektörlerinde kullanılan otobüs ve kamyon gibi motorlu taşıtların sayısının artmasıyla doğrudan ilişkilidir. Bu bağlamda, şehir içi trafik akışının analizi ve iyileştirilmesi, zararlı salınımların azaltılması için kritik bir öneme sahiptir. Bu çalışmada, Erzincan il merkezindeki en yoğun yedi kavşağın oluşturduğu trafik koridorunun mevcut durumu, kavşak sayımları ve sinyalizasyon verileri kullanılarak Aimsun ortamında modellenmiştir. Kavşaklardaki geometrik düzenlemeler ve araç hacimlerinin farklı kombinasyonlarıyla oluşturulan 2303 alternatif senaryo üzerinde analiz yapılmıştır. Toplam 2304 senaryonun analizinden elde edilen CO2 salınım değerleri, Hafif Gradyan Artırma Makinesi LightGBM, k-En Yakın Komşular kNN ve Bayesian Ridge regresyon algoritmaları kullanılarak modellenmiştir. En iyi CO2 salınım tahmini, LightGBM ile elde edilmiştir. Özellik önem analizi, Dörtyol Kavşağının mevcut durumunun CO2 salınımları üzerinde en büyük etkiye sahip olduğunu, Terzibaba Kavşağının farklı düzeyli kavşak olarak yeniden düzenlenmesinin ise koridor boyunca CO2 salınımların azaltmaya yardımcı olacağını ortaya koymuştur.

Makale detayları

Examination of the Impact of Intersection Geometries and Vehicle Volumes on CO2 Emissions

Yazarlar:

Muhammed Ali Çolak

Yayıncı:

Igdir University

Ana Başlıklar:

Ulaşım ve Trafik | Ulaştırma Mühendisliği

Dergi:

Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.15 Issue 3, pp.986-999

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001356708

pISSN:

2536-4618

Sustainable transportation

Urban transportation

Aimsun

Roundabout modeling

CO2 emissions

Regression algorithmsSürdürülebilir ulaşım

Kent içi ulaşım

Aimsun

Kavşak modelleme

CO2 emisyonu

Regresyon algortimaları

Sayı

Makale detayları

Yazarlar: Muhammed Ali Çolak

Yayıncı: Igdir University

Ana Başlıklar: Ulaşım ve Trafik | Ulaştırma Mühendisliği

Dergi: Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.15 Issue 3, pp.986-999

Belge Tipi: Makale

Yayın Tarihi: 1/2025

Belge Dili: Türkçe

Document ID (Org No.): 2001356708

pISSN: 2536-4618

Sayı

Yazarlar:

Muhammed Ali Çolak

Yayıncı:

Igdir University

Ana Başlıklar:

Ulaşım ve Trafik | Ulaştırma Mühendisliği

Dergi:

Iğdır Üniversitesi Fen Bilimleri Enstitüsü Dergisi Vol.15 Issue 3, pp.986-999

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001356708

pISSN:

2536-4618