Assessing the Operational Impacts of Road Intersection using PTV Vissim Microscopic Simulation

Assessing the Operational Impacts of Road Intersection using PTV Vissim Microscopic Simulation

Kudrat Kutlimuratov

Contact

Akmal Mukhitdinov

Contact

Tashkent State Transport University

Assessing the Operational Impacts of Road Intersection using PTV Vissim Microscopic Simulation

Article Fingerprint

ReserarchID

UBCRN

Assessing the Operational Impacts of Road Intersection using PTV Vissim Microscopic Simulation Banner

AI TAKEAWAY

Connecting with the Eternal Ground

Abstract

The purpose of this study is to analysis the signalized intersection performance based on traffic volume and redesigning type of intersection. The observed data were collected at signalized roundabout intersection in Tashkent, Uzbekistan for 12 hours duration on weekdays. Traffic volume were analyzed and estimated at peak hours and estimated by level of service (LOS). Traffic volumes were projected for next 5, 10 years. The results of intersection performance were LOS C based on delay values in 2020. The next five years projected volume will be exceeding than maximum capacity from existing condition data. The study was proposed to reduce the congestion level and delays using PTV vissim software. This study is expected to help traffic engineers, planners and policy makers understand the assessment of the signalized intersections under mixed traffic conditions.

References

29 Cites in Article

Reference Format

A Krasnov,Ya. Gorokhov (2013). THE MAIN DIRECTIONS OF DEVELOPMENT OF THE ENERGY SECTOR OF THE KYRGYZ REPUBLIC IN THE CONTEXT OF THE TRANSITION TO A “GREEN” ECONOMY.
Bahar Dadashova,Xiao Li,Shawn Turner,Pete Koeneman (2020). Multivariate time series analysis of traffic congestion measures in urban areas as they relate to socioeconomic indicators.
K Zhang,S Batterman,F Dion (2011). Vehicle emissions in congestion: Comparison of work zone, rush hour and free-flow conditions.
Wei Guan,Shuyan He,Jihui Ma (2012). Review on Traffic Flow Phenomena and Theory.
Carlos Daganzo,Nikolas Geroliminis (2008). An analytical approximation for the macroscopic fundamental diagram of urban traffic.
Sourabh Jain,Sukhvir Jain,Gaurav Jain (2017). Traffic Congestion Modelling Based on Origin and Destination.
A Palma,R Lindsey (2011). Traffic congestion pricing methodologies and technologies.
Matthew Barth,Kanok Boriboonsomsin (2008). Real-World Carbon Dioxide Impacts of Traffic Congestion.
Feifei He,Xuedong Yan,Yang Liu,Lu Ma (2016). A Traffic Congestion Assessment Method for Urban Road Networks Based on Speed Performance Index.
Afshin Abadi,Tooraj Rajabioun,Petros Ioannou (2015). Traffic Flow Prediction for Road Transportation Networks With Limited Traffic Data.
Xiaobao Yang,Ziyou Gao,Xiaomei Zhao,Bingfeng Si (2009). Road Capacity at Bus Stops with Mixed Traffic Flow in China.
Lai Zheng,Tarek Sayed,Fred Mannering (2021). Modeling traffic conflicts for use in road safety analysis: A review of analytic methods and future directions.
Ciro Caliendo,Maurizio Guida (2012). Microsimulation Approach for Predicting Crashes at Unsignalized Intersections Using Traffic Conflicts.
Saif Jabari (2016). Node modeling for congested urban road networks.
Taha Saleem,Bhagwant Persaud,Amer Shalaby,Alexander Ariza (2014). Can Microsimulation be used to Estimate Intersection Safety?.
Yang Wang,Yan-Yan Chen (2016). Modeling the effect of microscopic driving behaviors on Kerner’s time-delayed traffic breakdown at traffic signal using cellular automata.
Kudrat Kutlimuratov,Shaukat Khakimov,Akmal Mukhitdinov,Rustam Samatov (2021). Modelling traffic flow emissions at signalized intersection with PTV vissim.
K Hirschmann,M Zallinger,M Fellendorf,S Hausberger (2010). A new method to calculate emissions with simulated traffic conditions.
Matt Grote,Ian Williams,John Preston,Simon Kemp (2016). Including congestion effects in urban road traffic CO2 emissions modelling: Do Local Government Authorities have the right options?.
Silvio Nocera,Cayetano Ruiz-Alarcón-Quintero,Federico Cavallaro (2018). Assessing carbon emissions from road transport through traffic flow estimators.
K Kutlimuratov,A Mukhitdinov (2020). Impact of stops for bus delays on routes.
Krystian Birr,Kazimierz Jamroz,Wojciech Kustra (2014). Travel Time of Public Transport Vehicles Estimation.
A Osama,H Mahdy,K Kandil,M Elhabiby (2016). Monitoring the impact of unscheduled stops and unscheduled route deviations on bus service using automatic vehicle location system: A case study.
H Rakha,Y Ding (2003). Impact of stops on vehicle fuel consumption and emissions.
Ehsan Mazloumi,Graham Currie,Geoffrey Rose (2010). Using GPS Data to Gain Insight into Public Transport Travel Time Variability.
K Khudayberganovich,M,-E Science (2016). Estimation of efficiency of the road train used in mountain conditions.
Akmal Mukhitdinov,Kamoliddin Ziyaev,Janserik Omarov,Shokhsanam Ismoilova (2021). Methodology of constructing driving cycles by the synthesis.
Umidulla Abdurazzokov,Bakhramjan Sattivaldiev,Ravshan Khikmatov,Shakhnoza Ziyaeva (2021). Method for assessing the energy efficiency of a vehicle taking into account the load under operating conditions.
J,Barry Barker (2009). HCM2010.

Download References

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Kudrat Kutlimuratov. 2026. \u201cAssessing the Operational Impacts of Road Intersection using PTV Vissim Microscopic Simulation\u201d. Global Journal of Science Frontier Research - H: Environment & Environmental geology GJSFR-H Volume 22 (GJSFR Volume 22 Issue H1).

More Citation Formats

Select Citation Style:

Download Citation

GJSFR Volume 22 Issue H1

Explore Journals Explore Volume Read This Issue

Journal Specifications

Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

Keywords

Not Found

Classification

GJSFR-H Classification DDC Code: 363.125 LCC Code: HE5614

Submission ReceivedDecember 9, 2021
Peer Review Double Blind
Handling Editor
Accepted December 15, 2021
Published April 16, 2022

Version of record

v1.2

Issue date

April 16, 2022

Language

Experiance in AR

Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.

View in VR

Read in 3D

Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.

View in 3D

Article Matrices

Total Views: 1634

Total Downloads: 45

2026 Trends

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]