Year 2020, Volume 8 , Issue 1, Pages 49 - 54 2020-06-30

Real time traffic signal timing approach based on artificial neural network

Ali Tahir KARAŞAHİN [1] , Abdullah Erdal TÜMER [2]


As the population increases, is more and more increasing the number of vehicles in cities. The increasing number of vehicle make traffic management complicated. Difficult traffic management leads to more fuel consumption, CO2 and other harmful emissions. Therefore, real-time optimization of traffic lights (signaling) used in traffic management can make traffic management more efficient. In this study, green light time is optimized by estimating the number of vehicles in an intersection with signal lights in Konya city center through artificial neural network. The results are evaluated with different performance criteria and it has been shown that the developed estimation model can be successfully used to optimize the green light durations.
Dynamic traffic control, artificial neural network, traffic signalization, optimization
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Primary Language en
Subjects Engineering
Journal Section Research Article
Authors

Orcid: 0000-0002-7440-1312
Author: Ali Tahir KARAŞAHİN (Primary Author)
Institution: Karabük Üniversitesi
Country: Turkey


Orcid: 0000-0001-7747-9441
Author: Abdullah Erdal TÜMER
Institution: NECMETTİN ERBAKAN ÜNİVERSİTESİ, MÜHENDİSLİK VE MİMARLIK FAKÜLTESİ
Country: Turkey


Dates

Publication Date : June 30, 2020

Bibtex @research article { mjen741569, journal = {MANAS Journal of Engineering}, issn = {1694-7398}, eissn = {1694-7398}, address = {}, publisher = {Kyrgyz-Turkish Manas University}, year = {2020}, volume = {8}, pages = {49 - 54}, doi = {}, title = {Real time traffic signal timing approach based on artificial neural network}, key = {cite}, author = {Karaşahi̇n, Ali Tahir and Tümer, Abdullah Erdal} }
APA Karaşahi̇n, A , Tümer, A . (2020). Real time traffic signal timing approach based on artificial neural network. MANAS Journal of Engineering , 8 (1) , 49-54 . Retrieved from https://dergipark.org.tr/en/pub/mjen/issue/55261/741569
MLA Karaşahi̇n, A , Tümer, A . "Real time traffic signal timing approach based on artificial neural network". MANAS Journal of Engineering 8 (2020 ): 49-54 <https://dergipark.org.tr/en/pub/mjen/issue/55261/741569>
Chicago Karaşahi̇n, A , Tümer, A . "Real time traffic signal timing approach based on artificial neural network". MANAS Journal of Engineering 8 (2020 ): 49-54
RIS TY - JOUR T1 - Real time traffic signal timing approach based on artificial neural network AU - Ali Tahir Karaşahi̇n , Abdullah Erdal Tümer Y1 - 2020 PY - 2020 N1 - DO - T2 - MANAS Journal of Engineering JF - Journal JO - JOR SP - 49 EP - 54 VL - 8 IS - 1 SN - 1694-7398-1694-7398 M3 - UR - Y2 - 2020 ER -
EndNote %0 MANAS Journal of Engineering Real time traffic signal timing approach based on artificial neural network %A Ali Tahir Karaşahi̇n , Abdullah Erdal Tümer %T Real time traffic signal timing approach based on artificial neural network %D 2020 %J MANAS Journal of Engineering %P 1694-7398-1694-7398 %V 8 %N 1 %R %U
ISNAD Karaşahi̇n, Ali Tahir , Tümer, Abdullah Erdal . "Real time traffic signal timing approach based on artificial neural network". MANAS Journal of Engineering 8 / 1 (June 2020): 49-54 .
AMA Karaşahi̇n A , Tümer A . Real time traffic signal timing approach based on artificial neural network. MJEN. 2020; 8(1): 49-54.
Vancouver Karaşahi̇n A , Tümer A . Real time traffic signal timing approach based on artificial neural network. MANAS Journal of Engineering. 2020; 8(1): 54-49.