WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

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Author: search.filters.author.Tanyel, Serhan

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  • Article
    Citation - WoS: 15
    Citation - Scopus: 20
    Comparison of Intelligent Parking Guidance System and Conventional System With Regard To Capacity Utilisation
    (Elsevier, 2021) Doğaroğlu, Bora; Doğaroğlu, Bora; Çalışkanelli, S. Pelin; Tanyel, Serhan; 03.03. Department of Civil Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    The capacity utilisation of car parks is an important issue because of space deficiency for infrastructure improvement in city centres. Intelligent Parking Guidance Systems (IPGSs) provide a solution to such shortages by managing car park capacity. In this study, an IPGS model is proposed concerning the occupancy condition of three surface car parks, and the proposed model is compared with the conventional system (CS) where drivers tend to prefer the closest parking utility. A multi-agent-based simulation program investigates five scenarios and the results compared regarding the occupancy ratio, wasted Value of Time (VoT), and emission of harmful gases. The simulation results illustrate that the proposed IPGS model manages to equilibrate the capacity utilisation of car parks and the parking search period compared with the CS model. Analysis results show that emissions for CS of CO2, CO, HC, and NOx are 398.71, 19.90, 3.29, and 21.14 g/s/veh, respectively. This is attributed to the extra search period in the CS models. Besides, the cost of this extra searching period in CS is estimated in terms of the value of time for Turkey, Germany, U.K., and France as 0.49, 0.93, 1.42, and 1.42 euro/veh respectively. © 2021 Elsevier Ltd
  • Article
    Citation - WoS: 11
    Citation - Scopus: 12
    Passenger Flows Estimation of Light Rail Transit (lrt) System in Izmir, Turkey Using Multiple Regression and Ann Methods
    (Faculty of Transport and Traffic Sciences, University of Zagreb, 2012) Özuysal, Mustafa; Tayfur, Gökmen; Tayfur, Gökmen; Özuysal, Mustafa; 03.03. Department of Civil Engineering; 03.04. Department of Computer Engineering; 03. Faculty of Engineering; 01. Izmir Institute of Technology
    Passenger flow estimation of transit systems is essential for new decisions about additional facilities and feeder lines. For increasing the efficiency of an existing transit line, stations which are insufficient for trip production and attraction should be examined first. Such investigation supports decisions for feeder line projects which may seem necessary or futile according to the findings. In this study, passenger flow of a light rail transit (LRT) system in Izmir, Turkey is estimated by using multiple regression and feed-forward back-propagation type of artificial neural networks (ANN). The number of alighting passengers at each station is estimated as a function of boarding passengers from other stations. It is found that ANN approach produced significantly better estimations specifically for the low passenger attractive stations. In addition, ANN is found to be more capable for the determination of trip-attractive parts of LRT lines.