Hüseyin Murat Çelik

Bio: Hüseyin Murat Çelik is an academic researcher from Istanbul Technical University. The author has contributed to research in topics: Brownian motion & Traffic flow. The author has an hindex of 2, co-authored 6 publications receiving 8 citations.

Critical Moment for Taxi Sector: What Should Be Done by Traditional Taxi Sector After the TNC Disruption?

Abstract: The biggest change in urban mobility during recent years is introduction of TNCs (Transport Network Companies) like Uber and of course the most important impact of TNC disruption happened on traditional taxi services. It is a hot topic of discussion in many countries that how the current taxi industry should respond to TNC disruption. This paper will present the current situation regarding impact of TNCs on Taxis with examples from various countries. Reaction of traditional taxi sector will be analyzed and categorized within this paper as well. Main aim is to help better understanding of different reactions, their categorization and as well potential outcomes for traditional taxi sector to be sustainable in competitive business environment and take role as part of sustainable urban mobility puzzle. There are variety of responses already given by traditional taxi industry to the TNC disruption including ‘Ignoring’, ‘Resisting’ ‘Competition’ and ‘Collaborate’ with the new actors. Different options will be evaluated and discussed in this paper and recommendations will be presented to Traditional Taxi Sector.

Soft computing and regression modelling approaches for link-capacity functions

Abstract: Link-capacity functions are the relationships between the fundamental traffic variables like travel time and the flow rate. These relationships are important inputs to the capacity-restrained traffic assignment models. This study investigates the prediction of travel time as a function of several variables V/C (flow rate/capacity), retail activity, parking, number of bus stops and link type. For this purpose, the necessary data collected in Izmir, Turkey are employed by Artificial Neural Networks (ANNs) and Regression-based models of multiple linear regression (MLR) and multiple non-linear regression (MNLR). In ANNs modelling, 70% of the whole dataset is randomly selected for the training, whereas the rest is utilized in testing the model. Similarly, the same training dataset is employed in obtaining the optimal values of the coefficients of the regression-based models. Although all of the variables are used in the input vector of the models to predict the travel time, the most significant independent variables are found to be V/C and retail activity. By considering these two significant input variables, ANNs predicted the travel time with the correlation coefficient R = 0.87 while this value was almost 0.60 for the regression-based models.

An Analysis of Vehicular Traffic Flow Using Langevin Equation

Abstract: Traffic flow data are stochastic in nature, and an abundance of literature exists thereof. One way to express stochastic data is the Langevin equation. Langevin equation consists of two parts. The first part is known as the deterministic drift term, the other as the stochastic diffusion term. Langevin equation does not only help derive the deterministic and random terms of the selected portion of the city of Istanbul traffic empirically, but also sheds light on the underlying dynamics of the flow. Drift diagrams have shown that slow lane tends to get congested faster when vehicle speeds attain a value of 25 km/h, and it is 20 km/h for the fast lane. Three or four distinct regimes may be discriminated again from the drift diagrams; congested, intermediate, and free-flow regimes. At places, even the intermediate regime may be divided in two, often with readiness to congestion. This has revealed the fact that for the selected portion of the highway, there are two main states of flow, namely, congestion and free-flow, with an intermediate state where the noise-driven traffic flow forces the flow into either of the distinct regimes.

Investigation of the impact of railways on housing values; the case of Istanbul, Turkey

Abstract: Housing units located near transportation facilities tend to have a higher market value than those that are at a greater distance to transport facilities but have similar characteristics. Provision of public infrastructure has a great impact on urban areas, especially on urban development patterns, spatial distribution of urban land use and real estate values. Mass transit systems are one of the most important public infrastructures in cities. Mass transit operations have a significant effect on property values, since they increase accessibility in urban areas. Railway projects are long-lasting investments and by their nature are extremely expensive when compared to other land transportation modes. It is not always possible or reasonable for many countries to fund these high-price projects only with their national budget generated by taxes collected from all citizens. Literature suggests that property values tend to rise in parallel to land values after any kind of public infrastructure investment. Nowadays transportation, especially railway system investments, is regarded as the most important public infrastructure in urban areas impacting land values maximally. Railway investments are becoming widespread in Turkey, especially in Istanbul as Istanbul is the most important and most populated city in country. As due to their high operation costs urban public transport systems, especially railway systems, rarely make a profit, private investors are not willing to get involved in these projects. Furthermore, it is not possible to finance all rail system investments from public funds. This article aims to prove the impact of railway systems on housing values and investigate the possibility of internalizing this increased value for financing railway investments. The main objective of this article is to calculate the impact of distance to a railway station on the value of properties by using the hedonic price model on an existing railway corridor and applying this anticipated impact on a proposed railway corridor. Finally, the calculated value is used as a preliminary basis as a funding model for railway projects in developing countries like Turkey.

How to Level the Playing Field for Ride-Hailing and Taxis

Abstract: Introduction of ride-hailing services created many legal challenges in various countries because of their different features of operation and business model. Policy makers and regulators are pressured to define methods to handle these challenges. Today different countries has taken different approaches as policy and regulatory framework response to the entrance of ride-hailing companies but there is no common approach agreed. This research is meant to provide a system analysis and structured assessment regarding regulatory conflicts after introduction of ride-hailing services in different cities and also regulatory responses of these cities. This study presents an analysis and evaluation of developments to transportation policy and regulation since the proliferation of ride-hailing services with various examples and provide how to effectively approach “leveling the playing field” between traditional taxis and ride-hailing with set of principles to be considered while defining regulatory approach.

Urban travel demand modeling: from individual choices to general equilibrium

Abstract: Aos que acompanham os trabalhos de Norbert Oppenheim (Professor da CUNY-City University of New York) ao longo dos anos, este livro pode ser considerado um resultado esperado e bem-vindo. As pesquisas de Oppenhein nunca limitaram-se aos enfoques dominantes na teoria e na pratica da Engenharia de Transportes, em particular nos aspectos relacionados com os Modelos de Planejamento de Transportes, e sempre manifestaram uma forte vinculacao as tradicoes da Engenharia e Economia, simultaneamente. Por este motivo, era de esperar-se que um livro vindo desta veia trouxesse novidades, e este e o caso, apesar do tom didatico e introdutorio assumido pelo livro em boa parte do texto (finalidade ao qual ele tambem pode servir se o leitor estiver disposto a abandonar algumas tecnicas antigas, de certa forma ultrapassadas, e adotar a abordagem geral proposta pelo Autor). Especificamente no que se refere ao enfoque tradicional, embora revele um resultado superior ao que os trabalhos de pesquisas do autor permitiam antever, o livro de Oppenheim nao chega a ser um exemplo de profundidade e atualizacao. Entretanto, e um livro valioso por incorporar temas importantes que estiveram ausentes de outras publicacoes ate entao (salvo raras excecoes). E tambem um esforco interessante de unificacao de apresentacao de temas tradicionais diversos em Planejamento de Transportes (tratados sistematicamente ao longo dos seus capitulos) e de integracao das tecnicas da pratica em Engenharia de Transportes com a Teoria Economica tradicional (talvez o resultado mais desejado, como faz pensar a escolha de seu subtitulo, mas tambem o fruto menos amadurecido, entre os que o Autor colheu e ofereceu).

The Hamilton-Jacobi Partial Differential Equation and the Three Representations of Traffic Flow

Abstract: This paper applies the theory of Hamilton-Jacobi partial differential equations to the case of traffic flow. The traffic flow surface is analyzed with respect to the three 2-dimensional coordinate systems arising in the space of vehicle number, time and distance. In each case, the solution to the initial and boundary value problems are presented. Explicit solution methods and examples are shown for the triangular flow-density diagram case. This unveils new models and shows how a number of existing models are cast as special cases.

Development of Traffic Volume Forecasting Using Multiple Regression Analysis and Artificial Neural Network

Abstract: The purpose of this study is to develop a model for traffic volume forecasting of the road network in Anamorava Region. The description of the current traffic volumes is enabled using PTV Visum software, which is used as an input data gained through manual and automatic counting of vehicles and interviewing traffic participants. In order to develop the forecasting model, there has been the necessity to establish a data set relying on time series which enables interface between demographic, socio-economic variables and traffic volumes. At the beginning models have been developed by MLR and ANN methods using original data on variables. In order to eliminate high correlation between variables appeared by individual models, PCA method, which transforms variables to principal components (PCs), has been employed. These PCs are used as input in order to develop combined models PCA-MLR and PCA-RBF in which the minimization of errors in traffic volumes forecasting is significantly confirmed. The obtained results are compared to performance indicators such R 2 , MAE, MSE and MAPE and the outcome of this undertaking is that the model PCA-RBF provides minor errors in forecasting.

Assessment of thermal comfort preferences in Mediterranean climate: A university office building case

Abstract: This study aims at evaluating the perceived thermal sensation of occupants with respect to thermal comfort standards, ASHRAE 55 and ISO 7730, for office buildings located in Mediterranean climate. A small office building in Izmir Institute of Technology Campus Area, Izmir, Turkey, was chosen as a case building and equipped with measurement devices to assess thermal comfort of occupants with respect to predicted mean vote and actual mean vote. Both objective and subjective measurements were conducted. The former included indoor and out-door air temperature, mean radiant temperature, relative humidity and air velocity that were used for evaluating the thermal comfort of occupants. Oxygen concentration which can play an additional role in thermal comfort/discomfort, health and productivity of the office occupants, was also measured. Furthermore, occupants were subjected to a survey via a mobile application to obtain subjective measurements to calculate actual mean vote values. Based on objective and subjective measurements, the relationships among the parameters were derived by using simple regression analysis technique while a new combined mean vote correlation was also derived but this time by using multiple linear regression model. Neutral and comfort temperatures were obtained using indoor air temperature and actual mean vote values which were calculated from subjective measurements. The results showed that neutral temperature in the university office building was 20.9°C whilst the comfort temperature range was between 19.4 and 22.4°C for the heating season. By applying new comfort temperatures, energy consumption of the case building located in Mediterranean climate, can be reduced.