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ÖgeA new model and approach for assessing equity in public transport(Graduate School, 2024-10-09)Public Transportation is a cornerstone of urban mobility, ensuring access to essential services, employment, education, healthcare, and social participation for millions worldwide. However, the equitable distribution of public transport services presents a significant challenge, particularly in rapidly urbanizing regions with pronounced socioeconomic disparities. This thesis investigates the concept of public transport equity in Kocaeli, Turkey, using Smart Card Data (SCD), General Transit Feed Specification (GTFS), and Household (HH) data to critically assess the effectiveness of current travel-based transport models. A fundamental gap in traditional models is identified, as they often overlook the travel patterns of occasional users, thereby failing to account for the needs of the entire spectrum of public transport users. This omission challenges efforts to create inclusive and sustainable urban transport systems aligned with Sustainable Urban Mobility Plans (SUMP). The research methodology is divided into multiple phases, encompassing data extraction, cleaning, clustering, and merging of datasets. By integrating SCD, GTFS, and HH data, the study creates a unified dataset that combines transit behavior with socioeconomic indicators. Key analytical tools, such as the Public Transport Supply Index (PT index), Lorenz curves, Gini coefficients, and the Suits index, are employed to evaluate the equity of public transport services across different zones. The introduction of the frequency-weighted origin-destination (OD) matrix and Inverse Probability Weighting (IPW) method allows for a more nuanced analysis of travel demand, particularly accounting for the variability in travel behavior across frequent and infrequent users. By segmenting user groups based on onboarding patterns, card types, usage frequency, and weekday versus weekend travel, distinct profiles for regular and occasional users are developed. These user groups are analyzed both for daily data distribution and route-based representation. The trip chain method, used to construct an OD matrix, uncovers service gaps, highlighting how current models disproportionately favor frequent users in policy-making and resource allocation. This results in disparities in service, particularly for vulnerable populations such as low-income residents, the elderly, and those living in peripheral areas. The study's findings demonstrate that infrequent users, often reliant on public transport for essential trips, are underserved, while policy-making skews toward the needs of regular commuters. By incorporating frequency-based equity measures, such as the IPW-adjusted OD matrix, the thesis proposes a more equitable framework for transport planning. This new model advocates for a user-centered approach, where service frequency and socioeconomic factors are integrated into decision-making processes. The research concludes with recommendations for improving service frequency in underserved areas, enhancing multimodal integration, and adopting dynamic planning approaches that respond to real-time user data. These strategies aim to create a more equitable public transport system, ensuring that services benefit all city residents, including marginalized groups and occasional users. Ultimately, the thesis contributes to both academic discourse and practical applications in urban transport planning, advocating for sustainable and equitable urban mobility solutions
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ÖgeLif katkılı beton yol kaplamalarının dinamik yükler altındaki yorulma davranışının incelenmesi(Lisansüstü Eğitim Enstitüsü, 2024-01-23)Tam derzli beton yollarda derzlerden süzülen yağmur suları veya drenaj sularından kaynaklı kaplama altındaki temel tabakasında yumuşama meydana gelmektedir. Yollardan araçların sürekli geçişi ile birlikte, yağmur suları derzlerden geri yüzeye çıkmaktadır, bu çıkışları esnasında su ile birlikte, temel tabakasında ince taneli zeminleri, ve kumlarıda yüzeye çıkarmaktadır. İnce tanelerin ve kumların yüzeye çıkması sonrası temel tabakasında boşluklar oluşmaktadır. Tekrar eden trafik geçişleri esnasında bu durum sürekli tekrarlanır ve zamanla temel tabakasındaki boşluklar daha da artar. Bu arada oluşan mekanizmaya hydropomping mekanizmasıdır. Temel tabakasında meydana gelen boşalmalar sonucunda da, araçların tekrarlı geçişleri esnasında derz bölgelerinde kısa zamanda oluşan çatlaklar beton kaplamanın hizmet ömrünü kısaltabilmektedir. Bu çalışma kapsamında, türkiyede özellikle karadeniz bölgesinde bulunan köy yollarında , ilgili belediyeler , il özel idarelerinde ve kgm şartnamelerinde bu konuyla alakalı herhangi bir bilgi yer almamaktadır.
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ÖgeOECD ülkeleri ve ülkemizde meydana gelen karayolu trafik kazalarının incelenmesi ve sonuçlarının karşılaştırılması(Lisansüstü Eğitim Enstitüsü, 2023-04-05)Taşımacılık sektörü, tarih boyunca ülkelerin sosyal, ekonomik ve kültürel faaliyetlerinin gelişmesinde ve canlanmasında etkin rol oynayan önemli bir faaliyet alanıdır. Her geçen gün gelişen teknolojiye ve çalışma ortamlarının artık dijitalleşme çağına girmesine rağmen bu sektör işlerinin büyük bir kısmını hala fiziki olarak devam ettirmektedir. Sektör Karayolu Taşımacılığı, Demiryolu Taşımacılığı, Hava Taşımacılığı ve Denizyolu Taşımacılığı olmak üzere dört ana gruba ayrılmaktadır. Sektör bu dört ana alandaki farklı niteliklerdeki nakliye ve nakliye ihtiyaçlarını farklı koşul ve imkanlarla karşılamaktadır. Trafik kazaları bir taşıtın herhangi bir başka karayolu taşıtına, yayaya, hayvana veya herhangi bir başka nesneye çarpması sonucu oluşan durumdur. Bu çalışmanın kapsamı, Organisation for Economic Co-operation and Development (OECD) ülkelerinde ve Türkiye'de meydana gelen karayolu trafik kazalarının nedenlerinin literatürde nasıl analiz edildiğini belirlenmesi, incelenmesi ve bulunan sonuçların karşılaştırılmasıdır. Çalışmada OECD üyesi olan 38 ülkeden 21 ülkenin 2005 yılı ile 2018 yılları arasındaki karayolu trafik kazalarına bağlı ölüm verileri kullanılmıştır. Verileri eksik olan ülkeler analize dahil edilmemiştir. OECD' ye üye olan ülkelerin yolcu ve yük taşımacılığı, yaralanmalı karayolu trafik kaza sayısı ve karayolu trafik kazasına bağlı ölüm sayısı verilerinin 2005-2018 yılları arasındaki ortalaması ile analiz gerçekleştirilmiştir. Karayolu trafik kazasına bağlı ölen kişi sayısı, milyon kişi başına olarak ölçülmüştür. Analizde kullanılacak yıllar, Covid-19 pandemi zamanı da dikkate alınarak, pandemi öncesi zaman özellikle seçilmiştir. Analiz dışında bırakılan Covid-19 dönemi ayrı bir bölümde incelenmiştir. Çalışmada Covid-19 döneminde ülkelerin aldıkları fiziksel mesafe, karantina, evde kalma uygulamaları, okulların kapatılması, toplanma ve seyahat kısıtlamaları gibi günlük hayatın hareketliliğini önemli ölçüde etkileyen önlemlerin araç trafiği hareketliliği azaltmasının karayolu trafik kazaları üzerindeki etkisi araştırılmıştır. Ülkelerde Covid-19 döneminde alınan önlemlerin katılık derecesini ölçen Oxford Katılık Endeksi ile bu ülkelerde pandemi dönemi meydana gelen karayolu trafik kazalarında ölen kişi sayıları arasında bir korelasyon olduğu belirtilmiştir. Bu korelasyonun Oxford Katılık Endeksi 50'nin üzerinde olan Arjantina, İtalya ve Kolombiya gibi ülkelerde daha güçlü, 50'nin altında olan ülkelerde ise daha zayıf olduğu söylenmiştir. OECD' ye üye olan ülkelerin 2005-2018 yılları arası karayolu trafik kazasına bağlı ölüm sayısı verisi gri ilişkisel analiz tekniği kullanılarak analiz edilmiştir. Çalışmada karayolu trafik kazasına bağlı ölüm sayısı minimize edilecek değerler olarak alınmıştır. Çıkan sonuçlar ise OECD ülkelerinde ve Türkiye'de yaşanan kazalar olarak iki başlık altında incelenmiş ve karşılaştırma yapılmıştır. Ülkelerin yolcu ve yük taşımacılığı, yaralanmalı karayolu trafik kaza sayısı ve karayolu trafik kazasına bağlı ölüm sayısı verileri kullanılarak yapılan karşılaştırmalar sonrasında ulaşılan bulgulara göre, gri ilişki derecesi en yüksek olan ilk 5 ülke sırasıyla Türkiye, sonrasında Norveç, İsviçre, İngiltere ve Fransa olarak tespit edilmiştir. En düşük olan son 5 ülke sırasıyla Amerika Birleşik Devletleri (ABD), Litvanya, Letonya, Avustralya ve Almanya'dır.
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ÖgeEffects of cooperative vehicle dynamics on traffic flow control(Graduate School, 2022-02-25)In the era of advances in vehicular and communication technologies, the need to improve both the efficiency in the use of road capacities and the safety as a consequence of the increasing demand for transport has emerged the realization of traffic management strategies through by Intelligent Transportation Systems (ITS). Having been fed with the methodological advances, the implementation of several intelligent systems, including the Ramp Meters, Variable Speed Limits, and Route Guidance Tools, has therefore become well-known. Furthermore, new advancements in communications, as well as their integration with what recent vehicular technology recommends, increase the usefulness of ITS tools via Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication channels. In this context, the main purpose in a wide range of studies involving traffic flow modeling and control under various configurations has been to determine an ideal rate of penetration for Cooperative Adaptive Cruise Control (CACC) managed vehicles in mixed traffic. According to the related literature, the efficiency in road traffic management can be improved by combining the strategies and hence the tools for ITS in an integrated manner and by improving the control mechanisms used. The emerging research direction in the presence of autonomous road traffic systems contributes significantly to long-term infrastructure planning strategies necessitated by the introduction of connected vehicles into actual traffic. In other words, having projections on market penetration rates of connected vehicles and the effectiveness of varying penetration rates aid in minimizing costly infrastructure investments in the short term by spreading them out over time. Therefore, the main objective in this study has been to improve the performance of the control we employ to mixed traffic flow, which consists of Human Driven Vehicles (HDVs) and CACC equipped vehicles, through strategies for managing freeway traffic. To that end, we theoretically propose a complete control system for freeway networks by combining the RM and VSL tools. Using real data for model calibration, we demonstrate the performance of the controller that we have introduced for the integrated management of freeway traffic flow for the first time in the literature. The modeling and the control feature of this study involves proposing a control framework for freeway traffic, applying this framework to real network traffic simulated using real data, and evaluating the effects of changes in market penetration rate on performance measures such as total system travel time, total throughput, and emission pollutants. We have made use of an H∞ based control strategy to maintain robustness in the presence of disturbances, which could result in poor performance of the system behavior in the presence of exogeneous inputs. One of the primary benefits of such a control strategy is that it can be guaranteed that the dynamical system evolves properly in the absence of disturbances, and that such nominal behavior is preserved up to a steady-state error proportional to the applied disturbance and an H∞ gain in the presence of perturbations. Incorporated H∞ State Feedback Controller aims to sustain the mainstream traffic at a critical density through an integrated management system of freeway traffic. This is achieved by taking into account the queue lengths on on-ramps and the downstream and upstream occupancies on the mainstream in the presence of disturbances caused by inflows to the mainstream and from the on-ramps. In contrast to other robust control systems, H∞ based control is commonly used when working with linear models. We have made use of the Lighthill-Whitham-Richards (LWR) ordinary differential equations (ODE) model to describe traffic flow. The integrated control performance evaluations are carried out on the micro-simulation environments SUMO and PTV VISSIM using the features of a real network and model parameters calibrated based on field data. In order to simulate human drivers, Intelligent Driver Model (IDM) and Wiedemann 99 car-following models are used. For CACC vehicles, Milanes and Shladover's car-following model is utilized. The contribution of the work presented in this thesis is unique in two ways: using an H∞ State Feedback Controller for the integrated control involving RM and VSL; using real data to perform the integrated control for freeway traffic through RM and VSL and, discussing the effects of the combined control with the H∞ State Feedback Controller on the penetration rates of CACC equipped vehicles in mixed traffic.
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ÖgeInvestigating risk assessment and role of safety concerns in autonomous vehicle(Graduate School, 2022-11-14)Self-driving vehicles are of critical importance to a future sustainable transport system, which is expected to become widespread around the world. The future transportation system includes more automated driving technologies and intelligent systems. Autonomous vehicles are widely expected to be in common usage in cities and transform the mobility system in the coming years. Autonomous vehicle technology is expected to be an integral part of our future transportation system. However, a substantial amount of risk is associated with self-driving vehicles which must be considered by decision-makers effectively. Given that automated driving technology and how it will interact with the mobility system are substantially risky, the risks involved in self-driving vehicles need to be addressed appropriately. The identified knowledge gap of the pre-literature review is that an overview of the identification which completely considers all types of risks related to self-driving vehicles does not exist. In answer to the knowledge gap, the purpose of the first study is to rank the risks in self-driving vehicles. As the widespread usage of autonomous vehicles is closer to becoming a reality, substantial consideration should also be paid to the extent to which individuals choose vehicular mobility tools. Some evidence highlights the fact that the perceived safety of self-driving vehicle has a major impact on the social acceptance and application of autonomous technology. This may help identify the extent to which people will adopt and use self-driving vehicles and the rate at which their safety concerns might be realized on the road. The purpose of the second study is to examine vehicle ownership models to better understand the adoption of vehicles by considering some factors such as liability issues, cost, safety, and environmental characteristics. Investigating potential drawbacks and attitudes towards safety concerns of AVs have substantial amount of importance for transportation planners and policy-makers. Thus, this thesis will seek to provide a deeper understanding of behavioral aspects associated with individuals' autonomous vehicle choices. Specifically, it is investigated the travelers' risk perception toward AV future as well as the analysis and prioritization of the risks associated with self-driving vehicles. Chapter 2 summarizes the literature review related to road safety and risk landscape of self-driving vehicles, an overview on adoption and ownership of autonomous vehicle and literature about hybrid and integrated fuzzy multi-criteria decision-making methods and its applications to real-world problems. New hybrid MCDM approaches, integrating the extended Fuzzy AHP, extended Fuzzy TOPSIS, and extended Fuzzy VIKOR methods, are proposed for the selection problem in this research study. The proposed hybrid methods are extended with Pythagorean fuzzy sets to handle the complex decision problem involving self-driving vehicles. The extended approach comprises uncertainty in decision-making problems by implementing Fuzzy Set Theory (FST). Additionally, each Decision Maker (DM) in the decision-making team has their individual importance within the team. Chapter 3 formulates the methodological contributions of this research to the literature. Risk prioritization is a complicated multi-criteria decision-making (MCDM) problem that requires consideration of multiple feasible alternatives and conflicting intangible and tangible criteria. This study addresses the prioritization of risks involved with self-driving vehicles by proposing new hybrid MCDM methods based on the Analytic Hierarchy Process (AHP), the Technique for order preference by similarity to an ideal solution (TOPSIS) and Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) under Pythagorean fuzzy environment. According to the review of the literature on risk landscape of self-driving vehicles, there has been no study of reviewing and prioritizing all types of risks associated with autonomous vehicles. Therefore, an expert team is asked to specify the risks and criteria for evaluation. By personal interview with 4 experts from academia and industry as well as literature review, eight risks involved in autonomous vehicles, 7 main criteria together with 10 sub-criteria are identified, the proposed methodology is employed in Chapter 4. Calculations of proposed methods gave similar results. Distance from Pythagorean fuzzy positive ideal solution (PIS) and negative ideal solution (NIS) for Pythagorean fuzzy TOPSIS (PF-TOPSIS), and the utility measure Si, the regret measure Ri and VIKOR-specific index Qi for Pythagorean fuzzy VIKOR (PF-VIKOR) are utilized for ranking the alternatives. Based on the results of analysis, Cyber Attack Risk involves the maximum amount of risk, and the consecutive risk is Reputational risk. The result of the proposed model is validated by performing sensitivity analysis. Sensitivity analysis is carried out to specify the impact of criteria weights on the decision- making process. Sensitivity analysis is conducted by changing the weight of the maximum group utility, and through exchanging the weight values of criteria for observing which criteria are most significant and how the criteria weights affect the autonomous vehicles' risk prioritization. To further validate the effectiveness and robustness of the proposed hybrid method computations, two different comparative analyses are performed in this study. The performance of proposed methodology with Pythagorean fuzzy sets is compared with those with ordinary fuzzy sets and it is revealed that the proposed method provides informative and reliable outcomes to better represent the impreciseness of decision making problems. AHP method is also performed to conduct comparative analysis. Based on the AHP analysis, cyber attack risk was found to be the first risk, and the consecutive risk is reputational risk. This result is similar to the one acquired by the proposed method. The remaining ranking shows different precedence. Chapter 5 and Chapter 6 investigate the role of safety concerns in autonomous vehicle ownership choice. Survey design, data collection, and description of data sets are indicated in Chapter 5. 1197 respondents were recruited from Istanbul, Turkey to complete the stated choice experiment through a web-based survey. Revealed Preference (RP) and socio-demographics data set, and the impact of socio-demographic characteristics on vehicular mobility tools are analyzed in detail. Then, an experimental design is conducted to respond to the research questions as clearly as possible. Research methodology and results of autonomous vehicle ownership choice model estimation are given in Chapter 6. An overview of the disaggregate choice model, multinomial logit model (MNL) specification, and mixed logit choice model (ML) specification, specifically the Heteroscedastic mixed logit model are discussed in this chapter. The methodologies to test the model significance, such as Log Likelihood Ratio, Pseudo Rho Square tests are also provided. Multinomial logit and Heteroskedastic mixed logit models were estimated to unravel users' preferences concerning the selection of autonomous vehicles with distinction among private, shared, and ride-hailing vehicles. Results indicate that the adoption of those vehicles varied concerning the aforementioned characteristics, and these findings could help decision-makers to develop a vehicular mobility system for future transportation dynamics. The policy makers need to deal with legal issues surrounding automated vehicles, specifically liability issues. In case of any at fault accidents, vehicle and software manufacturers may be liable instead of users. Shifting the burden on manufacturers would enable users to purchase automated vehicles as there would be less liability upon them. Reduced cost is another factor affecting whether consumers will choose autonomous vehicles. Therefore, service providers should implement strategies for cost reduction. When commuters are also given an incentive to install ride-hailing applications, they will prioritize automated vehicle production which will incentive consumers to purchase ride-hailing and shared vehicles. The motivation of this study was to provide more insights into the identification and prioritization of self-driving vehicles' risks which is an essential knowledge gap in the literature. The evaluation criteria determined by this study is novel as well, hence the research gap about some safety issues on self-driving vehicles will be filled through the current study. The results are significant as they shed light on the risk perception of the self-driving vehicle industry taking into account the risk factors. The finding of this study will enable decision-makers to take into consideration not only the hacking and malfunction factors but also the environmental, acceptance, and liability factors by containing the vagueness of experts' judgments. The study demonstrates that more sustainable and safer travel is achieved by considering risks. The results of this study also present an essential contribution that could be useful to transportation planners for constructing the future transportation system by considering the preference for vehicular mobility tools. The research findings will enable AV developers to consider liability issues, cost, and safety factors before releasing the different types of self-driving vehicles.