Browsing by Author "Kaya, Omer"

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Accessibility of Vaccination Centers in COVID-19 Outbreak Control: A GIS-Based Multi-Criteria Decision Making Approach
(MDPI, 2021) Alemdar, Kadir Diler; Kaya, Omer; Codur, Muhammed Yasin; Campisi, Tiziana; Tesoriere, Giovanni
The most important protective measure in the pandemic process is a vaccine. The logistics and administration of the vaccine are as important as its production. The increasing diffusion of electronic devices containing geo-referenced information generates a large production of spatial data that are essential for risk management and impact mitigation, especially in the case of disasters and pandemics. Given that vaccines will be administered to the majority of people, it is inevitable to establish vaccination centres outside hospitals. Site selection of vaccination centres is a major challenge for the health sector in metropolitan cities due to the dense population and high number of daily cases. A poor site selection process can cause many problems for the health sector, workforce, health workers, and patients. To overcome this, a three-step solution approach is proposed: (i) determining eight criteria using from the experience of the advisory committee, (ii) calculating criterion weights using Analytic Hierarchy Process (AHP), and performing spatial analysis of criteria using Geographic Information System (GIS), (iii) assigning potential vaccination centres by obtaining a suitability map and determining service areas. A case study is performed for Bagcilar, Istanbul district, using the proposed methodology. The results show that the suitable areas are grouped in three different areas of the district. The proposed methodology provides an opportunity to execute a scientific and strategic vaccination programme and to create a map of suitable vaccination centres for the countries.
Automatic Detection and Classification of Road Defects on a Global-Scale: Embedded System
(Elsevier Sci Ltd, 2025) Kaya, Omer; Codur, Muhammed Yasin
Road networks are created with different pavement designs. In general, flexible pavement is preferred as the most used superstructure type in the world. Road networks with this superstructure experience deterioration for some reasons. These deteriorations take different forms over time and create road defects. The process of identifying defects is very important for the efficiency of the road pavement and traffic components. In this study, the process of automatic detection and classification of road defects occurring in flexible superstructure road networks was carried out with an intelligent system. Road images obtained from eight different countries and 10 different road defects were taken into consideration in the study. YOLOv5 object detection model was used in the detection process of defects. The training processes were completed by creating five different variants and different combinations and YOLOv5l provided the best performance. mAP and F1 Score values were determined as 0.526 and 0.540, respectively. In addition, a global-scale automatic road defect detection system has been developed via new data set consisting of different countries. The developed system is a prototype and has the ability to detect and classify defects occurring in road networks in real-time. To the best of our knowledge, this is the first study to detect the most road defect classes in real time. The created system was tested on a 4.5 km long university campus network as a case study. D00-517, D10-507, D20-50, D30-2, D40-48, D50-18, D60-343, D7025 and D80-9 were detected in real-time by the embedded system. It is clear that the system will be a guide for road network managers by obtaining location information of the identified defects. Detecting, classifying and locating road defects with the developed system will accelerate the maintenance and repair process of road networks and also extend their service life. Road safety and comfort of traffic components using the road network will also be increased. As a result, an example of vehicle-infrastructure (V2I) communication, which is a form of intelligent transportation systems application, is presented in this article.
Automatic Detection of Pedestrian Crosswalk with Faster R-CNN and Yolov7
(MDPI, 2023) Kaya, Omer; Codur, Muhammed Yasin; Mustafaraj, Enea
Autonomous vehicles have gained popularity in recent years, but they are still not compatible with other vulnerable components of the traffic system, including pedestrians, bicyclists, motorcyclists, and occupants of smaller vehicles such as passenger cars. This incompatibility leads to reduced system performance and undermines traffic safety and comfort. To address this issue, the authors considered pedestrian crosswalks where vehicles, pedestrians, and micro-mobility vehicles collide at right angles in an urban road network. These road sections are areas where vulnerable people encounter vehicles perpendicularly. In order to prevent accidents in these areas, it is planned to introduce a warning system for vehicles and pedestrians. This procedure consists of multi-stage activities by sending warnings to drivers, disabled individuals, and pedestrians with phone addiction simultaneously. This collective autonomy is expected to reduce the number of accidents drastically. The aim of this paper is the automatic detection of a pedestrian crosswalk in an urban road network, designed from both pedestrian and vehicle perspectives. Faster R-CNN (R101-FPN and X101-FPN) and YOLOv7 network models were used in the analytical process of a dataset collected by the authors. Based on the detection performance comparison between both models, YOLOv7 accuracy was 98.6%, while the accuracy for Faster R-CNN was 98.29%. For the detection of different types of pedestrian crossings, YOLOv7 gave better prediction results than Faster R-CNN, although quite similar results were obtained.
Comparison of Modern and Conventional Methods at the Entrance and Exit of Tunnels
(City Net Scien Res Ctr Ltd-belgrade, 2018) Alemdar, K. Diler; Kaya, Omer; Kuskapan, Emre; Codur, M. Yasin; Tortum, Ahmet
Turkey has gained importance especially highway transport since 1950. For this reason, the number of vehicles on the highways has rapidly increased and this increase has brought many problems. The most important problem is traffic accidents which cause material and spiritual loss. The Winter conditions that are effective in some regions of the country occur disruptions in highway transportation. Particularly in winter when the temperatures are below 0 degrees C accidents happen due to the snow and icing. Although millions of dollars are spent every year to struggle against snow and icing, existing methods are insufficient. Conventional methods used in the struggle against snow and ice damage to pavements, metal parts, environment, human health and economy of the country. Tunnels are often used because of Turkey's geographical situation. 'Traffic accidents are often seen at the entrance and exit of tunnels, especially during the winter seasons because of snow and icing. In these areas, the ice detection and prevention systems as an application of intelligent transportation system can be used instead of conventional methods to reduce the number of traffic accidents. In this study, it is compared that conventional method with the ice detection and prevention system in terms of advantages and disadvantages.
A Data-Driven Spatial Decision Framework for Assessing the Relationship Between Logistics Activities and Heavy Vehicle Accident Risks
(Elsevier, 2025) Kaya, Omer; Kabakus, Nuriye
The increase in consumption habits of societies causes individual and collective mobility. This situation gradually increases the importance of logistics centers (LCs), which are the key parts of the developed supply chain. However, heavy vehicles, which are frequently preferred for customer satisfaction and supply, have recently been involved in many traffic accidents. A balance must be achieved in order to carry out logistics activities safely. In this study, the interaction between the site selection of LCs and the severity of heavy vehicle accidents was investigated. To do so, a four-stage hybrid solution approach was proposed. (i) First, the criteria affecting the site selection and logistics activities of LCs were determined. Then, the risk factors causing heavy vehicle traffic accidents were determined. (ii) The weights of these criteria and risk factors were calculated with the fuzzy SIWEC method. (iii) The availability maps were obtained in the spatial decision-making process via GIS. (iv) Finally, the relationship between logistics activities and heavy vehicle accidents was defined by combining spatial outputs and weight values. The concrete relationship between logistics activities and heavy vehicle accident severity was carried out by Pearson coefficient analysis. The proposed approach was applied to T & uuml;rkiye as a case study. The correlation coefficient was determined as 0.611229 and the relationship between them was found to be moderate and strong correlation. The first step of safe supply can be achieved by reducing the occurrence of heavy vehicle accidents by opening new LCs in some critical areas.
Designing Green and Safe Micro Mobility Routes: An Advanced Geo-Analytic Decision System Based Approach to Sustainable Urban Infrastructure
(Elsevier - Division Reed Elsevier India Pvt Ltd, 2025) Kaya, Omer
Urban mobility faces increasing challenges due to congestion, environmental concerns, and inefficiencies in transport infrastructure. Micro-mobility solutions have gained significant attention as a sustainable alternative, yet their integration into urban transport networks remains a complex task. To this end, this study introduces a geo-analytic decision-making framework for optimizing micro-mobility route planning. The methodology consists of five key steps: (i) identification and spatial analysis of 33 critical factors influencing micro-mobility adoption in a Geographic Information Systems (GIS) environment; (ii) a suitability map for the routes was generated using the state-of-the-art Fuzzy Logarithm Methodology of Additive Weights (FLMAW) and Fuzzy Simple Weight Calculation (fuzzy SIWEC) weighting methods. It was determined that criteria such as cyclist lanes, public transportation routes, terrain inclination, and recreational areas have a high impact on micro mobility use; (iii) based on this analysis, 21 optimized routes were developed, and their relationships with the main criteria were validated through Spearman's rank correlation analysis, revealing a significant and strong positive correlation; (iv) additionally, Random Forest classification was applied to categorize routes into nine different usage classes. Route classes with different nicknames such as GreenLink and UrbanHealth Path have been created; and (v) DOmbi Bonferroni (DOBI) performance evaluation method was used to determine the preferred priority order for route construction in the study area. The results indicate that the construction priority of routes R9 and R10 is higher than that of other routes. The proposed framework offers a scalable, adaptable, data-driven, and evidence-based approach, providing valuable insights for urban planners and policymakers aiming to integrate micro-mobility into sustainable transportation strategies.
The Development of Decarbonisation Strategies: A Three-Step Methodology for the Suitable Analysis of Current EVCS Locations Applied to Istanbul, Turkey
(MDPI, 2021) Kaya, Omer; Alemdar, Kadir Diler; Campisi, Tiziana; Tortum, Ahmet; Codur, Merve Kayaci
One of the solutions to reduce environmental emissions is related to the deployment of electric vehicles (EVs) with sustainable energy. In order to be able to increase the number of electric vehicles in circulation, it is important to implement optimal planning and design of the infrastructure, with particular reference to areas equipped with charging stations. The suitable analysis of the location of current electric vehicle charging stations (EVCSs) is the central theme of this document. The research focused on the actual location of the charging stations of five major EVCS companies in the province by selecting Istanbul as the study area. The study was conducted through a three-step approach and specifically (i) the application of the analytical hierarchy process (AHP) method for creating the weights of the 6 main and 18 secondary criteria that influence the location of EVCSs; (ii) a geospatial analysis using GIS considering each criterion and developing the suitability map for the locations of EVCSs, and (iii) application of the technique for order preference by similarity to ideal solution (TOPSIS) to evaluate the location performance of current EVCSs. The results show that the ratio between the most suitable and unsuitable areas for the location of EVCSs in Istanbul and the study area is about 5% and 4%, respectively. The results achieved means of improving sustainable urban planning and laying the basis for an assessment of other areas where EVCSs could be placed.
Electric Car Sharing Stations Site Selection from the Perspective of Sustainability: A GIS-Based Multi-Criteria Decision Making Approach
(Elsevier, 2022) Kaya, Omer; Alemdar, Kadir D.; Atalay, Ahmet; Codur, Muhammed Y.; Tortum, Ahmet
It is undoubtedly that the environmental and economic benefits will increase by integrating electric vehicles, which are the vehicles of the future, with the car-sharing system. The problem of determining the locations of electric vehicle charging stations (EVCS) and service areas of the car-sharing system appear with the integration. Environmental and energy concerns are the biggest driving factor behind electric car-sharing systems. In this study, Geographic Information Systems (GIS) based fuzzy multi-criteria decision making (MCDM) method is proposed for the solution of site selection problems of electric car-sharing stations (ECSS). To do so, a three-step solution methodology is developed: (i) determining 20 sub-criteria and weighting the criteria with fuzzy Analytic Hierarchy Process (f-AHP), (ii) obtaining a suitability map for potential ECSS via GIS, (iii) sorting the performance levels of ECSSs assigned according to the suitability map by Elimination and Choice Translating Reality (ELECTRE). The proposed methodology is applied for Istanbul, a metropolitan city in Turkey as a case study. The results show that the most suitable areas for ECSSs in the European and Anatolian side, Istanbul is an intercontinental city, are the south-east part and south-western part, respectively.
Evaluation of Air Quality Index by Spatial Analysis Depending on Vehicle Traffic During the Covid-19 Outbreak in Turkey
(MDPI, 2021) Alemdar, Kadir Diler; Kaya, Omer; Canale, Antonino; Codur, Muhammed Yasin; Campisi, Tiziana
As in other countries of the world, the Turkish government is implementing many preventive partial and total lockdown practices against the virus's infectious effect. When the first virus case has been detected, the public authorities have taken some restriction to reduce people and traffic mobility, which has also turned into some positive affect in air quality. To this end, the paper aims to examine how this pandemic affects traffic mobility and air quality in Istanbul. The pandemic does not only have a human health impact. This study also investigates the social and environmental effects. In our analysis, we observe, visualize, compare and discuss the impact of the post- and pre-lockdown on Istanbul's traffic mobility and air quality. To do so, a geographic information system (GIS)-based approach is proposed. Various spatial analyses are performed in GIS with the statistical data used; thus, the environmental effects of the pandemic can be better observed. We test the hypothesis that this has reduced traffic mobility and improved air quality using traffic density cluster set and air monitoring stations (five air pollutant parameters) data for five months. The results shows that there are positive changes in terms of both traffic mobility and air quality, especially in April-May. PM10, SO2, CO, NO2 and NOx parameter values improved by 21.21%, 16.55%, 18.82%, 28.62% and 39.99%, respectively. In addition, there was a 7% increase in the average traffic speed. In order for the changes to be permanent, it is recommended to integrate e-mobility and sharing systems into the current transportation network.
Footprints of the Future: Cleaner and Faster Transportation with Shared E-Scooter Operational Models
(MDPI, 2025) Kaya, Omer
In recent years, shared e-scooters have become increasingly popular as a mode of transportation in urban areas. Shared e-scooters have emerged as a convenient and sustainable transportation option in urban areas, providing users with a flexible and efficient way to travel short distances within a city. Many service providers and local municipalities are interested in implementing shared e-scooter operational models. However, determining which operating model to prefer and what the service areas will be is a significant problem. We aimed to solve the implementation of three different operational models, the site selection problem of station locations, and service areas for Erzurum, the metropolitan city in this study. As shared e-scooter is quite a new transportation mode; information collected to assess the operational models' sustainability performance may be indeterminate and vague. In this study, the Geographic Information System (GIS)-based hybrid multi-criteria decision-making (MCDM) method is proposed for the solution of implementation, site selection, and service areas problems of three different shared e-scooter operational models. To this end, a four-step scientific and strategic solution approach is developed: (i) the identification and detailed explanation of 5 main and 24 sub-criteria, (ii) the weighting of criteria through the Analytical Hierarchical Process (AHP), Multi-Influencing Factor (MIF), and Best-Worst Method (BWM) in order to increase the sensitivity and robustness of the study, (iii) obtaining a suitability map for the solution of implementation, site selection, and service areas problems of operational models, and (iv) assigning shared e-scooter stations and analyzing their performance levels with COmplex PRoportional ASsessment (COPRAS). The results show that, in Erzurum, the central three districts are the most suitable for service areas. The paper's solution methodology can help service providers and policymakers invest in sustainable shared e-scooter operational models, even in situations of high uncertainty.
A GIS and Microsimulation-Based MCDA Approach for Evaluation of Pedestrian Crossings
(Pergamon-Elsevier Science Ltd, 2020) Alemdar, Kadir D.; Kaya, Omer; Codur, Muhammed Y.
Pedestrian crossings are sites in which vehicles and pedestrians can crash into each other, and are very important in terms of urban traffic. Drivers and pedestrians are more likely to violate traffic regulations, and thus adversely affect traffic safety and flow, in streets that have many such crossings. Careful planning of pedestrian crossing locations provides a solution to these problems. In this study, a corridor-based analysis of such sites is performed. Twenty-four criteria that are considered to affect pedestrian crossing locations and traffic flow aredetermined. Based on these criteria, the most suitable pedestrian crossing scenario is identified using Geographical Information Systems (GIS). The Analytic Hierarchy Process (AHP) and VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) from Multi-Criteria Decision Analysis (MCDA) methods are used to evaluate the pedestrian crossing locations, and PTV VISSIM is used to examine the impact of these sites on traffic. The proposed method is then applied to a case study of Erzurum, Turkey that involves determining the best pedestrian crossing scenario. The results show that the most suitable scenario is S.2. In terms of the evaluation criteria, this alternative scenario provides an improvement of up to 50 % over the current situation. Finally, a sensitivity analysis is performed to reveal the effect of changing the criteria weights on the evaluation process.
Interdisciplinary Evaluation of Intersection Performances-A Microsimulation-Based MCDA
(MDPI, 2021) Alemdar, Kadir Diler; Tortum, Ahmet; Kaya, Omer; Atalay, Ahmet
Intersections are the most important regions in terms of urban traffic management. The intersection areas on the corridor should be analyzed together for consistency in traffic engineering. To do so, three intersections on the Vatan Street corridor in Istanbul, the most crowded city of Turkey, were examined. Various geometric and signal designs were performed for intersections and the most suitable corridor design was analyzed. The corridor designs were modeled with the PTV VISSIM microsimulation software. The most suitable corridor design was evaluated by using the results obtained from the microsimulation via analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) from multi criteria decision analysis (MCDA) methods. The evaluation criteria in the study are vehicle delay, queue length, stopped delay, stops, travel time, vehicle safety, CO emission, fuel consumption, and construction cost. As a result, the current and the most suitable alternative corridors were compared according to the comparison parameters and up to 80% improvements were observed. Thus, some advantages were obtained in terms of energy, environment, time, and cost.
A New Data-Driven Model for Vehicle and Pedestrian Safety: Statistical Approach Based on Spatial Decision-Making
(Taylor & Francis Ltd, 2025) Kabakus, Nuriye; Kaya, Omer
Minimizing the losses that occur after traffic accidents is a primary duty for all humanity. To do so, it is necessary to examine and analyse the potential risk factors that affect the severity of traffic accidents. In this article, a new spatial decision-making-based statistical solution methodology is proposed to determine the accident risk factors that occur in three different accident types using 5-year (2015-2019) accident data. (i) 22 independent variables and 157 sub-variables were determined for the traffic accident categories where vehicle-vehicle, vehicle-pedestrian and vehicle-other collision types occurred, (ii) the fuzzy simple weight calculation method was preferred to determine the effects of risk factors on accident categories, (iii) spatial analyses of risk factors were provided via geographical information system and combined with the obtained effect values, (iv) the current effect of risk factors on accident categories was tested with the multinomial logistic regression model. The multinomial logistic regression model results revealed a strong model fit (McFadden R2 = 0.749) and identified the variables that significantly increase or decrease the probability of each crash type compared to the reference category. For instance, while the geo-intersection had the highest effect for vehicle-vehicle crashes, the pedestrian defect had the highest impact for vehicle-pedestrian crashes. Spatial analysis results also showed that accident severity tends to be higher in the western, southern, and central regions of T & uuml;rkiye. The proposed methodology offers a comprehensive framework that supports evidence-based policy development for improving traffic safety. The resulting findings serve as a guide for local administrators, policy makers, and traffic safety experts with regard to vehicle and pedestrian safety.
A Novel Two-Stage Approach for Electric Taxis Charging Station Site Selection
(Elsevier, 2020) Kaya, Omer; Alemdar, Kadir D.; Codur, Muhammed Y.
The biggest change will occur in taxis which have an important share in transportation along with the dissemination process of electric vehicles (EV). Therefore, charging infrastructure problem must be solved for electric taxis (ETs). It is aimed to solve the site selection problem of electric taxi charging station (ETCS) for Istanbul, a metropolitan city in this study. A four-step solution approach is developed: (i) determination of six main and 25 sub- criteria, (ii) weighting of evaluation criteria using fuzzy Analytic Hierarchy Process (fuzzy AHP), (iii) Performing spatial analysis of criteria via Geographical Information System (GIS) and assigning of ETCSs, (iv) ranking of assigned ETCSs using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) accordance with performance values. The results show that, in Istanbul, it is seen that the southeast part of the European side and the southwestern part of the Anatolian side are more suitable for ETCS. The proposed methodology approach provides a more accurate solution for high degree of uncertainty problems.
Photovoltaic Mobile Charging Station for Green Infrastructure: A Data-Driven Case Study
(Elsevier, 2025) Kaya, Omer
In this study, it is aimed to establish photovoltaic-based charging stations for electric micro mobility vehicles (EMMCS). A data-driven optimization approach is presented for the design and site selection solution of EMMCS. This approach consists of a three-step solution methodology. First, 18 criteria affecting the site selection of micro mobility vehicles were determined. The Analytical Hierarchy Process (AHP) was used to calculate the priority values of these criteria, and a new formulation was created by analysing them with six different machine-learning algorithms to increase consistency. Secondly, spatial analyses were conducted via Geographic Information Systems (GIS) to identify the most suitable areas for EMMCS, and a suitability map was obtained. Thirdly, the station assignment process analysis was carried out with Mixed-Integer Programming (MIP). It was recommended to establish 75 stations. The sample design of EMMCS was made based on photovoltaic (PV), and the Alternative ranking technique based on adaptive standardized intervals (ARTASI) approach was adopted to assess the performance of the alternatives. It is observed that EMMCS-8, 9, 31, and 25 have the highest construction priority. All these processes were implemented as a case study and four distinct service classes were defined based on the real- world scenario. To the best of the authors' knowledge, this is the first study in which both the site selection and siting problems of PV-based stations are solved together.
Site Selection for EVCS in Istanbul by GIS and Multi-Criteria Decision-Making
(Pergamon-Elsevier Science Ltd, 2020) Kaya, Omer; Tortum, Ahmet; Alemdar, Kadir Diler; Codur, M. Yasin
Considering the depletion of fossil fuels and the environmental impact of transport, reducing the use of such fuels is a globally accepted priority. Thus, when moving towards alternative energy types, the first will undoubtedly be electrical energy. In order to accelerate and contribute to this process, electric vehicles (EV) must be preferred over conventional motor vehicles. However, there are various problems associated with the use of EVs, such as range and recharge status. Optimal planning of electric vehicle charging stations (EVCS) is a solution to these problems. For this purpose, parameters affecting EVCS locations have been determined in the paper. Considering these parameters and the current EVCS locations, the most suitable alternative EVCS locations were identified using Geographical Information Systems (GIS). Both the current and alternative EVCS locations were evaluated by Analytic Hierarchy Process (AHP), Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE), and VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) from multi-criteria decision-making (MCDM) methods. The results show that, in Istanbul, the southeast of the European side and the southwest of the Anatolian side were most suitable for EVCS.
Turkey Railway Transport History and Policies
(City Net Scien Res Ctr Ltd-belgrade, 2018) Kaya, Omer; Kuskapan, Emre; Alemdar, K. Diler; Codur, M. Yasin; Atalay, Ahmet
The railways constructed and operated during the Ottoman Empire period were realized with the external capital that foreign entrepreneurs execute. Humanitarian Anatolia was introduced in 1856, 33 years after the first use of steam locomotives in the world. The total length of the railway network transferred to the Republic of Turkey, founded in 1923, it is 4,136 kilometers from the Ottoman Empire. During the period of 1923-1950, when railway transportation was considered as a state policy, a total of 3,764 kilometers of railways were built, average of 139 kilometers per year. Railways in this period were considered as a modernization project with all social aspects surrounding development and reconstruction. Due to seasonal problems, the railway was abandoned from 1950 to 2000. In these years when a recession period experienced, railways were completely neglected and only 945 kilometers of railways were built. Important investment projects to be put into practice after 2000 were planned and investment projects on railways were determined. Between 2004 and 2016, a total of 1,805 kilometers of railways were built an average of 138 kilometers per year. Currently, 4,053 km of railway is under construction. The studies that the country have carried out by focusing on the 2023 goals are now giving positive results. Efforts to increase the length of the railway network are under construction. Integration of the railway network with other transport systems must be ensured. It is aimed to reach the desired levels in railway freight and passenger transportation. Therefore, the study has presented suggestions about the improvement and development of Turkish railways and country policies.