In this research, the mechanical properties of lightweight mortars containing different percentages of additional powder materials has been investigated using response surface methodology (RSM). Box–Behnken design, one of the RSM techniques, was used to study the effects of silica fume content (5, 10, and 15%), vermiculite/cement (V/C) ratio (4, 6, and 8), and temperature (300, 600, and 900 °C) on the ultrasonic pulse velocity (UPV), bending strength, and compressive strength of lightweight mortars. Design expert statistical software was accustomed to determining and evaluating the mix-design of materials in mortar mixtures and temperature effect on mortars. After preliminary experimental research of the relationships between independent and response variables, regression models were built. During the selection of the model parameters, F value, p-value, and R² values of the statistical models were taken into account by using the backward elimination technique. The results showed a high correlation between the variables and responses. Multi-objective optimization results showed that the critical temperatures for different levels of silica fume (5–10–15%) were obtained as 371.6 °C, 306.3 °C, and 436 °C, respectively, when the V/C ratio kept constant as 4. According to the results obtained at high desirability levels, it is found that the UPS values varied in the range of 2480–2737 m/s, flexural strength of 3.13–3.81 MPa, and compressive strength of 9.9–11.5 MPa at these critical temperatures. As a result of this research, RSM is highly recommended to evaluate mechanical properties where concrete includes some additional powder materials and was exposed to high temperature.

Autonomous vehicles (AVs) are increasingly recognized for their potential to enhance urban traffic systems, particularly in traffic management and sustainability. This study explores AV integration into urban networks, focusing on transitions of control (ToC) and dedicated lane (DL) applications at varying AV penetration rates. Through simulations, various scenarios reveal the complex interactions between AVs and human-driven vehicles in mixed traffic conditions. The findings show that DLs can reduce local density, occupancy, and time loss by 5–35%, while improving travel time reliability by 15–25%. On an urban scale, DLs generally enhance traffic flow and reduce emissions, though the effects of ToC vary based on traffic conditions and AV automation levels. At lower AV penetration rates, ToC can lead to increased travel times and up to a 10% decline in traffic performance due to unpredictable human driver behavior during control transitions. The results highlight that DLs can significantly improve traffic flow, travel time reliability, and emissions, thereby contributing to sustainable urban mobility. However, the impacts of ToC are more complex, depending on specific traffic conditions and AV automation levels. This study emphasizes the importance of well-designed ToC and DL applications to optimize AV integration and support a balanced, sustainable future for urban mobility.

Bu çalışmada atık kömür katkılı modifiye bitüm kullanılarak Marshall tasarımı ile hazırlanmış asfalt betonu numunelerinin performans karakteristikleri deneysel tasarım yöntemlerinden Merkezi Kompozit Tasarım (MKT) ve Geri Yayılımlı Yapay Sinir Ağı (YSA) modeli kullanılarak tahmin edilmiştir. Her iki modelin tahmin ettiği performans değerleri karşılaştırılmıştır. MKT yönteminin optimum olarak belirlediği koşullarda doğrulama deneyleri gerçekleştirilmiştir. Ayrıca optimum deney koşulları YSA giriş parametresi olarak tanımlanmış ve ağın ürettiği çıktılar ile doğrulama deneyi sonuçları % 95 güven aralığının alt ve üst limitleri arasında incelenmiştir. MKT ve YSA modellerinin yanıt değişkenleri üzerindeki tahmin değerleri sırası ile %84.8 – 94.3 – 89.65 – 47.1 olarak elde edilmiştir. Kullanılan modeller karşılaştırıldığında MKT ve YSA tahminlerinin tamamının, doğrulama deney sonuçlarının ise %91.67 nin belirlenen güven aralıklarında kaldığı gözlemlenmiştir. Kullanılan her iki yöntemin ürettiği çıktılar sayesinde Marshall tasarımı performans değerlerinin belirlenmesi için üretilmesi gereken numune sayılarının azalacağı düşünülmüştür. Böylece zaman tasarrufu ve ekonomik kazançların sağlanabileceği belirlenmiştir.

Limited public awareness and insufficient parking spaces result in the conscious or unconscious occupation of disabled parking by other drivers. According to the law on traffic penalties, violation of disabled parking is punishable by penalty and driving reputation points. However, it is only possible to control and implement this law under ideal conditions. This study describes in detail the Disincentive Disabled Parking System (DDPS), a distinctive design, planned in order to control disabled parking and to allow the implementation of penal sanctions in case of violation and the algorithm for the system is presented. The design is modeled with Arduino UNO, ultrasonic distance sensor, Radio Frequency Identification (RFID), LCD screen and various connection elements. The performance of the system is tested with three different scenarios. It is observed that system performs successfully for all three, with a 76% accuracy. The results are discussed and ways of improvement are indicated.

This chapter critically examines how Autonomous Vehicles (AVs) and Urban Air Mobility (UAM) fit within Sustainable Urban Mobility (SUM). It argues that current SUM policies have reached an impasse and that AVs and UAM should not be seen as automatic or inherently sustainable solutions. Left lightly regulated, these technologies risk inducing extra travel, worsening congestion, and accelerating urban sprawl. To counter this, the chapter proposes a proactive, multi-layered governance framework built on three pillars. First, physical integration, requiring AVs and UAM to operate through Multimodal Mobility Hubs so they reinforce, not replace, mass transit. Second, digital integration, treating operational data as a public resource, using the Mobility Data Specification (MDS) for oversight, and embedding land-use and noise rules into Unmanned Aircraft System Traffic Management (UTM). Third, legal and economic governance, relying on adaptive regulation, open sandboxes, and pricing tools that discourage empty or low-occupancy trips while rewarding shared, transit-linked fleets.

This paper examined the impact of geometric irregularities on the intersection capacity at traffic circles. A new empirical capacity relation was proposed to predict the capacity of the traffic circles as a function of geometric elements, exit and circulating flows. Within this scope, first, the relationship between the vehicles entering from the minor approach and the circulating flow from the turning movement in the traffic circle was examined based on the K-Means cluster analysis method. The analysis was created in accordance with an exponential relationship between entry and circulating flow. Second, two clusters were selected by the partial least squares regression method to improve the model’s effectiveness. Lastly, to validate the model, “leave-one-out” cross-validation was used to select the components that maximize the model’s predictive ability. The results show that geometric parameters of a traffic circle create different effects on capacity, especially in different circulating flow conditions.