Search Results (2)

Accurate evaluation of the prevailing traffic operations plays an important part in developing sustainable transport systems. This research examines the suitability of the level of service (LOS) criteria developed by the Indian and United States (US) Highway Capacity Manuals (HCM) for heterogeneous and undisciplined traffic streams and proposes new criteria using a data-driven approach. Traffic data were collected from a selected major arterial in Karachi, and fundamental diagrams were developed using these data. These fundamental diagrams and field-collected data were analyzed using the K-mean clustering approach to examine the actual traffic states at various LOS bands used in practice. Associating the field-measured volume-to-capacity ratio with the speed bands used for LOS analysis gives insights into actual traffic conditions at various LOS categories. The research shows that the volume-to-capacity ratio corresponding to the speed range for LOS A is about 0.45, which implies that the heterogeneous traffic moves with comparatively higher speeds despite an increase in traffic volume. The criteria for LOS were developed using the K-mean cluster analysis technique. The proposed values of LOS criteria for speed percentages are significantly higher than those reported in both the HCMs. This research highlights the need to develop separate LOS criteria for heterogeneous and undisciplined traffic for all transportation facilities. The development of such new criteria can provide researchers and engineers with a schematic for the effective and realistic evaluation of local traffic regimes. Full article

Product performance, function, cost, and the level of module generalization are all significantly influenced by product modular design, but different goods require different division indicators and techniques. The purpose of this study is to provide a set of appropriate modular division techniques for FDM 3D printers. This research offers an ecologically friendly module division index and uses module clustering as the module division principle in accordance with the current industrial development trend and the fundamental requirements of FDM 3D printer consumers in the current market. The K-means algorithm is used to use the Jaccard similarity coefficient as the metric of similarity of the DSM clustering process to realize the module division of the FDM 3D printer after studying the function–behavior–structure mapping model of the 3D printer. Additionally, the elbow method–cluster error variance and average contour coefficient evaluation systems were built, respectively, in order to verify the viability of the FDM 3D printer module division method and obtain the best module division results. By analyzing these two systems, it was discovered that when the FDM 3D printer was divided into three modules, the in-cluster error variance diagram obviously had an inflection point, and the average profile coefficient and other modular approaches that need to be adjusted to their respective goods can use this division method as a theoretical foundation and point of reference. Full article