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Item Spatiotemporal Speed Characterization of Bus Rapid Transit System(Springer Science and Business Media Deutschland GmbH, 2024) Halyal, S.; Angadi, V.S.; Mulangi, R.H.Performance analysis of an urban transportation system, particularly a bus rapid transit system (BRTS), must report on its operations and dependability. The BRTS performance analysis includes many factors, including speed, directly impacting how the system functions and serves commuters. This study employs an experimental technique on a standardized basis to remark on the performance of the Hubballi–Dharwad BRTS by estimating the corridor's average speed at various spatial and temporal fluctuations. The BRTS route chosen included segregated (exclusive traffic environment) and unsegregated (mixed traffic environment) stretches. The current study primarily employed video graphics-based and manual surveys to collect data on identified spatial and temporal trends at different BRTS bus stations. The primary data required consists of dwell time (DT)-based data at each station, summarizing the total time a bus services a station for a unit of time, signal cycle data, and section speed, which corresponds to the speed of the buses between two BRT bus stations while observing spatial and temporal trends. The acceleration and deceleration rates were calculated using the section speed, followed by the acceleration and deceleration time. The addition of delays, errors, and bus congestion resulted in the average speed of various stretches. The average section speeds then facilitated the average facility speed. The variations in average section speed between stations were graphically presented, both spatially and temporally, which gave the conclusion that there was a higher section speed in the segregated stretch and a lower rate in the unsegregated stretch, followed by a higher speed in the off-peak hours and lower speed in the peak hours. The Level of Service (LOS) was developed for complete study sections considering the average facility speeds with and without the impedance, and the results were compared. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Item Spatiotemporal capacity estimation of bus rapid transit system based on dwell time analysis(King Saud University, 2024) Angadi, V.S.; Halyal, S.; Mulangi, R.H.The performance study of an urban transport system, particularly a Bus Rapid Transit System (BRTS), must report on its operations and reliability. Such study of BRTS comprises numerous facets, including capacity, which directly influences how the system practically operates and serves the commuters. Hubballi-Dharwad Bus Rapid Transit System (HDBRTS) has been operational since 2018. A performance study is necessary to evaluate the performance of HDBRTS, which aids in its upgradation and improvement. The current research uses the experimental technique through an innovative and inspired basis to comment on the HDBRTS's performance by estimating the corridor's operational capacity at different spatial and temporal fluctuations. The selected route of the HDBRTS comprises combined segregated (exclusive traffic environment) and unsegregated (mixed traffic environment) stretches. The current study mainly conducted a video graphics-based survey to acquire the necessary data on identified spatial and temporal trends at various HDBRTS bus stations. The essential data gathered consists of Dwell Time (DT)-based data at each station, summarising the total time a bus takes to serve passengers at a station. DT is inversely proportional to the capacity of the particular bus station, which is related to the Failure Rate (FR). FR values of all the bus stations of the route were analyzed using DT, and then capacity values were calculated at different spatiotemporal patterns. Study results show that the busiest stations of the identified routes with critical DT values have FR values in the range of 1–2%, contradicting previous studies. The variations in the capacity of the stations, both spatially and temporally, were graphically represented with the minimum capacity of the segregated stretch as 36 buses/hr and the unsegregated stretch as 31 buses/hr. Finally, the Level Of Service (LOS) of the chosen study corridor was developed using the K-Means clustering algorithm and validated using the Silhouette Coefficient technique. The silhouette coefficient values obtained range from 0.52 to 0.74, indicating a reasonable structure. © 2023 The Authors