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Item Delay Variability Analysis at Intersections Using Public Transit GPS Data(Springer Science and Business Media Deutschland GmbH, 2023) Lal, A.; Mulangi, R.H.; Harsha, M.M.India is competing with the fastest-growing countries in the world in terms of urbanization and development. Rapid urbanization and motorization have led to congestion in urban roads in India. Delay forms a significant part of congestion. It is necessary to analyze variability in delay for mitigation of traffic congestion. In recent years, GPS data has emerged as a novel data source for traffic state monitoring and analysis due to its better accuracy, coverage, and accessibility. However, little work has been done for control delay estimation especially in Indian traffic condition. In this paper, an attempt has been made to estimate control delay at selected intersections in Mysore city using GPS data from transit buses. A vehicle trajectory-based formulation is adopted for the estimation of delay. The results are fitted to statistical distributions to analyze variability in delay. Kolmogorov- Smirnov (K-S) test for goodness of fit is used to estimate best fitting distribution. Generalized extreme value (GEV) distribution is found to best-fit delay in terms of fitting performance, robustness, and accuracy. The performance analysis indicates greater variability in delay during morning and evening peak hours. Successful estimation of delay variability allows for the analysis of traffic state at various intersections, thus paving the way for effective congestion mitigation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item Analysis of Bus Stop Delay Variability Using Public Transit GPS Data(Springer Science and Business Media Deutschland GmbH, 2023) Ayana, H.; Mulangi, R.H.; Harsha, M.M.Travel time is considered as a direct measure of the efficiency and service reliability of a public transit system and increased travel time is contributed by delays at bus stops. Delay at bus stops affects the efficiency of bus operations and the level of service of public transportation. Day-to-day delay variability decreases passenger confidence in perceived reliability, causing uncertainty in making travel decisions. Many research works have been carried out to find delays at bus stops, but there are very few studies about the delay at bus stops in India using automatic vehicle location (AVL) data. In the present study, an attempt has been made to analyze delays at various bus stops in Mysore city using vehicle trajectory-based formulation based on AVL data collected from the Mysore Intelligent Transportation System (ITS). Delay variability has been analyzed using the coefficient of variation (COV) and also by fitting various probability distributions to the data, since distribution fitting helps in estimating the pattern of delay variability. The goodness of fit is tested by the Kolmogorov–Smirnov (KS) test. The results suggest that bus stops in the commercial area face more variability than the bus stops in residential areas. By fitting various distributions to delay data, it was observed that the performance of the generalized extreme value (GEV) distribution in fitting the data is better than other distributions. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.