Faculty Publications
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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 Visualization and Assessment of the Effect of Roadworks on Traffic Congestion Using AVL Data of Public Transit(Springer Nature, 2022) Harsha, H.; Mulangi, R.H.; Kulkarni, V.Congestion-free movement of traffic during peak hours in urban areas is rarely witnessed nowadays. Several factors are responsible for traffic congestion, and a large amount of reliable data is necessary to investigate them. In this study, we investigated the effectiveness of automated vehicle location (AVL) data of public transit in evaluating the effect of route diversion due to roadworks on traffic congestion. The public transit vehicle data from Mysore intelligent transport system were used for the purpose. In the preliminary analysis, the spatiotemporal variations in the speed data of public transit were visualized using spatiotemporal speed plots. A comparison study of traffic states in an urban street and an arterial road was conducted using a visualization tool. The data from Inner Ring Road of Mysore city were used to evaluate the effect of roadworks on traffic congestion. The road links of Inner Ring Road were evaluated for two scenarios: normal scenario and route diversion scenario. The results revealed that the spatiotemporal visualization technique can be used to diagnose the changes in traffic congestion, especially near intersections and bus stops. It is concluded that the AVL data from public transit buses proves to be a potential data source for traffic state prediction and evaluation of traffic congestion. © 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.Item Application of Public Transit AVL Data for Evaluation of Delay Variability(Institute for Transport Studies in the European Economic Integration, 2023) Harsha, M.M.; Mulangi, R.H.; Panditharadhya, B.J.The travel time is the significant factor in evaluating efficiency and performance of public transit system. A greater percentage of travel time is accounted by bus stop delays which depends on passenger count, bus stop characteristics, traffic condition, bus performance, etc. Many of the Indian transit agencies store the passenger details stage wise not stop wise, which makes it difficult to evaluate delay variability at bus stop level. In this connection, Automatic Vehicle Location (AVL) data from Intelligent Transport System (ITS) implemented at Mysore, India is considered for evaluating bus stop delay variability. The collected data is used for estimating delay at five stops by adopting trajectory-based formulation. The probability distributions have been utilized to model the variability in delay. The performance has been analysed using Kolmogorov-Smirnov (KS) test. The daily variability of delay at bus stops has been evaluated using Coefficient of Variation (COV). The results of the performance evaluation of delay distributions show that the Generalized Extreme Value (GEV) distribution is the best descriptor of the delay variability in terms of accuracy, robustness, and survival capacity. In the absence of passenger data collection systems, method of evaluation of delay using AVL data presented in this study is helpful. © 2023 Institute for Transport Studies in the European Economic Integration. All rights reserved.