Journal Articles

Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/19884

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Author: search.filters.author.Mulangi, R.H.

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    Use of inclined compound triangular notch-weir to improve discharge range
    (2009) Shivapur, A.V.; Mulangi, R.H.; Govardhan Swamy, H.S.
    The notch-weir having simple geometric shapes is unable to measure small as well as occasional large flows. In such situation compound weirs find application. In the present paper authors have reported their study on the use inclined compound notch-weir consisting of two triangular sections with different vertex angles. The notch plane is placed inclined to the general flow surface in the channel. The general discharge equation has been evolved through the semi analytical cum experimental procedure. Results show a significant improvement in discharging rate compared to normal weir. The lower triangular portion of the notch-weir handles the smaller flow whereas the upper part helps to measures the occasional high flows. Further advantages of the inclined compound weir in reducing afflux near the structure are also discussed. © 2009 Taylor & Francis Group, LLC.
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    Traffic management proposals for Udupi city
    (CAFET INNOVA Technical Society 1-2-18/103, Mohini Mansion, Gagan Mahal Road, Domalguda, Hyderabad 500029, 2011) Mulangi, R.H.; Ravi Shankar, A.U.; George, V.
    Udupi is amongst the most prominent places of pilgrimage in India and is famous for its Lord Krishna and many other deities. It is having population of 1.476 lacks in the year 2002, with floating population 100000 to 200000 per day. In view of growing importance of the Udupi city in the region of Central Business District (CBD), this is an urgent need for a comprehensive approach to tackle the short range and long-range traffic and transportation problems. To study the existing traffic and transportation system and prepare traffic management plan various traffic surveys have been carried out, and alternate proposal have been made. The proposals have been analysed for Level of Service (LOS) along the urban roads and LOS of turning traffic at junctions for next ten years. In present study an attempt is made to provide traffic management for CBD area. © 2011 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved.
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    Traffic characteristics evaluation and traffic management measures: A case study of Dharwad city
    (Bentham Science Publishers B.V. P.O. Box 294 Bussum 1400 AG, 2018) Hanumappa, D.; Mulangi, R.H.; Kudachimath, N.S.
    Traffic problems in the urban areas are increasing at a rapid rate. Engineers, planners or the policymakers are having a tough time in dealing with their multiple constraints for getting the desired solution. Some of the main transportation planning problems are mixed traffic plying on the roads, inadequate parking areas, increasing number of vehicles and road users, the unbalanced pattern of land use with obsolete road system, increasing number of road facilities and environmental pollution. Since in India most of the cities are unplanned, we are only left with an option management of existing infrastructure. In this paper, one such case study is presented in which a detailed traffic management for the city of Dharwad is carried out. © 2018 Hanumappa et al.
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    Bus passenger demand modelling using time-series techniques-big data analytics
    (Bentham Science Publishers B.V. P.O. Box 294 Bussum 1400 AG, 2019) Cyril, A.; Mulangi, R.H.; George, V.
    Background: Public transport demand forecasting is the fundamental process of transport planning activity. It plays a pivotal role in the decision making, policy formulations and urban transport planning procedures. In this paper, public bus passenger demand forecasting model is developed using a novel approach. The empirical passenger demand for a bus depot is modelled and forecasted using a data-driven method. The big data generated by Electronic Ticketing Machines (ETM) used for issuing tickets and collecting fares is sourced as the data for demand modelling. This big data is time indexed and hence has the potential for use in time-series applications which were not previously explored. Objectives: This paper studies the application of time-series method for forecasting public bus passenger demand using ETM based time-series data. The time-series approach used is the four Holt-Winters’ modeling methods. Holt-Winters’ additive and multiplicative models with and without damping have been empirically compared in this study using the data from the inter-zonal buses. The data used in the study is a part of the transaction on ticket sales by Kerala State Road Transport Corporation (KSRTC) maintained at the Trivandrum City depot of an Indian state Kerala, for the period between 2010 and 2013. The forecasting performance of four time-series models is compared using Mean Absolute Percentage Error (MAPE) and the model goodness of fit is determined using information criteria. Conclusion: The forecasts indicate that multiplicative models with and without damping, which better account for seasonal variations, outperform the additive models. © 2019 Cyril et al.
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    Development of a GIS-based composite public transport accessibility index
    (Universidade Federal da Paraiba celso@ct.ufpb.br, 2019) Cyril, A.; Mulangi, R.H.; George, V.
    The increasing interest in sustainable modes of transport such as public transport has triggered the need for evaluation of accessibility to and from the transit service. Accessibility to the transit service determines the service attractiveness and hence better accessibility increases the demand. Although accessibility has been the focus of research in the past few decades, it still remains a concept that has been poorly defined and hence finding a theoretically good and operationally sound measure of accessibility is a challenging task. The objective of this paper is to develop a composite public transport accessibility index using Geographic Information System (GIS) as a case study of an Indian city, Trivandrum. This concept is a spatio-temporal GIS-based public transport accessibility model which includes travel modes of walking and bus transit, travel impedance and service coverage of the transit network. The methodology used in the study is based on the factor that the index should measure the accessibility which comes from proximity to bus stops and land use destinations and the proportion of the population served. © 2019 Journal of Urban and Environmental Engineering (JUEE). All rights reserved.
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    Performance Optimization of Public Transport Using Integrated AHP–GP Methodology
    (Springer Berlin Heidelberg, 2019) Cyril, A.; Mulangi, R.H.; George, V.
    The State Road Transport Undertakings (SRTUs) are the economic providers of mass transport in India. The institutional constraints imposed on the SRTUs result in low productivity and inefficiency. In this fiercely competitive environment, the state-owned public transport industry cannot operate sustainably, showing mediocre performance. With relatively scarce financial resources, high political expectations, and competition between operators, the efficiency and performance of the industry must be improved by optimizing the available resources. In this study, an integrated analytical hierarchy process–goal programming technique considering both operators’ and users’ perceptions is used for performance optimization. The methodology starts with the selection of various performance indicators, considering both operators’ and users’ perceptions. The decision variables are then categorized into user-oriented and operator-oriented. The analytical hierarchy process (AHP), a multicriteria decision-making tool, is then used to evaluate the decision variables and calculate their weights to be used as penalties in goal programming (GP). Pairwise comparison of decision variables on the AHP rating scale was carried out by experts associated with bus transportation and academia. This was used to assign weights to the variables to denote their priority based on their importance. Then, these weights were assigned to the objective function of the GP problem to find a solution that minimizes the weighted sum of deviations from the goal values. As a case study, performance optimization of the Kerala State Road Transport Corporation was undertaken. Twelve decision variables were identified, by taking into account both user and operator perceptions, viz. controllable costs, noncontrollable costs, taxes, staff per bus ratio (fleet operated), safety, accessibility, regularity, load factor, fleet utilization, percentage of dead kilometers to effective kilometers, journey speed, and percentage of cancelled kilometers to scheduled kilometers. The perceived importance of each of these decisive factors from both the users’ and operators’ perspectives was obtained from the experts and prioritized using the AHP. The results indicated that operator cost and staff per schedule were the most important variables for the operators, while safety of travel had the highest weighting according to the users’ perceptions. The optimal solution indicated that increasing the accessibility, safety, and regularity would attract passengers to public transport, which would in turn improve the load factor and influence operators to maximize fleet utilization and reduce cancellation of schedules. Moreover, the solution also suggested that decreasing the staff per bus would further reduce the operating cost. Furthermore, sensitivity analysis was carried out to identify the impact of variations in the decision variables on the performance of the system. The presented method could be used for performance evaluation and optimization of urban rail, metro, and various other public transport systems. © 2019, The Author(s).
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    Impact of Side Friction on Travel Time Reliability of Urban Public Transit
    (Springer Science and Business Media Deutschland GmbH, 2021) Harsha, M.M.; Mulangi, R.H.
    Travel time reliability is the key aspect that indicates the quality of urban public transit service. The studies on travel time reliability of the public transit system in Indian traffic conditions are few. Also, the impact of side friction elements on travel time reliability has not been considered in the previous studies. Hence, the present study aims to quantify the different types of side friction elements and analyse their impact on the travel time reliability of the public bus transit system. The field data consisting of side friction elements, traffic volume, and travel time of public bus transit have been collected and extracted at two different road sections (divided and undivided) in the Mysore city (Karnataka, India) during weekdays and weekends. The data are grouped into static and dynamic side frictions. An approach has been proposed to represent different types of side friction elements with a single index called the Side Friction Index (SFI) using relative weight analysis. Travel time reliability is represented using measures such as Buffer Time Index (BTI), Planning Time Index (PTI), Travel Time Index (TTI) and Reliable Buffer Index (RBI). The impact of side friction on travel time reliability was found to be sensitive to traffic volume, and hence the thresholds for different traffic volume levels have been determined using K-means clustering method. It was observed from relative weight analysis that the static side friction has a higher weightage (0.509 and 0.327 for the undivided road and divided road respectively) than the dynamic side friction elements in describing the variation of travel time. The impact of side friction on reliability measures at different traffic volume levels has been studied and found to have a non-linear (exponential) relationship. The impact of SFI has been observed to be higher on TTI and PTI in comparison with BTI. The study outcomes show that the impact of side friction on TTI and PTI is sensitive to traffic volume, especially at higher traffic volume level and impact of side friction on BTI is less, especially at medium traffic volume level. The inference from the study shows that the impact of side friction elements varies with respect to the type of road (divided and undivided), traffic volume levels, different days of week (weekday and weekend), and different time periods of day. © 2021, Iran University of Science and Technology.
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    Forecasting public transit passenger demand: With neural networks using APC data
    (Elsevier Ltd, 2022) Halyal, S.; Mulangi, R.H.; Harsha, H.
    The implementation of Intelligent Transportation Systems (ITS) as a part of smart mobility is crucial for solving the current problems of the transportation industry. The setting up and maintenance of ITS requires not only the current passenger demand but also the future passenger demand. The future passenger demand can be obtained with time-series forecasting carried out with different techniques. With the advancements in the technological field, modern and more advanced methods of time-series forecasting using deep learning are being preferred over traditional forecasting techniques. However, the research carried out in this regard is quite limited, particularly considering the Indian scenario. Hence this research work focuses on exploring the performance of deep learning forecasting techniques considering the aspects mentioned previously. Here, the forecasting of passenger demand was done with Long Short-Term Memory (LSTM) using the three months Automatic Passenger Counter (APC) data of the Hubballi-Dharwad Bus Rapid Transit System (HDBRTS) as part of a case study. Then the forecasting of passenger demand was also done with Seasonal Autoregressive Integrated Moving Average (SARIMA), and the comparison of the forecasting accuracy of both methods was made using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). Furthermore, to validate the results, novel approach has been adopted for the process, by following some more time-series resampled with different time intervals. Study shows that LSTMs will be used satisfactorily in the traffic conditions of developing counties, for forecasting passenger demand using APC data. Study also provides detailed guiding methodologies of advanced methods of passenger forecasting along with conventional ones. © 2022 World Conference on Transport Research Society
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    Probability distributions analysis of travel time variability for the public transit system
    (KeAi Communications Co., 2022) Harsha, H.; Mulangi, R.H.
    Travel time variability (TTV) plays a significant role in analysing the reliability of public transit system. The research works carried out on travel time variability under Indian traffic conditions are very few and these studies did not analyse the performance of travel time distribution in detail, considering different temporal and spatial aggregations. In this study, travel time variability is analysed using travel time distributions considering different temporal and spatial aggregations. The Automatic Vehicle Location (AVL) data of four transit routes of Mysore City, Karnataka, India are used to evaluate travel time distributions with respect to temporal aggregations (peak period, off-peak period, 60 minutes, 30 minutes and 15 minutes) and spatial aggregations (route level and segment level). The performance of travel time distributions is analysed using the Anderson-Darling (AD) test. The segments with signalised intersections and different land-use types are analysed to evaluate the distribution fit for various conditions. The results of both route and segment level analysis report highest accuracy and robustness values for Generalised Extreme Value (GEV) distribution. The distribution is proved to be superior in describing travel time variability of public transit. © 2021 Tongji University and Tongji University Press
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    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.