Browsing by Author "Mulangi, Raviraj H."

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Application of Electronic Ticket Machine Data for Analysis and Forecasting of Bus Transport Demand
(National Institute of Technology Karnataka, Surathkal, 2019) Cyril, Anila; Mulangi, Raviraj H.; George, Varghese
Passenger demand estimation and forecasting is the fundamental process in public transport planning activity. The optimised operational planning of public transport requires the accurate prediction of the passenger flow on a periodical basis. This research tries to develop an intra-city and inter-city passenger demand estimation model using the data-driven time series approach. In this study, the source of time-series data is the Electronic Ticket Machine (ETM) data, which was not previously explored for passenger demand modelling and forecasting by the researchers. The data used for the study are mainly ETM data from Kerala State Road Transport Corporation (Kerala SRTC). During the analysis of the Kerala ETM data, it was found that the length of intra-city ETM data (for Trivandrum city) available for individual routes varies from 1.5 years to 2 years (2011 to 2013), while inter-city data were not sufficient for timeseries modelling. Therefore, inter-city ETM data of Mangalore division Karnataka State Road Transport Corporation (Karnataka SRTC) was collected for a period of 2013 to 2018, which comprises of a total five-year data, to perform inter-city passenger demand modelling. The intra-city ETM data for Mangalore was not collected since the intracity services are mainly operated by private operators. The private operators have not maintained and stored the ETM data. Since the travel demand is affected by the performance of the public transport system and the bus transport agencies operating the services, this study evaluates the performance of the public transport system and the public transport operator. Therefore, in addition to ETM data, this study also uses data provided by various state and central government agencies. The level of service offered by the public transport system in Trivandrum city, the accessibility of public transport and the performance evaluation of Kerala SRTC was performed to evaluate the present condition of the public transport system in Trivandrum and Kerala SRTC. The performance evaluation of Karnataka SRTC was not performed since the data collected from Karnataka was only for modelling inter-city passenger demand. The Level-of-Service (LoS) was determined using the service level benchmarks set by the Ministry of Urban Development, Government of India. This approach can be used to determine the LoS at the city-level and thus provides a measure for identifying the public transport quality of an urbanvi area. The overall LoS is found to be ‘one’. This indicates that the city has good service coverage, i.e., the public transport ply on most of the corridors in the urban area. The facilities are available wide-spread and are available to the people. This study proposed a methodology for the determination of the accessibility index, which 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. It was observed that the accessibility index in the central area has a higher value and the accessibility values decrease to the periphery of the city. It can be interpreted that the availability of opportunities is higher in the central area, while the number of opportunities is less in other areas. The density of the road network is more towards the city centre, which contributes to higher accessibility values. Also, given that the concentration of population is high in the city centre and the higher number of bus stops, the accessibility index tends to be more in these areas. The performance evaluation of Kerala SRTC was performed using the methodology developed in this study. A weighted Goal Programming (GP) methodology integrated with Analytical Hierarchy Process (AHP) considering the user’s and operator’s perception was used. The operator cost and staff per schedule were the most important variables in regard to the operator, while the safety of travel with respect to user perception. The optimal solution indicates that increasing the accessibility, safety and regularity attract passengers to the public transport that in turn improves the load factor which influences the operators to maximise the fleet utilisation and reduce the cancellation of schedules. The proposed model solution suggests decreasing the staff per bus that will further reduce the staff cost and hence the operating cost. The correlation analysis of ETM data revealed that the relevant temporal pattern in the time-series data (for both intra-city and inter-city) was daily time-series pattern, which was further taken into account during the modelling process. Also, in the data analysis, it was found that 85% of the intra-city data was nonstationary, while 100% of the data for inter-city was nonstationary. The nonstationary data were differenced to make it stationary for further time series analysis. Only 30% of the intra-city data was having seasonal effect while 100% of the inter-city data exhibits seasonality. It is due to the fact that the seasonal variations are not that prevalent in urban travel demand. But intervii city travel is affected by seasonal variations. 95% and 99% of intra-city and inter-city data respectively were non-normal. Therefore, data transformation was required to make these data normal for further analysis. 90% of the intra-city routes were having nonlinearity while all the routes of the inter-city were nonlinear. Hence, nonlinear modelling was required to model it. A methodology to develop an empirical passenger demand estimation model using the data-driven time series approach, employing the capabilities of AutoRegressive Integrated Moving Average (ARIMA) method is developed. The ARIMA model is suitable when dealing with a nonstationary time-series data. But, it cannot be applied to data sets having volatility. When the time-series data has heteroscedasticity, i.e., the variances of error terms are not equal, or some of the error terms are reasonably large, AutoRegressive Conditional Heteroscedasticity (ARCH) models are used for modelling the data sets. When the data have non-standard features like non-normal distribution, and non-linear relationship with lagged values require non-linear AutoRegressive Neural Network (ARNN) modelling methods. The methodology to improve the developed model using the nonlinear ARCH and ARNN methods are determined. It includes a comprehensive methodology for model selection and forecasting, which requires only basic econometric knowledge. The empirical results were compared with the actual value for 30 days and 7 days forecast horizon; and found that the time series model could predict the future observations with an acceptable forecast accuracy. The forecasting performance of developed models are measured using the Mean Absolute Percentage Error (MAPE), and the model goodness of fit is determined using information criteria. The lower value of MAPE represents a good forecast. Lewis (1982) describes MAPE greater than 50% as inaccuracy in forecasting, 20-50% as reasonable forecast, 10-20% as good forecast and less than 10% as highly accurate forecast. In this study, the MAPE values for the 30 days and 7 days forecast were less than 10%. This time-series methodology is useful when there is limited or no information available about the factors affecting the demand. Recommendations have been made to improve the performance of bus operating organisations.
Efficiency and Effectiveness Studies for Performance Evaluation in Public Transport Systems
(National Institute of Technology Karnataka, Surathkal, 2024) P, Praveen Kumar; George, Varghese; Mulangi, Raviraj H.
Bus-based public transport systems are considered to provide affordable means of transport to trip-makers of urban and rural areas. The use of bus transport modes can help reduce traffic congestion and pollution on urban roads. However, the mode share of travel by public transport has witnessed a steep declined since the last 3 decades especially in the large cities with population of 4-8 million and above 8 million (MoUD, 2016). The major reasons for the decline in patronage of public transport modes include non-availability of services, inaccessibility, inadequate comfort and convenience, and poor reliability of services offered. Despite the limitations of the public bus transport system, it is still considered to be a viable mode of transport especially for the economically weaker sections of the society. Public transport undertakings are prone to making losses since these agencies focus on providing mobility to people on commercially viable routes, while providing accessibility and mobility to under-developed remote regions. For example, State Road Transport Undertakings (SRTUs) operating in India accrued a total loss Rs. 113.5 million for the year 2015-16. (MoRTH, 2016). The increasing cost of fuel and spares, increasing cost of labor, resource crunch on fund allocation in the form of subsidies, the lack of sufficient level of transparency in accounting, the rising trend in the use of private vehicles, coupled with the lack of computational tools for performing advanced in-depth analysis on performance-related aspects have affected the functioning of SRTUs leading to financial losses. In view of the need to satisfy the increasing travel demand of urban trip-makers, it is imperative to rejuvenate and promote public transport systems. The scope of the present work involves system evaluation of the performance of State Road Transport Undertakings (SRTUs) in India, with a special emphasis on micro-level performance evaluation of Mysore City Transport Division (MCTD), a part of Karnataka State Road Transport Corporation (KnSRTC). The overall approach adopted in this study for performance evaluation of SRTUs is expected to provide the basic framework for fine-tuning the functioning of similar organizations. These approaches will assist in identifying bottlenecks that need to be streamlined for improving the financial and physical performance of transport undertaking. In the initial phase of the study, a thorough understanding of important performance indicators was attained based on a comprehensive literature review on the use of efficiency and effectiveness measures in transport organizations. This was followed by a questionnaire survey where responses from experts in the field of transport operations, and academicians were elicited in order to rate the importance of various performance criteria in a scale of 1-9. The inputs from the experts were then processed using the AHP and the Fuzzy AHP approaches which gave similar results. Further analyses were performed using another Multi-Criteria Decision Making (MCDM) approaches such as, TOPSIS, and Fuzzy-TOPSIS. A total of nine KPIs were identified for further analysis to evaluate performance of SRTUs at system level. The second phase of the study focused on conducting a system level evaluation of performance of various SRTUs across India with respect to cost efficiency, cost effectiveness, and service effectiveness. Suitable variables that had to be considered to represent the performance in the above-mentioned categories were selected using statistical tools such as the Akaike’s Information Criterion (AIC), and the Bayesian Information Criterion (BIC). The system level analysis of 31 SRTUs operating in Urban, Rural, and Hilly regions of India were carried out using parametric and non-parametric approaches. As part of the parametric approach, the stochastic frontier analysis (SFA) method was adopted, while the Data Envelopment Analysis (DEA) method was adopted as part of the non-parametric approach. Overall results indicated that SRTUs serving hilly regions performed poorly in all the three categories of performance evaluation. The third phase of the study involved the analysis of exogenous variables related to vehicle emissions and accidents as part of the performance evaluation using the DEA approach. In this part of the study, the performance of 25 SRTUs were evaluated for various time periods 2004-05, 2009-10, and 2014-15. The results indicate that CO2-PKM can be effectively used to represent the environmental sustainability of transport organization in the evaluation of SRTUs performance at system level. In the fourth phase of the study, a micro-level analysis related to 82 bus-routes out of a total of 842 routes operated by Mysuru City Transport Division (MCTD), a part of KnSRTC was performed. The QGIS open source software was used to identify the 82 routes based on route-length, and the direction of travel. The parameters representing micro-level performance such as route-length, number of bus-stops, revenue and passengers carried for each route, and so on were obtained using Structured Query Languages (SQL). The elimination of outliers in the database related to the computation of the journey times was performed using a program written in Python. The important variables to be considered in the micro-level analysis related to performance of bus-routes were identified using the principal component analysis (PCA) method, and the recursive feature elimination (RFE) approach using RStudio. The variables identified were then used to analyze the performance
Use of Aluminium Refinery Residue (Red Mud) as A Construction Material for Pavements
(National Institute of Technology Karnataka, Surathkal, 2022) Kudachimath, Nityanand S.; Mulangi, Raviraj H.; Das, Bibhuti Bhusan
A good road network connects remote places and also acts as a feeder system to the other modes of transportation. Manufacturing and the construction industries are in boom with the growing economy of the World. With the growing infrastructure, the demand for conventional construction materials is high, resulting in the depletion of natural resources. In recent days, pavements are subjected to excessive loads due to freight traffic, meanwhile, the depletion of conventional materials has forced people to shift towards alternate construction materials and researchers are in search of alternate materials which can provide the same strength as that of conventional materials. Therefore, waste materials from different industries are tested in laboratories by researchers to replace the natural materials in pavement constructions. Aluminium and steel are produced in very large quantities compared to other metals, these industries also produce the by-products that are either partially utilized or unutilized. Aluminium refinery residue (ARR) with its colour known as red mud, produced from bauxite by Bayer process, its high pH demands huge storage land. The steel and Iron Industries produce ground granulated blast furnace slag (GGBS) as a by-product. In road construction, a large quantity of material is required at the lower layers. In this present work, waste from both industries was used, GGBS makes complex compounds with sodium hydroxide and sodium silicate which increases the strength properties of ARR. The aluminium refinery residue was stabilized with 20, 25, 30% of GGBS, 3, 4, 5% of sodium oxide (Na2O) and silica modulus (Ms) of 0.5, 1.0,1.5 at fixed water to binder ratio 0.25. The compaction test was done on both the treated and untreated aluminium refinery residue to check the maximum dry density and optimum moisture content. The treated samples were cured (for 0,7,28 days) at room temperature. In case of stabilized ii aluminium refinery residue, the maximum strength was achieved at 25% of GGBS and alkali solution consisting of 4% Na2O and 1.0 Ms at both standard and modified Proctor densities. The stabilized aluminium refinery residue with 25% and 30% of GGBS and alkali solution consisting of 4 and 5% of Na2O having 1.0 and 1.5 Ms has passed durability test after 28 days of curing at both densities. The stabilized ARR with 25% of GGBS and alkali solution consisting of 4% of Na2O having Ms of 1.0 at both densities achieved the maximum flexural strength, fatigue life, and the densified structure. The formation of calcium-silicate hydrate and calcium aluminosilicate hydrate structures resulted in a remarkable improvement of compressive strength, flexural strength and fatigue life of the stabilized samples due to the dissolved calcium ions from GGBS, and silicate and aluminium ions from alkali solutions. The design of roads was done by replacing the conventional granular layer with the durable stabilized ARR based on Indian standard codes and the thickness of pavement with stabilised ARR was lesser than the conventional pavement layer. Stress-strain analysis was carried out using IITPAVE software and found that stresses were within the limit. The cost comparison of the pavement made with conventional material and with the proposed GGBS stabilized ARR was carried out and the cost of stabilised pavement layer was nearly same as that of the conventional pavement layer.