Faculty Publications
Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736
Publications by NITK Faculty
Browse
9 results
Search Results
Item The calibration of vehicle and pedestrian flow in mangalore city using PARAMICS(WITPress marketing@witpress.com, 2014) Prusty, S.K.; Phadnis, R.; Kunal, R.P.This paper presents a traffic simulation approach for evaluating the pedestrian behaviour by developing a model which includes pedestrians in a vehicular micro-simulation model i.e. PARAMICS that provides a default mechanism for simulating pedestrian movements. This approach is demonstrated by using a case study of a signalized intersection having large pedestrian flow interacting with large vehicular flow in the city of Mangalore, India. In this paper pedestrian behaviour is calibrated with pedestrian speed flow models by defining pedestrians as vehicles. This work provides different methods for evaluating policies that effect both pedestrian and vehicle flow. In this work different critical factors that affect the pedestrian and vehicle flow are considered (i.e. Vehicle queue discharge rate, Pedestrian queue discharge rate, Pedestrian gap acceptance, Pedestrian speed etc.) and finally the network was coded in PARAMICS. The major parameters defined of the driving behaviour that control the car-following behaviour, lane changing behaviour, lateral position and driver reaction to traffic lights are considered and calibrated in PARAMICS. After calibration and validation of pedestrian and vehicle flows the difference between the simulated and observed data were analysed. The high variability in data sets confines the simulation resulting in a constant queue discharge rate at flows approaching saturated conditions. This work finally concludes that PARAMIC'S car-following algorithm is very much helpful in reproducing vehicle and pedestrian flow in complex as well as heterogeneous urban traffic. Application of this car-following algorithm demonstrated by calibrating in PARAMICS will be very useful in predicting known pedestrian speed-flow relationship. © 2014 WIT Press.Item Study on Travel Time Characteristics of Hubli-Dharwad Bus Rapid Transit System in Comparison with Heterogeneous Traffic Lane(Springer Science and Business Media Deutschland GmbH, 2022) Halyal, S.; Mulangi, R.H.; Harsha, M.M.; Laddha, H.Bus Rapid Transit System, which is also known as BRTS, is a very effective transit system in terms of travel time reduction. It has advantages compared to conventional road-based public transport like dedicated lane and pre-board fare collections. In the current study, performance-based travel time characteristics like travel time and travel speeds are evaluated by conducting the speed and delay survey for the BRT buses and private vehicles separately. The survey was performed by moving the car observation method to find out travel time and respective delays that are currently hampering the operations. Speed and delay survey for BRT buses was performed through the manual observation by travelling in the bus. Based upon the study, it has been found that there is a positive side effect of a dedicated corridor on the operation of BRTS buses, as obtained trial running speed values are almost very near to measured free-flow speed values on the selected study corridors. Meanwhile, it has been observed that the BRTS bus operation has faced many delays due to bus bunching, dwell time at the stations and delays at the intersections but delays occurring at the stations have contributed major proportion in the total delay. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.Item A Two-Class Continuum Traffic Flow Model Considering the Disordered Behavior at Nodes(Springer Science and Business Media Deutschland GmbH, 2024) Nair, P.; Abhiram Naidu, M.N.; Sreekumar, M.A peculiar feature of smaller vehicles in multi-class disordered traffic flow is higher maneuverability and lower time of travel. The smaller vehicles can move through the gaps between larger vehicles and reach the downstream end faster. Such features of smaller vehicles contradict traditional concepts of traffic flow such as First In First Out and car following theory. On account of the distinctive features of smaller vehicles in multi-class disordered traffic stream, a macroscopic model is developed for urban corridor incorporating the two-wheeler specific features. The model captures the overtaking and creeping behavior of two-wheelers under congested conditions. The study formulates a multi-class continuum model by combining the link and node model. The link model formulated in this study comprises the fundamental relations of traffic flow with the concept of traversable distance incorporated in the equilibrium speed function to capture the two-wheeler dynamics. The output of the link model is used as input to the nodes, and node model is formulated by defining the supply and demand functions based on the type of intersection. The two-wheeler specific behavior at the intersections is reproduced through the queue formation and dissipation during congestion by simulating the traffic stream under varying external conditions. For this, the study presents four test cases to interpret the typical creeping behavior of two-wheelers at signalized and unsignalized intersections. The difference in class-wise travel time is computed, and it is observed that the travel time and delay of two-wheelers is lesser than that of cars even in congested conditions. The model is also used to demonstrate the typical bus bunching problem at intersections. The study emphasizes on the necessity for an extensive representation of two-wheeler specific features at intersections. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.Item 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.Item 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 PressItem 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.Item Systematic study on deep learning-based plant disease detection or classification(Springer Nature, 2023) Sunil, C.K.; Jaidhar, C.D.; Patil, N.Plant diseases impact extensively on agricultural production growth. It results in a price hike on food grains and vegetables. To reduce economic loss and to predict yield loss, early detection of plant disease is highly essential. Current plant disease detection involves the physical presence of domain experts to ascertain the disease; this approach has significant limitations, namely: domain experts need to move from one place to another place which involves transportation cost as well as travel time; heavy transportation charge makes the domain expert not travel a long distance, and domain experts may not be available all the time, and though the domain experts are available, the domain expert(s) may charge high consultation charge which may not be feasible for many farmers. Thus, there is a need for a cost-effective, robust automated plant disease detection or classification approach. In this line, various plant disease detection approaches are proposed in the literature. This systematic study provides various Deep Learning-based and Machine Learning-based plant disease detection or classification approaches; 160 diverse research works are considered in this study, which comprises single network models, hybrid models, and also real-time detection approaches. Around 57 studies considered multiple plants, and 103 works considered a single plant. 50 different plant leaf disease datasets are discussed, which include publicly available and publicly unavailable datasets. This study also discusses the various challenges and research gaps in plant disease detection. This study also highlighted the importance of hyperparameters in deep learning. © 2023, The Author(s), under exclusive licence to Springer Nature B.V.Item A dynamic traffic assignment framework for policy analysis in cities with significant share of two-wheelers(Elsevier Ltd, 2024) Chapala, S.B.K.; Nair, P.; Sreekumar, M.; Bhavathrathan, B.K.High maneuverability of motorized two-wheelers amidst vehicles of bigger size and different dynamics invalidates FIFO to traverse through the gaps between other vehicles for faster mobility. The failure of existing dynamic traffic assignment frameworks with multi-class conditions to capture this behaviour results in inaccurate routing. The study proposes a simulation based two-class dynamic traffic assignment framework comprising of two-wheeler specific behaviour. These features when incorporated in the framework will add to the utility of the traditional dynamic traffic assignment framework in travel time prediction and planning level applications and is therefore relevant to regions with significant share of two-wheelers. The study gives a clear view of the effect of two-wheeler specific features on the route choice behaviour based on the dynamic travel time. The results of the study shows that there occurs an unintentional separation of vehicle classes during congestion; this effect can be utilized for a two-wheeler specific policy implication for congestion management in cities. The proposed framework can be employed in identifying the optimal provision of exclusive two-wheeler lanes. It is also observed that the provision of exclusive lanes may sometimes be counterproductive. © 2023Item Towards Sustainable Transport: An Analysis of Urban Mobility in Hyderabad, Telangana Using Uber Movement Data(Budapest University of Technology and Economics, 2025) Kuchu, J.; Tatipamula, S.; Ankam, C.; Birukuri, N.Cities worldwide face traffic congestion, challenging sustainable development and requiring insight into its dynamics, dispersion, and stability. Effective traffic management is pivotal for fostering sustainable urban mobility and enhancing quality of life. Leveraging Uber movement data, this study examines travel times and speeds across Hyderabad over a four-year span from 2016 to 2019. Congestion and friction indices from travel time matrices, along with network analysis, gauge urban accessibility, revealing similar magnitudes of Congestion and Travel Time Delay Transition Indices for inbound and outbound traffic within specific intervals. Notably, there is an inverse proportional relationship between these two indices. The Congestion Index values indicate that most zones experience significant traffic jams, while the Travel Time Delay Transition Index was calculated to affirm its inverse relationship with the Congestion Index. Employing fractal geometry, the study delves into the spatial complexity of the network and its correlation with urban growth parameters, contributing to sustainable urban planning efforts. Furthermore, the fractal dimension value obtained from the Mass-Radius method is 1.6955, with a correlation coefficient of 0.99, indicating a high degree of linearity between the road network and friction index. Results underscore the intricate interplay between traffic congestion, macroeconomic factors, and urban form, highlighting the imperative of integrating sustainability principles into transportation policies. By leveraging readily available Uber movement data, this research provides a comprehensive assessment of citywide traffic conditions, offering valuable insights for crafting sustainable transportation management strategies aimed at mitigating congestion and promoting equitable access to mobility. © 2025 Budapest University of Technology and Economics. All rights reserved.