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375 results on '"Vanajakshi, Lelitha"'

1. DSRC-Based Bus Trajectory Analysis and Prediction Near Signalized Intersection

Author

Chandrahasan, Aswathi, Jain, Aayush, Vanajakshi, Lelitha, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Dhamaniya, Ashish, editor, Chand, Sai, editor, and Ghosh, Indrajit, editor

Published
2024
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2. Calibration of Microscopic Traffic Simulation for Signalized Intersections Under Heterogeneous Traffic Conditions

Author

Katkar, Rushikesh, Venugopal, Anagha, Saikrishna, Chithra A., Vanajakshi, Lelitha, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Dhamaniya, Ashish, editor, Chand, Sai, editor, and Ghosh, Indrajit, editor

Published
2024
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6. Characterisation and Prediction of Motorised Three Wheelers Travel Time in Urban Roadways

Author

Kundu, Durba, Mahour, Hemant, Bharathi, Dhivya, Vanajakshi, Lelitha, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Devi, Lelitha, editor, Errampalli, Madhu, editor, Maji, Avijit, editor, and Ramadurai, Gitakrishnan, editor

Published
2023
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7. Platoon and Red Light Violation Detection Using Image Processing

Author

Muthurajan, Bharathiraja, Sudheer, Sidharth, Ram, Bhargav, Vanajakshi, Lelitha, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Devi, Lelitha, editor, Errampalli, Madhu, editor, Maji, Avijit, editor, and Ramadurai, Gitakrishnan, editor

Published
2023
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8. Comparison of Delay Estimation Techniques for Advanced Traffic Management

Author

Renju, P. B., Navali, Nitin, Vanajakshi, Lelitha, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Devi, Lelitha, editor, Errampalli, Madhu, editor, Maji, Avijit, editor, and Ramadurai, Gitakrishnan, editor

Published
2023
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9. Application of On-Board Diagnostics (OBD) Data for Vehicle Trajectory Prediction

Author

Navali, Nitin, Vanajakshi, Lelitha, Bullock, Darcy M., di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Devi, Lelitha, editor, Errampalli, Madhu, editor, Maji, Avijit, editor, and Ramadurai, Gitakrishnan, editor

Published
2023
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10. Evaluation of Bus Signal Priority and Dedicated Bus Lane for Efficiency Improvement

Author

Baalaganapathy, V. L., Girijan, Anagha, Vanajakshi, Lelitha Devi, Chilukuri, Bhargava Rama, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Devi, Lelitha, editor, Das, Animesh, editor, Sahu, Prasanta Kumar, editor, and Basu, Debasis, editor

Published
2023
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11. Departure Time Planner for Multimodal Public Transport Network Using Dynamic Programming

Author

Kulkarni, Mihir, Kaur, Arshinder, Vanajakshi, Lelitha, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Devi, Lelitha, editor, Das, Animesh, editor, Sahu, Prasanta Kumar, editor, and Basu, Debasis, editor

Published
2023
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13. Bus Travel Time Prediction: A Lognormal Auto-Regressive (AR) Modeling Approach

Author

Dhivyabharathi, B., Kumar, B. Anil, Achar, Avinash, and Vanajakshi, Lelitha

Subjects
Statistics - Applications
Abstract

Providing real time information about the arrival time of the transit buses has become inevitable in urban areas to make the system more user-friendly and advantageous over various other transportation modes. However, accurate prediction of arrival time of buses is still a challenging problem in dynamically varying traffic conditions especially under heterogeneous traffic condition without lane discipline. One broad approach researchers have adopted over the years is to segment the entire bus route into segments and work with these segment travel times as the data input (from GPS traces) for prediction. This paper adopts this approach and proposes predictive modelling approaches which fully exploit the temporal correlations in the bus GPS data. Specifically, we propose two approaches: (a) classical time-series approach employing a seasonal AR model (b)unconventional linear, non-stationary AR approach. The second approach is a novel technique and exploits the notion of partial correlation for learning from data. A detailed analysis of the marginal distributions of the data from Indian conditions (used here), revealed a predominantly log-normal behavior. This aspect was incorporated into the above proposed predictive models and statistically optimal prediction schemes in the lognormal sense are utilized for all predictions. Both the above temporal predictive modeling approaches predict ahead in time at each segment independently. For real-time bus travel time prediction, one however needs to predict across multiple segments ahead in space. Towards a complete solution, the study also proposes an intelligent procedure to perform (real-time) multi-section ahead travel-time predictions based on either of the above proposed temporal models. Results showed a clear improvement in prediction accuracy using the proposed methods, Comment: 36 pages

Published
2019

14. Simulation-Based Optimization for Heterogeneous Traffic Control

Author

Maripini, Himabindu, Vanajakshi, Lelitha Devi, Chilukuri, Bhargava Rama, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Maurya, Akhilesh Kumar, editor, Maitra, Bhargab, editor, Rastogi, Rajat, editor, and Das, Animesh, editor

Published
2022
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22. Calibration of SUMO for Indian Heterogeneous Traffic Conditions

Author

Sashank, Yadavilli, Navali, Nitin A., Bhanuprakash, Arjuna, Kumar, B. Anil, Vanajakshi, Lelitha, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Arkatkar, Shriniwas S., editor, Velmurugan, S., editor, and Verma, Ashish, editor

Published
2020
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31. Development of a Theoretical Delay Model for Heterogeneous and Less Lane-Disciplined Traffic Conditions

Author

Khadhir, Abdhul, Bhaskar, Ashish, Vanajakshi, Lelitha, and Haque, Md. Mazharul

Subjects
Developing countries, Transportation industry
Abstract

In developing countries with limited or no availability of traffic sensors, theoretical delay models are the most commonly used tool to estimate control delay at intersections. The traffic conditions in such countries are characterised by a large mix of vehicle types and limited or no lane discipline (Heterogeneous, Less Lane-Disciplined (HLLD) traffic conditions), resulting in significantly different traffic dynamics. This research develops a queueing theory-based theoretical delay model that explicitly incorporates HLLD traffic conditions' characteristic features like lack of lane discipline, violation of the First-In-First-Out rule, and a large mix of vehicle types. A new saturation flow-based Passenger Car Equivalent (PCE) estimation methodology to address heterogeneity and a virtual lane estimation approach to address lack of lane-discipline are proposed. The developed model shows 64% lesser error in average control delay estimation compared to the in-practice delay estimation models under HLLD traffic conditions. The developed model is used for signal optimisation under HLLD traffic conditions and reductions of up to 24% in control delay in comparison to the in-practice signal timing approach are observed. The study also highlights the significance of knowing the variation of delay in addition to average delay and presents a simple approach to capture the variation in delay., Author(s): Abdhul Khadhir [1,2]; Ashish Bhaskar (corresponding author) [1,3]; Lelitha Vanajakshi [1,2]; Md. Mazharul Haque [2] 1. Introduction Delay is the primary performance measure used to evaluate and quantify the [...]

Published
2022
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32. List of Contributors to Volume 4

Author

Pinjari, Abdul Rawoof, primary, Karimpour, Abolfazl, additional, Davis, Adam Wilkinson, additional, Adebisi, Adekunle, additional, Ferreira, Amanda Fernandes, additional, Falamarzi, Amir, additional, Kumar, Anil, additional, Yadav, Ankit Kumar, additional, Enam, Annesha, additional, Bhaskar, Ashish, additional, Verma, Ashish, additional, Toriumi, Azusa, additional, Sridhar, Banavar, additional, De Schutter, Bart, additional, Loo, Becky P.Y., additional, Assemi, Behrang, additional, Farooq, Bilal, additional, Morency, Catherine, additional, Shirke, Chaitrali, additional, Bhat, Chandra R., additional, Choudhury, Charisma F., additional, Advani, Chintan, additional, Wu, Chunliang, additional, Garcia, Cristiano P, additional, Chen, Cynthia, additional, Boyce, David, additional, López, David, additional, Ory, David T., additional, L, Deepa, additional, Baker, Douglas, additional, Groth, Sören, additional, Chung, Edward, additional, Frejinger, Emma, additional, Naznin, Farhana, additional, Zhang, Feiyang, additional, de Souza, Felipe, additional, Dias, Felipe F., additional, Sprei, Frances, additional, Witlox, Frank, additional, Chatterji, Gano B., additional, Shivaraman, Gayathri, additional, Sciara, Gian-Claudia, additional, Circella, Giovanni, additional, Asaithambi, Gowri, additional, Yang, Guang, additional, Zhang, H. Michael, additional, Yang, Hai, additional, Zurlinden, Hendrik, additional, Shao, Hu, additional, Kim, Inhi, additional, Banerjee, Ipsita, additional, Pawlak, Jacek, additional, Bourdeau, Jean-Simon, additional, Li, Jia, additional, Xie, Jiani, additional, Ma, Jiaqi, additional, Yao, Jiarong, additional, Freedman, Joel, additional, Gaffney, John, additional, Frejo, José Ramón D., additional, Auld, Joshua, additional, Chen, Jun, additional, Xie, Jun, additional, Geistefeldt, Justin, additional, Khanali, Kamal, additional, Deutsch-Burgner, Kathleen, additional, Wada, Kentaro, additional, Tang, Keshuang, additional, Habib, Khandker Nurul, additional, Chin, Kian Keong, additional, Suzuki, Koji, additional, Goulias, Konstadinos G., additional, Vanajakshi, Lelitha, additional, Weigang, Li, additional, Wang, Lijiao, additional, Wang, Ling, additional, Cheng, Long, additional, Zimmermann, Maëlle, additional, Kashyap, Madhuri, additional, Mesbah, Mahmoud, additional, Salari, Mahmoud, additional, Guerrieri, Marco, additional, Burns, Maria G., additional, Taylor, Michael A.P., additional, Iryo-Asano, Miho, additional, Thomas, Milan Mathew, additional, Balac, Milos, additional, Ha, Min-Ho, additional, Zhang, Ming, additional, Menendez, Monica, additional, Stinson, Monique, additional, Velaga, Nagendra R, additional, McGuckin, Nancy, additional, Iraganaboina, Naveen Chandra, additional, Eluru, Naveen, additional, Verbas, Omer, additional, Wittowsky, Dirk, additional, Lin, Qiheng, additional, Mauro, Raffalele, additional, Benekohal, Rahim F., additional, Paleti, Rajesh, additional, Pendyala, Ram M., additional, Javid, Ramina Jahanbakhsh, additional, Guadamuz, Renato, additional, Javid, Roxana J., additional, Guo, Rui-jun, additional, Li, Ruimin, additional, Wong, S.C., additional, Chang, S.K. Jason, additional, Moridpour, Sara, additional, Raveau, Sebastián, additional, Thyagarajan, Senthilmurugan, additional, Banik, Sharmili, additional, Tanaka, Shinji, additional, Habibi, Shiva, additional, Bekhor, Shlomo, additional, Cao, Shuhan, additional, Chen, Shuyan, additional, Kaplan, Sigal, additional, Balakrishnan, Srijith, additional, Bricka, Stacey G., additional, Boyles, Stephen D., additional, Rashidi, Taha Hossein, additional, Tsubota, Takahiro, additional, Rossi, Thomas F., additional, Hau, Timothy D., additional, Seo, Toru, additional, Kanagaraj, Venkatesan, additional, Alhajyaseen, Wael K.M., additional, Ma, Wanjing, additional, Yang, Wenruifan, additional, Lam, William H.K., additional, Wu, Yao-Jan, additional, Shiomi, Yasuhiro, additional, Murat, Yetis Sazi, additional, Guo, Yi, additional, Pan, Yingjiu, additional, Seo, Young-Joon, additional, Nie, Yu (Marco), additional, Cao, Yumin, additional, Susilo, Yusak, additional, Yang, Zaili, additional, Zhang, Zhanmin, additional, and Li, Zhi-Chun, additional

Published
2021
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35. Optimal Signal Control Design for Isolated Intersections Using Sample Travel-Time Data

Author

Maripini, HimaBindu, Vanajakshi, Lelitha, and Chilukuri, Bhargava Rama

Subjects
Control systems, Sensors, Transportation industry
Abstract

Increased travel times are often observed on urban roads, with signalized intersections being the major bottlenecks. The inability of existing static signal timings in accommodating the actual demand fluctuations could be one of the contributing factors. A traffic-responsive signal control system that changes signal timings according to traffic volume fluctuations may alleviate this problem. However, such problems are conventionally formulated based on the data collected from location-based sensors, which are infrastructure intensive and costly and fail to capture mixed and disordered traffic conditions. Considering these limitations, this paper presents an optimal signal design using sample travel time information collected from mobile data sources such as GPS/Bluetooth/Wi-Fi sensors that work independently of the traffic conditions and are relatively cost-effective. The proposed adaptive signal design minimizes total intersection delay at isolated intersections for every cycle based on the traffic conditions observed in the previous cycle. The mathematical programming-based formulation uses shock waves formed during the red and green phases to estimate optimal-phase durations. Results revealed that the proposed design is capable of handling traffic flow fluctuations without requiring the entire traffic stream data. The system demonstrated that sample data from four probe vehicles per phase is adequate for real-time optimal signal design. Results showed that the proposed model outperformed the existing Webster's signal design procedure with a delay reduction of 11.78% when compared theoretically and 10.41% when implemented in VISSIM., Author(s): HimaBindu Maripini [1]; Lelitha Vanajakshi (corresponding author) [1]; Bhargava Rama Chilukuri [1] 1. Introduction Increasing congestion at signalized intersections has always been a concern for road users as well [...]

Published
2022
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38. A probe-based demand responsive signal control for isolated intersections under mixed traffic conditions.

Author

Maripini, Himabindu, Vanajakshi, Lelitha, and Chilukuri, Bhargava Rama

Subjects
*TRAVEL time (Traffic engineering), *TRAFFIC engineering, *ROAD interchanges & intersections, *TRAFFIC signs & signals, *WAVE analysis, *SHOCK waves, *EDDY current testing
Abstract

The paper presents a model-based demand-responsive traffic control system for mixed traffic conditions using sample travel time data. The model incorporates mixed traffic characteristics such as heterogeneity, limited lane discipline of varied vehicle types, and spatio-temporal traffic dynamics across the width of the road. The methodology includes optimization of intersection performance by accommodating the varying traffic demand through signal timing variables. On validation, the model yielded reliable queue estimates within a close proximity of the actual, ranging from 20 to 40 meters. Upon optimization, the proposed model reduced total intersection delay by 15.42% on an average across 14 cycles, for near-saturated traffic conditions. The optimal green splits are found to be responsive to the varying traffic demand. The proposed system is simple and can be easily implemented in the mixed traffic conditions. [ABSTRACT FROM AUTHOR]

Published
2024
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