Rishav Sen is a graduate student and a Russel G. Hamilton Scholar in the Department of Electrical Engineering and Computer Science at Vanderbilt University. He completed his Undergraduate in Electronics and Communication from the Heritage Institute of Technology in August, 2020 and had been working as a Software Engineer before starting his Graduate studies.

Rishav Sen Publications

1. R. Sen, T. Tran, S. Khaleghian, M. Sartipi, H. Neema, and A. Dubey, BTE-Sim: Fast simulation environment for public transportation, 2022 IEEE International Conference on Big Data, 2022.
   Bibtex Abstract PDF

   @article{sen2022,
     author = {Sen, Rishav and Tran, Toan and Khaleghian, Seyedmehdi and Sartipi, Mina and Neema, Himanshu and Dubey, Abhishek},
     title = {BTE-Sim: Fast simulation environment for public transportation},
     year = {2022},
     isbn = {},
     publisher = {IEEE},
     address = {},
     url = {},
     booktitle = {2022 IEEE International Conference on Big Data},
     pages = {},
     numpages = {8},
     keywords = {public transit, fast traffic simulation, model integration, data processing, road speed calibration},
     location = {},
     series = {}
   }
   

   The public commute is essential to all urban centers and is an efficient and environment-friendly way to travel. Transit systems must become more accessible and user-friendly. Since public transit is majorly designed statically, with very few improvements coming over time, it can get stagnated, unable to update itself with changing population trends. To better understand transportation demands and make them more usable, efficient, and demographic-focused, we propose a fast, multi-layered transit simulation that primarily focuses on public transit simulation (BTE-Sim). BTE-Sim is designed based on the population demand, existing traffic conditions, and the road networks that exist in a region. The system is versatile, with the ability to run different configurations of the existing transit routes, or inculcate any new changes that may seem necessary, or even in extreme cases, new transit network design as well. In all situations, it can compare multiple transit networks and provide evaluation metrics for them. It provides detailed data on each transit vehicle, the trips it performs, its on-time performance and other necessary factors. Its highlighting feature is the considerably low computation time it requires to perform all these tasks and provide consistently reliable results.

2. R. Sen, A. K. Bharati, S. Khaleghian, M. Ghosal, M. Wilbur, T. Tran, P. Pugliese, M. Sartipi, H. Neema, and A. Dubey, E-Transit-Bench: Simulation Platform for Analyzing Electric Public Transit Bus Fleet Operations, in Proceedings of the Thirteenth ACM International Conference on Future Energy Systems, New York, NY, USA, 2022, pp. 532–541.
   Bibtex Abstract DOI PDF

   @inproceedings{rishav2022eEnergy,
     author = {Sen, Rishav and Bharati, Alok Kumar and Khaleghian, Seyedmehdi and Ghosal, Malini and Wilbur, Michael and Tran, Toan and Pugliese, Philip and Sartipi, Mina and Neema, Himanshu and Dubey, Abhishek},
     title = {E-Transit-Bench: Simulation Platform for Analyzing Electric Public Transit Bus Fleet Operations},
     year = {2022},
     isbn = {9781450393973},
     publisher = {Association for Computing Machinery},
     address = {New York, NY, USA},
     url = {https://doi.org/10.1145/3538637.3539586},
     doi = {10.1145/3538637.3539586},
     booktitle = {Proceedings of the Thirteenth ACM International Conference on Future Energy Systems},
     pages = {532–541},
     numpages = {10},
     keywords = {model-integration, cyber-physical systems, co-simulation, powergrid simulation, traffic simulation},
     location = {Virtual Event},
     series = {e-Energy '22}
   }
   

   When electrified transit systems make grid aware choices, improved social welfare is achieved by reducing grid stress, reducing system loss, and minimizing power quality issues. Electrifying transit fleet has numerous challenges like non availability of buses during charging, varying charging costs and so on, that are related the electric grid behavior. However, transit systems do not have access to the information about the co-evolution of the grid’s power flow and therefore cannot account for the power grid’s needs in its day-to-day operation. In this paper we propose a framework of transportation-grid co-simulation, analyzing the spatio-temporal interaction between the transit operations with electric buses and the power distribution grid. Real-world data for a day’s traffic from Chattanooga city’s transit system is simulated in SUMO and integrated with a realistic distribution grid simulation (using GridLAB-D) to understand the grid impact due to transit electrification. Charging information is obtained from the transportation simulation to feed into grid simulation to assess the impact of charging. We also discuss the impact to the grid with higher degree of transit electrification that further necessitates such an integrated transportation-grid co-simulation to operate the integrated system optimally. Our future work includes extending the platform for optimizing the charging and trip assignment operations.