Printer Friendly

 2021

  1. R. Sandoval et al., Data driven methods for effective micromobility parking, Transportation Research Interdisciplinary Perspectives, 2021.
  2. R. Sun, Y. Chen, A. Dubey, and P. Pugliese, Hybrid electric buses fuel consumption prediction based on real-world driving data, Transportation Research Part D: Transport and Environment, vol. 91, p. 102637, 2021.
  3. J. Martinez et al., Predicting Public Transportation Load to Estimate the Probability of Social Distancing Violations, in Proceedings of the Workshop on AI for Urban Mobility at the 35th AAAI Conference on Artificial Intelligence (AAAI-21), 2021.
  4. M. Wilbur, P. Pugliese, A. Laszka, and A. Dubey, Efficient Data Management for Intelligent Urban Mobility Systems, in Proceedings of the Workshop on AI for Urban Mobility at the 35th AAAI Conference on Artificial Intelligence (AAAI-21), 2021.
  5. A. Sivagnanam, A. Ayman, M. Wilbur, P. Pugliese, A. Dubey, and A. Laszka, Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service, in Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-21), 2021.
  6. Y. Chen, G. Wu, R. Sun, A. Dubey, A. Laszka, and P. Pugliese, A Review and Outlook of Energy Consumption Estimation Models for Electric Vehicles, Society of Automotive Engineers (SAE) International Journal of Sustainable Transportation, Energy, Environment, & Policy, 2021.

 2020

  1. J. P. Talusan, M. Wilbur, A. Dubey, and K. Yasumoto, On Decentralized Route Planning Using the Road Side Units as Computing Resources, in 2020 IEEE International Conference on Fog Computing (ICFC), 2020.
  2. M. Wilbur, C. Samal, J. P. Talusan, K. Yasumoto, and A. Dubey, Time-dependent Decentralized Routing using Federated Learning, in 2020 IEEE 23nd International Symposium on Real-Time Distributed Computing (ISORC), 2020.
  3. Y. Chen, G. Wu, R. Sun, A. Dubey, A. Laszka, and P. Pugliese, A Review and Outlook of Energy Consumption Estimation Models for Electric Vehicles, in Preprint at Arxiv, 2020.
  4. M. Wilbur et al., Impact of COVID-19 on Public Transit Accessibility and Ridership, in Preprint at Arxiv, 2020.
  5. W. Barbour et al., Data Driven Methods for Effective Micromobility Parking, in Proceedings of the Transportation Research Board Annual Meeting, 2020.
  6. A. Ayman, M. Wilbur, A. Sivagnanam, P. Pugliese, A. Dubey, and A. Laszka, Data-Driven Prediction of Route-Level Energy Use for Mixed-Vehicle Transit Fleets, in 2020 IEEE International Conference on Smart Computing (SMARTCOMP) (SMARTCOMP 2020), Bologna, Italy, 2020.
  7. G. Pettet et al., A Decision Support Framework for Grid-Aware Electric Bus Charge Scheduling , in 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2020.
  8. A. Ayman, A. Sivagnanam, M. Wilbur, P. Pugliese, A. Dubey, and A. Laszka, Data-Driven Prediction and Optimization of Energy Use for Transit Fleets of Electric and ICE Vehicles, ACM Transations of Internet Technology, 2020.

 2019

  1. F. Sun, A. Dubey, J. White, and A. Gokhale, Transit-hub: a smart public transportation decision support system with multi-timescale analytical services, Cluster Computing, vol. 22, no. Suppl 1, pp. 2239–2254, Jan. 2019.
  2. S. Basak, F. Sun, S. Sengupta, and A. Dubey, Data-Driven Optimization of Public Transit Schedule, in Big Data Analytics - 7th International Conference, BDA 2019, Ahmedabad, India, 2019, pp. 265–284.
  3. S. Basak, A. Dubey, and B. P. Leao, Analyzing the Cascading Effect of Traffic Congestion Using LSTM Networks, in IEEE Big Data, Los Angeles, Ca, 2019.