Smart Mobility

Transit Agencies struggle to maintain transit accessibility with reduced resources, changing ridership patterns, vehicle capacity constraints. We have been working for the last several years to design AI-based scheduling systems to solve the problem of allocating vehicles and drivers to transit services, scheduling vehicle maintenance, and electric-vehicle charging, proactive stationing, and dispatch of vehicles for fixed-line service to mitigate unscheduled maintenance and unmet transit demand, aggregating on-demand transit requests, and dispatching and routing on-demand vehicles. Similar to the incident response, the decision support systems face key challenges: environments are non-stationary and difficult to predict due to human factors and complex processes affecting transit demand and traffic as well as unscheduled maintenance and accidents; simulations are expensive and complex as city-scale simulations need to consider millions of individuals and vehicles.

Visit SmartTransit.ai for details on current projects in this area.

Publications in this area

  1. Y. Kim, D. Edirimanna, M. Wilbur, P. Pugliese, A. Laszka, A. Dubey, and S. Samaranayake, Rolling Horizon based Temporal Decomposition for the Offline Pickup and Delivery Problem with Time Windows, in Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI-23), 2023.
  2. M. Wilbur, A. Mukhopadhyay, S. Vazirizade, P. Pugliese, A. Laszka, and A. Dubey, Energy and Emission Prediction for Mixed-Vehicle Transit Fleets Using Multi-Task and Inductive Transfer Learning, in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2021.
  3. R. Sun, R. Gui, H. Neema, Y. Chen, J. Ugirumurera, J. Severino, P. Pugliese, A. Laszka, and A. Dubey, Transit-Gym: A Simulation and Evaluation Engine for Analysis of Bus Transit Systems, in Preprint at Arxiv. Accepted at IEEE SmartComp., 2021.
  4. R. Sandoval, C. Van Geffen, M. Wilbur, B. Hall, A. Dubey, W. Barbour, and D. B. Work, Data driven methods for effective micromobility parking, Transportation Research Interdisciplinary Perspectives, 2021.
  5. 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.
  6. 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.
  7. 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.
  8. J. Martinez, A. M. A. Ayman, M. Wilbur, P. Pugliese, D. Freudberg, A. Laszka, and A. Dubey, 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.
  9. F. Tiausas, J. P. Talusan, Y. Ishimaki, H. Yamana, H. Yamaguchi, S. Bhattacharjee, A. Dubey, K. Yasumoto, and S. K. Das, User-centric Distributed Route Planning in Smart Cities based on Multi-objective Optimization, in 2021 IEEE International Conference on Smart Computing (SMARTCOMP), 2021, pp. 77–82.
  10. 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.
  11. J. P. V. Talusan, M. Wilbur, A. Dubey, and K. Yasumoto, Route Planning Through Distributed Computing by Road Side Units, IEEE Access, vol. 8, pp. 176134–176148, 2020.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. M. Wilbur, A. Ayman, A. Ouyang, V. Poon, R. Kabir, A. Vadali, P. Pugliese, D. Freudberg, A. Laszka, and A. Dubey, Impact of COVID-19 on Public Transit Accessibility and Ridership, in Preprint at Arxiv, 2020.
  17. W. Barbour, M. Wilbur, R. Sandoval, A. Dubey, and D. B. Work, Streaming computation algorithms for spatiotemporal micromobility service availability, in 2020 IEEE Workshop on Design Automation for CPS and IoT (DESTION), 2020, pp. 32–38.
  18. 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.
  19. W. Barbour, M. Wilbur, R. Sandoval, C. V. Geffen, B. Hall, A. Dubey, and D. Work, Data Driven Methods for Effective Micromobility Parking, in Proceedings of the Transportation Research Board Annual Meeting, 2020.
  20. S. Shekhar, A. Chhokra, H. Sun, A. Gokhale, A. Dubey, X. Koutsoukos, and G. Karsai, URMILA: Dynamically Trading-off Fog and Edge Resources for Performance and Mobility-Aware IoT Services, Journal of Systems Architecture, 2020.
  21. 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.
  22. 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.
  23. S. Nannapaneni and A. Dubey, Towards demand-oriented flexible rerouting of public transit under uncertainty, in Proceedings of the Fourth Workshop on International Science of Smart City Operations and Platforms Engineering, SCOPE@CPSIoTWeek 2019, Montreal, QC, Canada, 2019, pp. 35–40.
  24. 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.
  25. S. Shekhar, A. Chhokra, H. Sun, A. Gokhale, A. Dubey, and X. D. Koutsoukos, Supporting fog/edge-based cognitive assistance IoT services for the visually impaired: poster abstract, in Proceedings of the International Conference on Internet of Things Design and Implementation, IoTDI 2019, Montreal, QC, Canada, 2019, pp. 275–276.
  26. G. Pettet, S. Sahoo, and A. Dubey, Towards an Adaptive Multi-Modal Traffic Analytics Framework at the Edge, in IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2019, Kyoto, Japan, March 11-15, 2019, 2019, pp. 511–516.
  27. J. P. Talusan, F. Tiausas, K. Yasumoto, M. Wilbur, G. Pettet, A. Dubey, and S. Bhattacharjee, Smart Transportation Delay and Resiliency Testbed Based on Information Flow of Things Middleware, in IEEE International Conference on Smart Computing, SMARTCOMP 2019, Washington, DC, USA, June 12-15, 2019, 2019, pp. 13–18.
  28. M. Wilbur, A. Dubey, B. Leão, and S. Bhattacharjee, A Decentralized Approach for Real Time Anomaly Detection in Transportation Networks, in IEEE International Conference on Smart Computing, SMARTCOMP 2019, Washington, DC, USA, 2019, pp. 274–282.
  29. C. Samal, A. Dubey, and L. J. Ratliff, Mobilytics-Gym: A Simulation Framework for Analyzing Urban Mobility Decision Strategies, in IEEE International Conference on Smart Computing, SMARTCOMP 2019, Washington, DC, USA, 2019, pp. 283–291.
  30. S. Basak, A. Aman, A. Laszka, A. Dubey, and B. Leao, Data-Driven Detection of Anomalies and Cascading Failures in Traffic Networks, in Proceedings of the 11th Annual Conference of the Prognostics and Health Management Society (PHM), 2019.
  31. A. Oruganti, S. Basak, F. Sun, H. Baroud, and A. Dubey, Modeling and Predicting the Cascading Effects of Delay in Transit Systems, in Transportation Research Board Annual Meeting, 2019.
  32. W. Barbour, C. Samal, S. Kuppa, A. Dubey, and D. B. Work, On the Data-Driven Prediction of Arrival Times for Freight Trains on U.S. Railroads, in 21st International Conference on Intelligent Transportation Systems, ITSC 2018, Maui, HI, USA, November 4-7, 2018, 2018, pp. 2289–2296.
  33. F. Sun, A. Dubey, C. Samal, H. Baroud, and C. Kulkarni, Short-Term Transit Decision Support System Using Multi-task Deep Neural Networks, in 2018 IEEE International Conference on Smart Computing, SMARTCOMP 2018, Taormina, Sicily, Italy, June 18-20, 2018, 2018, pp. 155–162.
  34. C. Samal, A. Dubey, and L. J. Ratliff, Mobilytics- An Extensible, Modular and Resilient Mobility Platform, in 2018 IEEE International Conference on Smart Computing, SMARTCOMP 2018, Taormina, Sicily, Italy, June 18-20, 2018, 2018, pp. 356–361.
  35. C. Samal, L. Zheng, F. Sun, L. J. Ratliff, and A. Dubey, Towards a Socially Optimal Multi-Modal Routing Platform, CoRR, vol. abs/1802.10140, 2018.
  36. F. Sun, A. Dubey, and J. White, DxNAT - Deep neural networks for explaining non-recurring traffic congestion, in 2017 IEEE International Conference on Big Data, BigData 2017, Boston, MA, USA, December 11-14, 2017, 2017, pp. 2141–2150.
  37. A. Ghafouri, A. Laszka, A. Dubey, and X. D. Koutsoukos, Optimal detection of faulty traffic sensors used in route planning, in Proceedings of the 2nd International Workshop on Science of Smart City Operations and Platforms Engineering, SCOPE@CPSWeek 2017, Pittsburgh, PA, USA, April 21, 2017, 2017, pp. 1–6.
  38. S. P. Khare, J. Sallai, A. Dubey, and A. S. Gokhale, Short Paper: Towards Low-Cost Indoor Localization Using Edge Computing Resources, in 20th IEEE International Symposium on Real-Time Distributed Computing, ISORC 2017, Toronto, ON, Canada, May 16-18, 2017, 2017, pp. 28–31.
  39. C. Samal, F. Sun, and A. Dubey, SpeedPro: A Predictive Multi-Model Approach for Urban Traffic Speed Estimation, in 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017, Hong Kong, China, May 29-31, 2017, 2017, pp. 1–6.
  40. F. Sun, C. Samal, J. White, and A. Dubey, Unsupervised Mechanisms for Optimizing On-Time Performance of Fixed Schedule Transit Vehicles, in 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017, Hong Kong, China, May 29-31, 2017, 2017, pp. 1–8.
  41. A. Oruganti, F. Sun, H. Baroud, and A. Dubey, DelayRadar: A multivariate predictive model for transit systems, in 2016 IEEE International Conference on Big Data, BigData 2016, Washington DC, USA, December 5-8, 2016, 2016, pp. 1799–1806.
  42. S. Shekhar, F. Sun, A. Dubey, A. Gokhale, H. Neema, M. Lehofer, and D. Freudberg, A Smart Decision Support System for Public Transit Operations, in Internet of Things and Data Analytics Handbook, 2016.
  43. F. Sun, Y. Pan, J. White, and A. Dubey, Real-Time and Predictive Analytics for Smart Public Transportation Decision Support System, in 2016 IEEE International Conference on Smart Computing, SMARTCOMP 2016, St Louis, MO, USA, May 18-20, 2016, 2016, pp. 1–8.
  44. A. Dubey, M. Sturm, M. Lehofer, and J. Sztipanovits, Smart City Hubs: Opportunities for Integrating and Studying Human CPS at Scale, in Workshop on Big Data Analytics in CPS: Enabling the Move from IoT to Real-Time Control, 2015.