Journal papers

  1. P. Chakraborty and A. Sharma. Public Opinion Analysis of Transportation Policy using Social Media Data: Case Study on the Delhi Odd-Even Policy, Transportation in Developing Economies, March 2019. https://doi.org/10.1007/s40890-019-0074-8
  2. P. Chakraborty, Y.O. Adu-Gyamfi, S. Poddar, V. Ahsani, A. Sharma, and S Sarkar. Traffic Congestion Detection from Camera Images using Deep Convolution Neural Networks. Transportation Research Record: Journal of the Transportation Research Board, vol. 2672, no. 45, p222-231, December 2018. https://doi.org/10.1177/0361198118777631.
  3. M. Amin-Naseri, P. Chakraborty, A. Sharma, S.B. Gilbert, and M. Hong. Evaluating the Reliability, Coverage, and Added Value of Crowdsourced Traffic Incident Reports from Waze. Transportation Research Record: Journal of the Transportation Research Board, vol. 2672, no. 43, p34-43, December 2018. https://doi.org/10.1177/0361198118790619.
  4. P. Chakraborty and P. Chakroborty. Empirical analysis of short period traffic counts and their efficiency: The case of Indian traffic. Transportation Planning and Technology, vol. 40, no. 7, p812-827, June 2017. https://doi.org/10.1080/03081060.2017.1340021
  5. P. Chakroborty, R. Gill, and P. Chakraborty. Analysing queueing at toll plazas using a coupled, multiple-queue, queueing system model: application to toll plaza design, Transportation Planning and Technology, vol. 39, no. 7, p675-692, July 2016. https://doi.org/10.1080/03081060.2016.1204090

Under Review

  1. P. Chakraborty, C. Hegde, and A. Sharma. Data-driven parallelizable traffic incident detection using spatio-temporally denoised robust thresholds. Transportation Research-Part C.
  2. P. Chakraborty, J. Merickel, V. Shah, A. Sharma, C. Hegde, C. Desouza, A. Drincic, P. Gunaratne, and M. Rizzo. Quantifying vehicle control from physiology in type 1 diabetes. Traffic Injury Prevention.
  3. S. Poddar, P. Chakraborty, A. Sharma, S. Knickerbocker, and N. Hawkins. Massively parallelizable approach for evaluating signalized arterial performance using probe-based data. Transportation Research-Part C.

Conference papers

  1. V. Shah, J. Merickel, P. Chakraborty, C. Hegde, A. Sharma, P. Gunaratne, A. Drincic, C. Desouza, and M. Rizzo (Accepted). Quantifying driver speed behavior from real-time physiology in type 1 diabetes. 5th International Symposium on Future Active Safety Technology, September 2019.
  2. P. Chakraborty, A. Sharma, and C. Hegde. Freeway Traffic Incident Detection from Cameras: A Semi-Supervised Learning Approach, 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 1840-1845., December 2018. doi:10.1109/ITSC.2018.8569426
  3. M. Naphade, M.C. Chang, A. Sharma, D.C. Anastasiu, V. Jagarlamudi, P. Chakraborty, T. Huang, S. Wang, M.Y. Liu, R. Chellappa, J.N. Hwang, S. Lyu. The 2018 NVIDIA AI City Challenge, IEEE Conference on Computer Vision and Pattern Recognition Workshops, June 2018.
  4. S. Poddar, K. Ozcan, P. Chakraborty, V. Ahsani, A. Sharma, and S. Sarkar. Comparison of machine learning algorithms to determine traffic congestion from camera images, Transportation Research Board 96th Annual Meeting, January 2018.
  5. P. Chakraborty, C. Hegde, and A. Sharma. Trend Filtering in Network Time Series, with Applications to Traffic Incident Detection, NIPS Time Series Workshop (TSW), December 2017.
  6. P Chakraborty, J.R. Hess, A. Sharma, and S. Knickerbocker. Outlier mining based traffic incident detection using big data analytics, Transportation Research Board 96th Annual Meeting, January 2017.
  7. P. Chakraborty and P. Chakroborty. Studying the effectiveness of using fuel sales as a proxy for estimating seasonal factors of traffic, 3rd Conference of Transportation Research Group of India, December 2015.
  8. P. Chakraborty and P. Chakroborty. Estimation of Annual Average Daily Traffic (AADT) for Indian Highways, Transportation Research Board 94th Annual Meeting, January 2015.