Publications

Active-Sensing

  1. H. Park, J. Darko, N. Deshpande, V. Pandley, H. Sui, M. Ono, D. Barkely, D. Posselt, S. Chien. Temporal Multimodal Multivariate Learning (TMML). The SIG Knowledge Discovery and Data Mining (SIGKDD 2022) Conference, Washington DC, USA August 14-18, (2022) [DOI] [PDF] SIGKDD Ranked 1st in Data Mining & Analysis according to Google Scholar
  2. J. Darko, L. Folsom , H. Park, M. Minamide, M. Ono, H. Su. A Sampling-Based Path Planning Algorithm for Improving Observations in Tropical Cyclones. Earth and Space Science 9 (1), e2020EA001498, (2022) [DOI][PDF]
  3. L. Folsom, M. Ono, K. Otsu, H. Park. Scalable Information-Theoretic Path Planning for a Rover-Helicopter Team in Uncertain Environments, International Journal of Advanced Robotic Systems 18 (2), 1–18. (2021) [DOI]
  4. H. Park, S. Gao, A. Haghani, M.A. Knodler, S. Samuel. Anticipatory sensor location problem in connected vehicle environment. Transportation Science 52 (6), 1299–1326. (2018) [DOI][PDF]
  5. H. Park, A. Haghani. Optimal number and location of Bluetooth sensors considering stochastic travel time prediction. Transportation Research Part C: Emerging Technologies, 55, 203-216. (2015) [DOI] [PDF]
  6. M. Ono, B. Rothrock, K. Otsu,…, H. Park. MAARS: Machine learning-based Analytics for Rover Systems. Proceedings of the International IEEE 2020 Aerospace Conference (with AIAA and PHM Society as technical cosponsors), Yellowstone Conference Center, Big Sky, Montana, Mar 7-14 (2020). [DOI]
  7. H. Park, A. Haghani. Connected Vehicle Sensor Location Model for Traffic Congestion Mitigation. Proceedings of the Tenth Triennial Symposium on Transportation Analysis (TRISTAN), Hamilton Island, Australia. (2019).
  8. H. Park. Sensor Deployment for Reduction of Arterial Traffic Congestion. Proceedings of 98th Annual Meeting of Transportation Research Board (TRB 2019), # 19-04832, Washington, DC. (2019).
  9. H. Park and A. Haghani. Stochastic Dynamic Sensor Location Problem with Efficient Solutions. Proceedings of 98th Annual Meeting of Transportation Research Board (TRB 2019), # 19-04783, Washington, DC. (2019).
  10. H. Park. 2018. Simulation-based Optimization for Reconfiguration of Mobile Wireless Sensor Network. IEEE Wireless Telecommunications Symposium (WTS), Phoenix, Arizona. (2018).
  11. H. Park. Portable traffic sensors to enhance arterial mobility. IEEE SoutheastCon, St. Petersburg, FL. (2018).
  12. H. Park, S. Gao, A. Haghani. Optimal relocation of portable traffic sensors to improve arterial mobility. The 96th Annual Meeting of Transportation Research Board (TRB 2017).
  13. H. Park, A. Haghani. Dynamic relocation of Bluetooth sensors for improvement of signal timing. The 9th Triennial Symposium on Transportation Analysis (TRISTAN) Oranjested, Aruba. (2016).
  14. H. Park, A. Haghani. Innovative use of Bluetooth technology considering dynamic relocation. Intelligent Transportation Systems of America (ITS America) Annual Meeting and Expo, Pittsburgh, PA 2015. Best Student Essay Award [PDF]
  15. H. Park, A. Haghani. Optimal number and location of Bluetooth sensors considering stochastic travel time prediction. The 56th Annual Transportation Research Forum (TRF 2015), Atlanta, GA, March, 2015. Best Student Paper Award [PDF]
  16. H. Park, A. Haghani, Y. Aliari. Optimal number and location of Bluetooth sensors on arterial roads: The stochastic and dynamic approaches. The 1st International Conference on Engineering and Applied Sciences Optimization (OPTI 2014) Kos Island, Greece (2014).

Digital-Twin

  1. J. Darko, L. Folsom, N. Pugh, H. Park, K. Shirzad, J. Owens, A. Miller. Adaptive Personalized Routing for Vulnerable Road Users, IET Intelligent Transport Systems, 16 (8), 1011–1025. (2022) [DOI]
  2. J. Darko, H. Park. Modeling and Assessing the Impact of a Traveler’s Preference on Transit Route-Choice Behavior. North Carolina Department of Transportation Research & Innovation Summit – 2020. Poster Competition Winner. [DOI]
  3. Darko, J., H. Park, Chow, J., Vulnerable Road User Personalized Optimum and Dynamic (VRUPOD) Routing. International symposium on transport network reliability (INSTR), Stockholm, Sweden, June 16-18, (2021).
  4. N. Pugh, H. Park, P. Derjany, S. Namalie, D. Liu. Deep adaptive learning for safe and efficient navigation of pedestrian dynamics. IET Intelligent Transport Systems, 15 (4), 538–548. (2021) [DOI]
  5. S. Haghani, M. Bikdash, H. Park. Robust Virtual Backbone for Vehicular Ad-Hoc Network Reliability in Intelligent Transportation Systems. International symposium on transport network reliability (INSTR), Stockholm, Sweden, June 16-18. (2021).
  6. K Shirzad, J Darko, L Folsom, N Pugh, H. Park, J Owens, A Miller, A Personalized Trip Planner for Vulnerable Road Users. The 100th Annual Meeting of Transportation Research Board (TRB2021), # 21-02068, Washington, DC. (2021).
  7. J Darko, H. Park, Modeling and Assessing the Impact of a Traveler’s Preference on Transit Route-Choice Behavior. The 100th Annual Meeting of Transportation Research Board (TRB2021), # 21-02784, Washington, DC. (2021).
  8. S. Haghani, M. Bikdash, H. Park, Area-Based Backbone for Vehicular Ad-Hoc Networks. Proceedings of the IEEE SoutheastCon (2021).
  9. H. Park, N. Pugh, J. Darko, L. Folsom, S. Samuel. Explicit Forward Glance Duration Hidden Markov Model for Inference of Spillover Detection. In: Stanton N. (eds) Advances in Human Factors of Transportation. (AHFE). Advances in Intelligent Systems and Computing, vol 964. Springer, Cham. (2020)
  10. J. Shirzad, H. Park. Adaptive Personalized Routing For Vulnerable Road Users. The 2nd Triennial Transportation Science and Logistics Society Conference (TSL II), Arlington, VA. (2020).
  11. J. Darko, H. Park. Vulnerable road user navigation considering perception on the transit uncertainty. The 2nd Triennial Transportation Science and Logistics Society Conference (TSL II), Arlington, VA. (2020).
  12. X. Yu, S. Gao, X. Hu, H. Park. A Markov Decision Process Approach to Vacant Taxi Routing with Ehailing. Transportation Research Part B: Methodological, 121, 114-134. (2019) [DOI][PDF]
  13. H. Park, N. Pugh. Generalized Estimating Equations Model Based Recursive Partitioning: Applied to Distracted Driving. In: Stanton N. (eds) Advances in Human Aspects of Transportation. (AHFE). Advances in Intelligent Systems and Computing, vol 786. Springer, Cham. (2019)
  14. Folsom, L., Darko, J., Pugh N., H. Park. Travelers’ rationality in anticipatory online emergency response. Safe Systems Summit, Durham Convention Center. (2019).
  15. H. Park, N. Pugh, P. Schonfeld. A. Haghani. Effect of Demand Shifting on Security Checkpoint Operation. The 22nd Air Transport Research Society (ATRS) World Conference, #287. Seoul, Korea. (2018).
  16. X. Yu, S. Gao, H. Park. 2018. Multi-Cycle Optimal Taxi Routing with E-hailing. Proceedings of the 18th COTA International Conference of Transportation Professionals (CICTP), No. 664, Beijing, China, July 5–8, (2018).
  17. X. Yu, S. Gao, H. Park. 2018. Multi-Cycle Optimal Taxi Routing with E-hailing. The 97th Annual Meeting of Transportation Research Board, Washington, DC, Paper #18-04575, (2018).  [PDF]
  18. H. Park, S. Gao, S. Samuel, 2017. Modeling effects of forward roadway glance durations on latent hazard detection. TRR: Journal of the Transportation Research Board 2663, 90-98. (2017). [DOI][PDF]
  19. X. Yu, S. Gao, H. Park. Muti-Cycle Optimal Taxi Routing. The 1st Triennial Transportation Science and Logistics Society Conference (TSL I), Chicago, Illinois (2017).
  20. H. Park, S. Gao, S. Samuel. Modeling effects of forward roadway glance durations on latent hazard detection. The 96th Annual Meeting of Transportation Research Board (TRB 2017).
  21. H. Park. Explicit forward glance duration hidden Markov model for inference of hazard detection. Human Factors and Ergonomics Society (HFES 2017), October, Austin, Texas, (2017).

Adaptive-Service

  1. Y. Yupeng, Y. Jiahao and L. Dahai and L. Sang-A and N. Sirish and I. Sabique-UI and G. Huaxing and H. Park, Multi-agent collaboration for emergency evacuation using reinforcement learning for transportation systems. IEEE Journal on Miniaturization for Air and Space Systems. (2022) [DOI]
  2. J. Darko, H. Park, Unmanned Aerial and Ground Emergency Vehicles in Traffic Incident Management: An Anticipatory Assignment Model. The 101th Annual Meeting of Transportation Research Board (TRB2022), # 22-03332, Washington, DC, January, (2022).
  3. J. Darko, H. Park, Proactive Distributed Constraint Optimization of Heterogeneous Incident Vehicle Teams. International Journal of Distributed Sensor Networks. (Under review) [DOI]
  4. J. Darko, H. Park, Multimodal Trip Planning for Vulnerable Road Users Considering Risk-Preference. (Under review)
  5. J. Darko, H. Park. A Proactive Dynamic-Distributed Constraint Optimization Framework for Unmanned Aerial and Ground Vehicles in Traffic Incident Management. The 6th International Conference on Intelligent Transportation Engineering (ICITE2021). October, 2021. [PDF]
  6. J. Darko, L. Folom, N. Deshpande, H. Park. Distributed Constraint Optimization Problem for Coordinated Response of Unmanned Aerial Vehicles and Ground Vehicles. The 55th Annual Conference on Information Sciences and Systems (CISS2021), # 2131, March, 2021. [DOI]
  7. J. Darko, L. Folsom, N. Deshpande, H. Park. A New Distributed Agent Framework for Traffic Incident Management. ASCE International Conference on Transportation & Development (ISTD), (2021).
  8. J. Darko, Y. Acquaah, L. Folsom, H. Park, A., Alden. DRONETIM: Dynamic Routing of Unmanned-aerial and Emergency Team Incident Management. The 99th Annual Meeting of Transportation Research Board (TRB2020), # 20-02283, Washington, DC. (2020).
  9. J. Darko, H. Park. DRONETIM:Dynamic Routing Of uNmanned-aerial and Emergency Team Incident Management. The 2nd Triennial Transportation Science and Logistics Society Conference (TSL II), Arlington, VA. (2020).
  10. H. Park, D. Waddel, A. Haghani. Online emergency vehicle dispatching with look-ahead on a transportation network. Transportation Research Part C: Emerging Technologies 109, 95-116. (2019). [DOI]
  11. D. Waddell, N. Pugh, K. Shirzad, H. Park. Simulation-Based Optimization of Emergency Response Considering Rationality of Travelers. Proceedings of the 98th Annual Meeting of Transportation Research Board (TRB 2019), # 19-05975, Washington, DC. (2019).
  12. D. Waddell, N. Pugh, H. Park. 2019. Visualization-based Dynamic Dispatching of First Responders. Proceedings of 98th Annual Meeting of Transportation Research Board (TRB 2019), # 19-05569, Washington, DC. (2019).
  13. H. Park, A. Haghani. Online redeployment and routing of emergency vehicles considering sequence of incidents. The 9th Triennial Symposium on Transportation Analysis (TRISTAN) Oranjested, Aruba. (2016).
  14. H. Park, A. Shafahi, A. Haghani. A stochastic emergency response location model considering secondary incidents on freeways. IEEE Transactions on Intelligent Transportation Systems, 17 (9), 2528-2540 (2016). [DOI] [PDF]
  15. H. Park, A. Haghani. Stochastic emergency response units allocation considering secondary incident occurrences. The 95th Annual Meeting of Transportation Research Board (TRB 2016), Washington, DC. (2016).
  16. H. Park, A. Haghani. Online emergency vehicle dispatching with look-ahead on a transportation network. The 95th Annual Meeting of Transportation Research Board (TRB 2016), Washington, DC. (2016).
  17. H. Park, A. Haghani. An optimal fleet allocation of emergency response teams on freeway using a two stage stochastic programming. The 20th Conference of the International Federation of Operational Research Societies (IFORS 2014), Barcelona, Spain, July, (2014).
  18. Y. Aliari, A. Haghani, H. Park. An efficient network model for allocation of in-house and outsourced construction equipment among projects. The 1st International Conference on Engineering and Applied Sciences Optimization (OPTI 2014) Kos Island, Greece (2014).

Non-I.I.D.

  1. H. Patel, R. Zhao, H. Park, Data-Driven Machine Learning Models for Estimation of Partitioning Behavior of Per- and Poly-Alkyl Substances (PFAS) on Liquid-Solid Interface for Carbon and Mineral Based Surfaces. Environmental Science & Technology Letters. (Under review) [DOI]
  2. N. Pugh, H. Park. High-Order Markov Model for Prediction of Secondary Crash Likelihood considering Incident Duration, Cogent Engineering, 8 (1). Taylor & Francis (2021) [DOI]
  3. N. Pugh, H. Park. High-Order Markov Model for Prediction of Secondary Crash Likelihood Considering Incident Duration. Proceedings of the 99th Annual Meeting of Transportation Research Board (TRB 2020), # 20-02092, Washington, DC. (2020).
  4. K. Shirzad, B. Vafaei, H. Park. Prediction of Critical Factor of Safety in Soil Slopes Using Adaptive NetworkBased Fuzzy Inference System (ANFIS). Proceedings of the 99th Annual Meeting of Transportation Research Board (TRB 2020), # 20-02315, Washington, DC. (2020).
  5. Y. Acquaah, J. Vine-Hodge, H. Park. Development of multinomial and ordinal logistic models for bicyclist and pedestrian crashes across Divisions 13 and 14 of North Carolina. Proceedings of the 99th Annual Meeting of Transportation Research Board (TRB 2020), # 20-02263, Washington, DC. (2020).
  6. S. Haghani, S. Yi, H. Park. Predicting the Budburst of Deciduous Trees in North Carolina from the Interaction between Precipitation and Temperature. Proceedings of the IEEE SoutheastCon, Huntsville, AL. (2019).
  7. N. Pugh, H. Park. Prediction of Secondary Crash Likelihood considering Incident Duration using High Order Markov Model. Proceedings of the IEEE SoutheastCon, Huntsville, AL. (2019).
  8. J. Darko, L. Kurkalova, H. Park. The Intensity of North Carolina Cropland Use. AAEA 2019 Annual Meeting, Atlanta, July 21-23, (2019). Trust Funded Programs AAEA Travel Grant Award.
  9. H. Park, A. Haghani, M.A. Knodler, S. Samuel, March. Real-time crash prediction and avoidance under unexpected traffic congestion. Accident Analysis & Prevention 112, 39-49. (2018) [DOI]
  10. H. Park, A. Haghani. Stochastic capacity adjustment considering secondary incidents. IEEE Transactions on Intelligent Transportation Systems, 17 (10), 2843-2853. (2016) [DOI] [PDF]
  11. H. Park, A. Haghani. Real-time prediction of secondary incident occurrences using vehicle probe data. Transportation Research Part C: Emerging Technologies, 70, 69–85. (2015) [DOI]
  12. H. Park, A. Haghani, X. Zhang. Interpretation of Bayesian neural networks for predicting the duration of detected incidents. Journal of Intelligent Transportation Systems: Technologies, Planning, and Operations, 20 (4), 385-400. (2015) [DOI] [PDF]
  13. H. Park, B. Son, H. Kim. Development of accident prediction models for freeway interchange ramps. Journal of the Korean Society of Transportation, 25(3), 123-135. (2007) [DOI]
  14. H. Park, S. Gao, A. Haghani. Sequential interpretation and prediction of secondary incident probability in real time. The 96 th Annual Meeting of Transportation Research Board (TRB 2017).
  15. H. Park, A. Haghani. Stochastic capacity adjustment considering secondary incidents. The 95th Annual Meeting of Transportation Research Board (TRB 2016), Washington, DC (2016).
  16. H. Park, A. Haghani. Use of clustering model and adjusted boxplot model for identification of secondary incidents. The 95th Annual Meeting of Transportation Research Board (TRB 2016), Washington, DC (2016).
  17. H. Park, A. Haghani. Capacity adjustment considering the impact of secondary incidents. The 94th Annual Meeting of Transportation Research Board (TRB 2015), Washington, DC. (2015).
  18. H. Park, A. Haghani, Y. Aliari. A pedagogical rule extraction from Bayesian neural networks for prediction of secondary incidents. The 1st International Conference on Engineering and Applied Sciences Optimization (OPTI 2014) Kos Island, Greece (2014).
  19. H. Park, A. Haghani. Identification and prediction of secondary crashes using vehicle probe data. The 93rd Annual Meeting of Transportation Research Board (TRB 2014), AFB20(2) Subcommittee, Washington, DC. (2014).
  20. H. Park, A. Haghani. Quantifying non-recurrent congestion impact on secondary incidents using probe vehicle data. The 54th Annual Transportation Research Forum (TRF 2013), Annapolis, MD. (2013).
  21. H. Park, A. Haghani, X. Zhang. ATIS: Interpretation of Bayesian neural network for predicting the duration of detected incidents. The 92nd Annual Meeting of Transportation Research Board (TRB 2013), Washington, DC. (2013).
  22. H. Park, A. Haghani., H. Masoud. Real-time filtering of vehicle probe data for secondary incident prediction. The 8th Triennial Symposium on Transportation Analysis (TRISTAN), San Pedro de Atacama, Chile. (2013).
  23. H. Park, A. Haghani. Identification and prediction of secondary incidents. The 9th of US–KOREA Conference (UKC 2013) , New York/New Jersey. (2013).

Mobility & Energy

  1. A. Neupane, N. Deshpande, V. Pandley, H. Park, Multimodal Learning Models for Traffic Datasets. The SIG Knowledge Discovery and Data Mining (KDD 2022) Conference, Washington DC, USA August 14-18, (2022). [PDF]
  2. L. Folsom, H. Park, V. Pandey, Dynamic Routing of Heterogeneous Users After Traffic Disruptions Under a Mixed Information Framework. Frontiers in Future Transportation. 3:851069. 2022. [DOI] 
  3. D. Hale, A. Hajbabaie, J. Ma, J. Hu, H. Park, and J. Bared, 2016. Proposed data-driven performance measures for comparing and ranking traffic bottlenecks. Transportation Research Procedia 15, 483-494. [DOI] [PDF]
  4. J. Darko, H. Park. Integrating Pedestrian Accessibility with Public Transit Routing in a Multimodal Trip Planning Framework. The 101 th Annual Meeting of Transportation Research Board (TRB 2022), # 22-03342, Washington, DC. (2022).
  5. J. Darko, H. Park. Multimodal Public Transit Routing considering Travelers' Risk-Preference, Annual Meeting of the Transportation Research Forum (TRF2021), #154. (2021).
  6. L. Folom, H. Park. Multi-agent Information-Theoretic Decision-Making in Congested Network Conditions. ASCE International Conference on Transportation & Development (ISTD 2021).
  7.  L Folsom, H. Park, Dynamic Mixed Information Strategy for Heterogeneous Network Users and System Optimal Design. The 100th Annual Meeting of Transportation Research Board (TRB2021), # 21-02070, Washington, DC. (2021).
  8. L. Folsom, H. Park. Congestion Reduction Using Information-Theoretic Multi-agent Decision-Making, Annual Meeting of the Transportation Research Forum (TRF2021), #145. (2021).
  9. L. Folsom, H. Park. Information-theoretic navigation and stochastic user equilibrium. The 2nd Triennial Transportation Science and Logistics Society Conference (TSL II), Arlington, VA. (2020).
  10. N. Pugh, H. Park. Morning Peak Hour Speed Prediction using Deep Learning Neural Networks. Proceedings of the IEEE SoutheastCon 2019, Huntsville, AL. (2019).
  11. C. Azevedo, R. Seshadri, S. Gao, B. Atasoy, A. Akkinepally, H. Park et al., 2018. Tripod: Sustainable Travel Incentives with Prediction, Optimization, and Personalization. The 97th Annual Meeting of Transportation Research Board (TRB 2018) Washington, DC. Paper # 18-06769, (2018). [PDF]
  12. N. Pugh, H. Park. Prediction of Red-Light Running using an Artificial Neural Network. IEEE SoutheastCon, St. Petersburg, FL. (2018)
  13. S. Ayaz, S. Gao, H. Park. 2018. Cooperative Scheme - An Alternative Approach to an Equitable and ParetoImproving Transportation System. The 97 th Annual Meeting of Transportation Research Board Washington, DC, Paper #18-00304 (2018). [PDF]
  14. S. Ayaz, S. Gao, H. Park. An Alternative Approach to Equitable and Pareto-Improving System Optimum. The 1st Triennial Transportation Science and Logistics Society Conference (TSL I), Chicago, Illinois (2017).
  15. D. Hale, A. Hajbabaie, J. Ma, J. Hu, H. Park, J. Bared. Proposed Data-Driven Performance Measures for Comparing and Ranking Traffic Bottlenecks. The 96 th Annual Meeting of Transportation Research Board (TRB 2017).
  16. H. Park, A. Haghani. Improving mobility of urban arterial roads using Bluetooth technology. The 4th International Conference on Mobile Services, Resources, and Users (MOBILITY 2014), France, Paris (2014).

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