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CANVAS Related Publications

  1. Mazin Hnewa and Hayder Radha, “Object Detection under Rainy Conditions for Autonomous Vehicles,” IEEE Signal Processing Magazine, Special Issue on Autonomous Vehicles, accepted, January 2021.
  2. Su Pang, Daniel Morris and Hayder Radha, “CLOCs: Camera-LiDAR Object Candidates Fusion for 3D Object Detection,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2020.
  3. Daniel Kent, Philip K. McKinley and Hayder Radha, “Localization Uncertainty-driven Adaptive Framework for Controlling Ground Vehicle Robots,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2020.
  4. Su Pang and Hayder Radha, “Multi-Object Tracking using Poisson Multi-Bernoulli Mixture Filtering for Autonomous Vehicles,” CVPR 2020 Workshop on Autonomous Driving, 3D Tracking Challenge, Honorable Mention Winner. http://cvpr2020.wad.vision
  5. Mazin Hnewa and Hayder Radha, “Rain-Adaptive Intensity-Driven Object Detection for Autonomous Vehicles,” SAE World Congress, May 2020.
  6. Eric Klinefelter, Jeffrey A. Nanzer, and Hayder Radha, “Radar Tracking with Orthogonal Velocity Measurements for Autonomous Ground Vehicles,” IEEE Radar Conference 2020.
  7. Yasir K. Al-Nadawi, Hothaifa Al-Qassab, Daniel Kent, Su Pang, Vaibhav Srivastava, and Hayder Radha, “Design of Robust Path-Following Control System for Self-driving Vehicles Using Extended High-Gain Observer,” American Control Conference (ACC), July 2020.
  8. Su Pang, Daniel Kent, Daniel Morris, and Hayder Radha, “FLAME: Feature-Likelihood Based Mapping and Localization for Autonomous Vehicles,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2019.
  9. Hothaifa Al-Qassab and Hayder Radha, “Active Safety System for Connected vehicles,” SAE International Journal of Connected and Automated Vehicles, Manuscript Number: JCAV-2018-0008R3, August 2019
  10. Su Pang, Daniel Kent, Xi Cai, Daniel Morris, Hayder Radha, “3D Scan Registration Based Localization for Autonomous Vehicles - A Comparison of NDT and ICP under Realistic Conditions”, IEEE Connected and Automated Vehicles Symposium 2018, Chicago, USA
  11. Al-Qassab, H., Pang, S., Al-Qizwini, M., and Radha, H., "Visual Sensor Fusion and Data Sharing across Connected Vehicles for Active Safety," Society of Automotive Engineers (SAE) World Congress. SAE Technical Paper 2018-01-0026, 2018.
  12. M. Al-Qizwini, I. Barjasteh, H. Al-Qassab and H. Radha, "Deep learning algorithm for autonomous driving using GoogLeNet," 2017 IEEE Intelligent Vehicles Symposium (IV), Los Angeles, CA, 2017, pp. 89-96. doi: 10.1109/IVS.2017.7995703
  13. S. D. Bopardikar and V. Srivastava. Dynamic Vehicle Routing in Presence of Random Recalls. IEEE Control Systems Letters, 4(1):37-42, 2020.
  14. C. J. Boss, V. Srivastava, and H. K. Khalil. Robust tracking of an unknown trajectory with a multi-rotor UAV: A high-gain observer approach. In American Control Conference, Denver, CO, July 2020.
  15. Y. Bagla and V. Srivastava. On Receding Horizon Chance Constraint Motion Planning for Uncertain Multi-agent Systems. In ASME Dynamic Systems and Control Conference, Park City, UT, pages V003T19A012, October 2019.
  16. S. D. Bopardikar, "A randomized approach to sensor placement with observability assurance”, Automatica, conditionally accepted, 2020.
  17. S. D. Bopardikar, O. Ennasr and X. Tan, ``Randomized Sensor Selection for Nonlinear Systems with Application to Target Localization." IEEE Robotics and Automation Letters vol. 4, no. 4, pages 3553-3560, 2019.
  18. J. P. Hespanha and S. D. Bopardikar, “Output-feedback linear quadratic robust control under actuation and deception attacks”, In American Control Conference (ACC) (pp. 489-496), Philadelphia, PA, USA, July 2019.
  19. S. D. Bopardikar, "Sensor Selection in Presence of Random Failures”, In American Control Conference (ACC) (pp. 3105-3110), Philadelphia, PA, USA, July 2019.
  20. S. Bajaj and S. D. Bopardikar, "Dynamic boundary guarding against radially incoming targets”, In IEEE International Conference on Decision and Control, Nice, France, Dec. 2019
  21. M. Zhang, R. Fu, D. Morris, C. Wang, “A Framework for Turning Behavior Classification at Intersections Using 3D LIDAR,” in IEEE Transactions on Vehicular Technology, 68(8), pp. 7431 – 7442, 2019.
  22. S. Imran, Y. Long, X. Liu, D. Morris, “Depth Coefficients for Depth Completion,” in Proc. of Computer Vision and Pattern Recognition (CVPR), pp. 12438-12447, Jun 2019.
  23. Ziyuan Zhang, Luan Tran, Feng Liu, Xiaoming Liu, “On Learning Disentangled Representations for Gait Recognition,” in IEEE Transactions on Pattern Analysis Machine Intelligence (PAMI), May 2020. (accepted)
  24. Shengjie Zhu, Garrick Brazil, Xiaoming Liu, “The Edge of Depth: Explicit Constraints between Segmentation band Depth,” in Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2020), Seattle, WA, June 2020.
  25. Garrick Brazil, Xiaoming Liu, “Monocular 3D Region Proposal Network for 3D Object Detection,” In Proceeding of International Conference on Computer Vision (ICCV 2019), Seoul, South Korean, Oct. 2019. (Oral, Acceptance rate 4.3%)
  26. Ziyuan Zhang, Luan Tran, Xi Yin, Yousef Atoum, Xiaoming Liu, Jian Wan, Nanxin Wang, “Gait Recognition via Disentangled Representation Learning,” in Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2019), Long beach, CA, June 2019. (Oral, Acceptance rate 5.6%) 6.
  27. Garrick Brazil, Xiaoming Liu, “Pedestrian Detection with Autoregressive Network Phases,” in Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2019), Long beach, CA, June 2019.
  28. O. Styles, V. Sanchez, A. Ross, “Forecasting Pedestrian Trajectory with Machine-Annotated Training Data,” IEEE Intelligent Vehicles Symposium, (Paris, France), June 2019.
  29. D. Deb, A. Ross, A. K. Jain, K. Prakah-Asante, K. V. Prasad, “Actions Speak Louder Than (Pass)words: Passive Authentication of Smartphone Users via Deep Temporal Features,” Proc. of 12th IAPR International Conference on Biometrics (ICB), (Crete, Greece), June 2019.
  30. E. Klinefelter and J. A. Nanzer, “Interferometric Microwave Radar with a Feedforward Neural Network for Vehicle Speed-Over-Ground Estimation,” IEEE Microwave and Wireless Components Letters, vol. 30, no. 3, 2020
  31. E. Klinefelter, J. A. Nanzer, and H. Radha, "Radar Tracking with Orthogonal Velocity Measurements for Autonomous Ground Vehicles," 2020 IEEE Radar Conference
  32. E. Klinefelter and J. A. Nanzer, "Millimeter-Wave Interferometric Radar for Speed-Over-Ground Estimation," 2020 IEEE International Microwave Symposium
  33. E. Klinefelter and J. A. Nanzer, "Multiple Target Angular and Radial Velocity Association in Interferometric Radar," 2020 IEEE International Symposium on Antennas and Propagation
  34. E. Klinefelter and J. A. Nanzer, "A Bound on Radial Velocity and Observation Time in Interferometric Angular Velocity Measurement," 2020 IEEE International Symposium on Antennas and Propagation
  35. E. Klinefelter and J. A. Nanzer, “Velocity Estimation with a Distributed Array for Autonomous Ground Vehicles,” IEEE International Conference on Microwaves for Intelligent Mobility, 2019
  36. E. Klinefelter and J. A. Nanzer, “Radar Measurement of the Angular Velocity of Moving Objects,” in Short-Range Micro-Motion Sensing with Radar Technology, C. Gu and J. Lien, Eds., IET Press, 2019
  37. Zhichao Lu, Ian Whalen, Vishnu Boddeti, Yashesh Dhebar, Kalyanmoy Deb, Erik Goodman and Wolfgang Banzhaf, “NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm,” GECCO 2019 (Best Paper Award)
  38. Zhichao Lu, Kalyanmoy Deb and Vishnu Boddeti, "MUXConv: Information Multiplexing in Convolutional Neural Networks,” CVPR 2020
  39. “Assuring Vehicle Update Integrity using Asymmetric Public Key Infrastructure (PKI) and Public Key Cryptography (PKC),” (Daniel Kent, Betty H.C. Cheng, and Joshua Siegel), 2020 escar USA Special Issue of the SAE International Journal of Transportation Cybersecurity and Privacy (in press).
  40. “Enki: A Diversity-Driven Approach to Test and Train Robust Learning-Enabled Systems” (Michael A. Langford and Betty H.C. Cheng), ACM Transactions on Autonomous and Adaptive Systems (under revision).
  41. “Security Patterns for Connected and Automated Vehicles” (Betty H.C. Cheng, Bradley Doherty, Nick Polanco, and Matthew Pasco), Journal for Automotive Software Engineering (JASE) Special Themed Issue, (under revision).
  42. “Goal-Oriented Non-Functional Specifications: Modeling, Analyzing, and Monitoring” (Byron DeVries and Betty H.C. Cheng), submitted to Software and Systems Modeling, June 2020.
  43. “MAPE-K/MAPE-SAC: Interaction Framework for Adaptive Systems with Security Assurance Cases,” Sharmin Jahan, Ian Riley, Charles Walter, Rose F. Gamble, Matthew Pasco, Betty H.C. Cheng, and Philip K. McKinley, Special Issue on Self-Protecting Systems in Journal of Future Generation Computer Systems, Volume 109, August 2020, pp. 197-209 (available online March 2020).
  44. “Providentia: Automatically Optimizing Weighted Non-Functional Objectives in SelfAdaptive Systems,” (K. Bowers, E.M. Fredericks, R.H. Hariri, and B.H.C. Cheng), Journal of Systems and Software, April, vol. 162, 2020 (online version available December 2019).
  45. “Automotive Cybersecurity and Situational Crime Prevention: Assessing a New Platform for Cybercrime and Malicious Hacking” (Jay P. Kennedy, Thomas J. Holt, and Betty H.C. Cheng) Journal of Crime and Justice, vol. 42, no. 5, pp. 632–645, 2019.
  46. Z. Marvi and B. Kiumarsi, "Safety Planning Using Control Barrier Function: A Model Predictive Control Scheme," IEEE 2nd Connected and Automated Vehicles Symposium (CAVS), Honolulu, HI, USA, 2019, pp. 1-5, 2019.
  47. N. M. Yazdani, R. K. Moghaddam, B. Kiumarsi and H. Modares, "A Safety-Certified Policy Iteration Algorithm for Control of Constrained Nonlinear Systems," in IEEE Control Systems Letters, vol. 4, no. 3, pp. 686-691, July 2020.
  48. Z. Marvi and B. Kiumarsi, " Safe Off-Policy Reinforcement Learning Using Barrier Functions," To be presented at American Control Conference (ACC), July, 2020.
  49. Z. Marvi and B. Kiumarsi, " Safe Reinforcement Learning: A Control Barrier Function Optimization Approach,” Accepted in International of Journal of Robust and Nonlinear Control, 2020.
  50. Y. Yang, K. G. Vamvoudakis, and H. Modares, "Safe reinforcement learning for dynamical games," International Journal of Robust and Nonlinear Control, vol. 30, no. 9, pp. 3706-3726, 2020.
  51. Y. Yang, K. G. Vamvoudakis, H. Modares, Y. Yin, and D. C. Wunsch, "Safe Intermittent Reinforcement Learning With Static and Dynamic Event Generators," IEEE Transactions on Neural Networks and Learning Systems, 2020.
  52. A. Mustafa and H. Modares, "Attack Analysis and Resilient Control Design for Discrete-Time Distributed Multi-Agent Systems," IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 369-376, 2019.
  53. B. Kiumarsi, B. AlQaudi, H. Modares, F. L. Lewis, and D. S. Levine, "Optimal control using adaptive resonance theory and Q-learning," Neurocomputing, vol. 361, pp. 119-125, 2019.
  54. Y. Yang, Y. Yin, W. He, K. G. Vamvoudakis, H. Modares, and D. C. Wunsch, "Safety-aware reinforcement learning framework with an actor-critic-barrier structure," In 2019 American Control Conference (ACC), pp. 2352-2358, 2019.
  55. Y. Yang, K. G. Vamvoudakis, H. Ferraz, and H. Modares, "Dynamic intermittent Q ‐learning–based model‐free suboptimal co‐design of L_2‐stabilization," International Journal of Robust and Nonlinear Control, vol. 29, no. 9, pp. 2673-2694, 2019.
  56. C. Chen, H. Modares, K. Xie, F. L. Lewis, Y. Wan, and S. Xie, "Reinforcement learning-based adaptive optimal exponential tracking control of linear systems with unknown dynamics," IEEE Transactions on Automatic Control, vol. 64, no. 11, pp. 4423-4438, 2019.
  57. Yongbin Sun, Yue Wang, Ziwei Liu, Joshua Siegel, Sanjay Sarma. "PointGrow: Autoregressively Learned Point Cloud Generation with Self-Attention." The IEEE Winter Conference on Applications of Computer Vision (WACV), 2020, pp. 61-70.
  58. Joshua Siegel and Daniel Morris. “Robotics, Automation, and the Future of Sports,” accepted to appear in Springer book “Sports and Technology,” 2020.
  59. Greg Falco, Joshua Siegel (equal contribution). “Assuring Automotive Data and Software Integrity Employing Distributed Hash Tables and Blockchain.” Under review in SAE International Journal of Transportation Cybersecurity and Privacy. Available: https://arxiv.org/abs/2002.02780
  60. Jevin Barnett, Nicholas Gizinski, Eduardo Mondragón-Parra, Joshua Siegel, Daniel Morris, Timothy Gates, Eva Kassens-Noor, Zachary Neal, Peter Savolainen. "Sharing the Road: Improving Automated Vehicle Compliance with Pedalcyclist Passing Laws.” Under review in IEEE Transactions on Intelligent Vehicles.
  61. Joshua Siegel and Umberto Coda. "Surveying Off-Board and Extra-Vehicular Monitoring and Progress Towards Pervasive Diagnostics.” Under review in IEEE Transactions on Intelligent Transportation Systems.
  62. Joshua Siegel, Georgios Pappas, Konstantinos Politopoulos and Yongbin Sun. "A gamified simulator and physical platform for self-driving algorithm training and validation.” Under review in IEEE Transactions on Games. Available: https://arxiv.org/abs/1911.07759
  63. Piyush Gupta, Demetris Coleman and Joshua Siegel. "Towards Safer Self-Driving Through Great PAIN (Physically Adversarial Intelligent Networks).” Available: https://arxiv.org/abs/2003.10662
  64. T. Chu, J. Wang, L. Codecà and Z. Li, "Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control," in IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 3, pp. 1086-1095, March 2020, doi: 10.1109/TITS.2019.2901791.
  65. A. Li, H. Jiang, Z. Li, J. Zhou and X. Zhou, "Human-Like Trajectory Planning on Curved Road: Learning from Human Drivers," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2019.2926647.
  66. A. Li, H. Jiang, Z. Li, J. Zhou and X. Zhou, "Human-Like Trajectory Planning on Curved Road: Learning from Human Drivers," in IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/TITS.2019.2926647.
  67. Z. Song et al., "Simultaneous Identification and Control for Hybrid Energy Storage System using Model Predictive Control and Active Signal Injection," in IEEE Transactions on Industrial Electronics, doi: 10.1109/TIE.2019.2952825.
  68. Z. Li, M. Zheng and H. Zhang, "Optimization-Based Unknown Input Observer for Road Profile Estimation with Experimental Validation on a Suspension Station," 2019 American Control Conference (ACC), Philadelphia, PA, USA, 2019, pp. 3829-3834, doi: 10.23919/ACC.2019.8815321.
  69. Z. Li, T. Chu and U. Kalabić, "Dynamics-Enabled Safe Deep Reinforcement Learning: Case Study on Active Suspension Control," 2019 IEEE Conference on Control Technology and Applications (CCTA), Hong Kong, China, 2019, pp. 585-591, doi: 10.1109/CCTA.2019.8920696.
  70. Wang, R., Biswas, S., Das, S., & Rao, J. (2019, April). Collaborative Caching for Dynamic Map Dissemination in Vehicular Networks. In 2019 IEEE ComSoc International Communications Quality and Reliability Workshop (CQR) (pp. 1-6). IEEE.