IEEE/CAA Journal of Automatica Sinica
Citation: | Y. Rahman, A. Sharma, M. Jankovic, M. Santillo, and M. Hafner, “Driver intent prediction and collision avoidance with barrier functions,” IEEE/CAA J. Autom. Sinica, vol. 10, no. 2, pp. 365–375, Feb. 2023. doi: 10.1109/JAS.2023.123210 |
[1] |
H. A. P. Blom, “An efficient filter for abruptly changing systems,” in Proc. 23rd IEEE Conf. Decision and Control, Las Vegas, USA, 1984, pp. 656–658.
|
[2] |
L. A. Johnston and V. Krishnamurthy, “An improvement to the interacting multiple model (IMM) algorithm,” IEEE Trans. Signal Process., vol. 49, no. 12, pp. 2909–2923, Dec. 2001. doi: 10.1109/78.969500
|
[3] |
R. R. Pitre, V. P. Jilkov, and X. R. Li, “A comparative study of multiple-model algorithms for maneuvering target tracking,” in Proc. SPIE 5809, Signal Processing, Sensor Fusion, and Target Recognition XIV, Orlando, USA, 2005, pp. 549–560.
|
[4] |
C. Manasseh and R. Sengupta, “Predicting driver destination using machine learning techniques,” in Proc. 16th Int. IEEE Conf. Intelligent Transportation Systems, The Hague, Netherlands, 2013, pp. 142–147.
|
[5] |
Y. Hou, P. Edara, and C. Sun, “Modeling mandatory lane changing using Bayes classifier and decision trees,” IEEE Trans. Intell. Transp. Syst., vol. 15, no. 2, pp. 647–655, Apr. 2014. doi: 10.1109/TITS.2013.2285337
|
[6] |
F. Altchá and A. De La Fortelle, “An LSTM network for highway trajectory prediction,” in Proc. IEEE 20th Int. Conf. Intelligent Transportation Systems, Yokohama, Japan, 2017, pp. 353–359.
|
[7] |
A. Zyner, S. Worrall, J. Ward, and E. Nebot, “Long short term memory for driver intent prediction,” in Proc. IEEE Intelligent Vehicles Symp., Los Angeles, USA, 2017, pp. 1484–1489.
|
[8] |
T. Streubel and K. H. Hoffmann, “Prediction of driver intended path at intersections,” in Proc. IEEE Intelligent Vehicles Symp. Proc., Dearborn, USA, 2014, pp. 134–139.
|
[9] |
X. H. Li, W. S. Wang, and M. Roetting, “Estimating driver’s lane-change intent considering driving style and contextual traffic,” IEEE Trans. Intell. Transp. Syst., vol. 20, no. 9, pp. 3258–3271, Sep. 2019. doi: 10.1109/TITS.2018.2873595
|
[10] |
S. Prajna, A. Jadbabaie, and G. J. Pappas, “A framework for worst-case and stochastic safety verification using barrier certificates,” IEEE Trans. Autom. Control, vol. 52, no. 8, pp. 1415–1428, Aug. 2007. doi: 10.1109/TAC.2007.902736
|
[11] |
Y. Rahman, M. Jankovic, and M. Santillo, “Driver intent prediction with barrier functions,” in Proc. American Control Conf., New Orleans, USA, 2021, pp. 224–230.
|
[12] |
P. Wieland and F. Allgöwer, “Constructive safety using control barrier functions,” IFAC Proc. Vol., vol. 40, no. 12, pp. 462–467, 2007. doi: 10.3182/20070822-3-ZA-2920.00076
|
[13] |
A. D. Ames, X. R. Xu, J. W. Grizzle, and P. Tabuada, “Control barrier function based quadratic programs for safety critical systems,” IEEE Trans. Autom. Control, vol. 62, no. 8, pp. 3861–3876, Aug. 2017. doi: 10.1109/TAC.2016.2638961
|
[14] |
M. Jankovic, “Robust control barrier functions for constrained stabilization of nonlinear systems,” Automatica, vol. 96, pp. 359–367, Oct. 2018. doi: 10.1016/j.automatica.2018.07.004
|
[15] |
W. Xiao and C. Belta, “Control barrier functions for systems with high relative degree,” in Proc. IEEE 58th Conf. Decision and Control, Nice, France, 2019, pp. 474–479.
|
[16] |
Q. Nguyen and K. Sreenath, “Exponential control barrier functions for enforcing high relative-degree safety-critical constraints,” in Proc. American Control Conf., Boston, USA, 2016, pp. 322–328.
|
[17] |
R. Rajamani, Vehicle Dynamics and Control. Springer Science & Business Media, 2011.
|
[18] |
I. Gat, M. Benady, and A. Shashua, “A monocular vision advance warning system for the automotive aftermarket,” SAE Trans., vol. 114, pp. 403–410, 2005.
|
[19] |
M. R. Hafner, K. S. Zhao, A. Hsia, and Z. Rachlin, “Localization tools for benchmarking ADAS control systems,” in Proc. IEEE Int. Conf. Systems, Man, and Cybernetics, Budapest, Hungary, 2016, pp. 002665–002670.
|
[20] |
C. Su, W. W. Deng, H. Sun, J. Wu, B. H. Sun, and S. Yang, “Forward collision avoidance systems considering driver’s driving behavior recognized by Gaussian mixture model,” in Proc. IEEE Intelligent Vehicles Symp., Los Angeles, USA, 2017, pp. 535–540.
|
[21] |
W. S. Wang, J. Q. Xi, and J. K. Hedrick, “A learning-based personalized driver model using bounded generalized Gaussian mixture models,” IEEE Trans. Veh. Technol., vol. 68, no. 12, pp. 11679–11690, Dec. 2019. doi: 10.1109/TVT.2019.2948911
|
[22] |
J. Ziegler, P. Bender, T. Dang, and C. Stiller, “Trajectory planning for bertha—a local, continuous method,” in Proc. IEEE Intelligent Vehicles Symp. Proc., Dearborn, USA, 2014, pp. 450–457.
|
[23] |
C. K. Verginis and D. V. Dimarogonas, “Closed-form barrier functions for multi-agent ellipsoidal systems with uncertain lagrangian dynamics,” IEEE Control Syst. Lett., vol. 3, no. 3, pp. 727–732, Jul. 2019. doi: 10.1109/LCSYS.2019.2917822
|
[24] |
M. Brannström, E. Coelingh, and J. Sjöberg, “Model-based threat assessment for avoiding arbitrary vehicle collisions,” IEEE Trans. Intell. Transp. Syst., vol. 11, no. 3, pp. 658–669, Sep. 2010. doi: 10.1109/TITS.2010.2048314
|
[25] |
G. M. Hoffmann, C. J. Tomlin, M. Montemerlo, and S. Thrun, “Autonomous automobile trajectory tracking for off-road driving: Controller design, experimental validation and racing,” in Proc. American Control Conf., New York, USA, 2007, pp. 2296–2301.
|