Abstract
In many automated motion planning systems, vehicles are tasked with tracking a reference path or trajectory that is safe by design. However, due to various uncertainties, real vehicles may deviate from such references, potentially leading to collisions. This paper presents rigorous reachable set bounding methods for rapidly enclosing the set of possible deviations under uncertainty, which is critical information for online safety verification. The proposed approach applies recent advances in the theory of differential inequalities that exploit redundant model equations to achieve sharp bounds using only simple interval calculations. These methods have been shown to produce very sharp bounds at low cost for nonlinear systems in other application domains, but they rely on problem-specific insights to identify appropriate redundant equations, which makes them difficult to generalize and automate. Here, we demonstrate the application of these methods to tracking problems for the first time using three representative case studies. We find that defining redundant equations in terms of Lyapunov-like functions is particularly effective. The results show that this technique can produce effective bounds with computational times that are orders of magnitude less than the planned time horizon, making this a promising approach for online safety verification. This performance, however, comes at the cost of low generalizability, specifically due to the need for problem-specific insights and advantageous problem structure, such as the existence of appropriate Lyapunov-like functions.
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The datasets generated for this article are obtainable from the corresponding author upon reasonable request.
References
Paden, B., Cáp, M., Yong, S.Z., Yershov, D., Frazzoli, E.: A survey of motion planning and control techniques for self-driving urban vehicles. IEEE Trans. Intell. Veh. 1(1), 33–55 (2016)
Broadhurst, A., Baker, S., Kanade, T.: Monte Carlo road safety reasoning. IEEE Intell. Veh. Symp. 319–324 (2005)
Eidehall, A., Petersson, L.: Statistical threat assessment for general road scenes using Monte Carlo sampling. IEEE Trans. Intell. Transp. Syst. 9(1), 137–147 (2008)
Zhou, Y., Baras, J.S.: Reachable set approach to collision avoidance for UAVs. IEEE Conf. Decis. Control. 5947–5952 (2015)
Rubies-Royo, V., Fridovich-Keil, D., Herbert, S., Tomlin, C.J.: A classification-based approach for approximate reachability. Int. Conf. Robot. Autom. 7697–7704 (2019)
Kleff, S., Li, N.: Robust motion planning in dynamic environments based on sampled-data Hamilton-Jacobi reachability. Robotica 38(12), 2151–2172 (2020)
Obayashi, M., Takano, G.: Real-time autonomous car motion planning using NMPC with approximated problem considering traffic environment. IFAC-Pap 51(20), 279–286 (2018)
Ames, A.D., Xu, X., Grizzle, J.W., Tabuada, P.: Control barrier function based quadratic programs for safety critical systems. IEEE Trans. Automat. Contr. 62(8), 3861–3876 (2016)
Jankovic, M.: Robust control barrier functions for constrained stabilization of nonlinear systems. Automatica 96, 359–367 (2018)
Prandini, M., Hu, J.: Application of reachability analysis for stochastic hybrid systems to aircraft conflict prediction. IEEE Conf. Decis. Control. 4036–4041 (2008)
Althoff, M., Stursberg, O., Buss, M.: Model-based probabilistic collision detection in autonomous driving. IEEE Trans. Intell. Transp. Syst. 10(2), 299–310 (2009)
Falcone, P., Ali, M., Sjoberg, J.: Predictive threat assessment via reachability analysis and set invariance theory. IEEE Trans. Intell. Transp. Syst. 12(4), 1352–1361 (2011)
Kianfar, R., Falcone, P., Fredriksson, J.: Safety verification of automated driving systems. IEEE Intell. Transp. Syst. Mag. 5(4), 73–86 (2013)
Althoff, M., Dolan, J.M.: Online verification of automated road vehicles using reachability analysis. IEEE Trans. Robot. 30(4), 903–918 (2014)
Anderson, S.J., Peters, S.C., Pilutti, T.E., Iagnemma, K.: An optimal-control-based framework for trajectory planning, threat assessment, and semi-autonomous control of passenger vehicles in hazard avoidance scenarios. Int. J. Veh. Auton. Syst. 8(2–4), 190–216 (2010)
Althoff, M., Stursberg, O., Buss, M.: Reachability analysis of nonlinear systems with uncertain parameters using conservative linearization. IEEE Conf. Decis. Control. 4042–4048 (2008)
Nedialkov, N.S., Jackson, K.R., Corliss, G.F.: Validated solutions of initial value problems for ordinary differential equations. Appl. Math. Comput. 105(1), 21–68 (1999)
Lin, Y., Stadtherr, M.A.: Validated solutions of initial value problems for parametric ODEs. Appl. Numer. Math. 57(10), 1145–1162 (2007)
Houska, B., Villanueva, M.E., Chachuat, B.: Stable set-valued integration of nonlinear dynamic systems using affine set-parameterizations. SIAM J. Numer. Anal. 53(5), 2307–2328 (2015)
Schürmann, B., Heß, D., Eilbrecht, J., Stursberg, O., Köster, F., Althoff, M.: Ensuring drivability of planned motions using formal methods. IEEE Trans. Intell. Transp. Syst. 1–8 (2017)
Heß, D., Althoff, M., Sattel, T.: Formal verification of maneuver automata for parameterized motion primitives. IEEE Int. Conf. Intell. Robots Syst. 1474–1481 (2014)
Harrison, G.W.: Dynamic models with uncertain parameters. In Proceedings of the first international conference on mathematical modeling 1, 295–304 (1997)
Harwood, S.M., Barton, P.I.: Efficient polyhedral enclosures for the reachable set of nonlinear control systems. Math. Control Signals Syst. 28(1), 8 (2016)
Chachuat, B., Villanueva, M.: Bounding the solutions of parametric ODEs: When Taylor models meet differential inequalities. Comput. Aided Chem. Eng. 30, 1307–1311 (2012)
Shen, K., Scott, J.K.: Exploiting nonlinear invariants and path constraints to achieve tighter reachable set enclosures using differential inequalities. Math. Control Signals Syst. 1–27 (2020)
Scott, J.K., Barton, P.I.: Bounds on the reachable sets of nonlinear control systems. Automatica 49(1), 93–100 (2013)
Shen, K., Scott, J.K.: Rapid and accurate reachability analysis for nonlinear dynamic systems by exploiting model redundancy. Comput. Chem. Eng. 106, 596–608 (2017)
Althoff, M., Dolan, J.M.: Reachability computation of low-order models for the safety verification of high-order road vehicle models. Am. Control Conf. 3559–3566 (2012)
Neumaier, A.: Interval Methods for Systems of Equations. Cambridge University Press, Encyclopedia of Mathematics and its Applications (1991)
Teixeira, B.O.S., Chandrasekar, J., Torres, L.A.B., Aguirre, L.A., Bernstein, D.S.: State estimation for linear and non-linear equality-constrained systems. Int. J. Contr. 82(5), 918–936 (2009)
Scott, J.K.: Reachability analysis and deterministic global optimization of differential-algebraic systems. PhD thesis, Massachusetts Institute of Technology (2012)
Barton, P.I., Scott, J.K.: Interval bounds on the solutions of semi-explicit index-one DAEs. Part 2: computation. Numer. Math. 125(1):27–60 (2013)
Kochdumper, N., Gassert, P., Althoff, M.: Verification of collision avoidance for commonroad traffic scenarios. In ARCH@ ADHS, p 184–194 (2021)
Hindmarsh, A.C., Brown, P.N., Grant, K.E., Lee, S.L., Serban, R., Shumaker, D.E., Woodward, C.S.: Sundials: Suite of nonlinear and differential/algebraic equation solvers. ACM Trans. Math. Softw. 31(3), 363–396 (2005)
Kanayama, Y., Kimura, Y., Miyazaki, F., Noguchi, T.: A stable tracking control method for an autonomous mobile robot. Proc. IEEE Int. Conf. Robot. Autom. 384–389 (1990)
Althoff, M.: An introduction to CORA Proc. of the Workshop on Applied Verification for Continuous and Hybrid Systems, p 120–151 (2015)
Werling, M., Groll, L., Bretthauer, G.: Invariant trajectory tracking with a full-size autonomous road vehicle. IEEE Trans. Robot. 26(4), 758–765 (2010)
Samson, C.: Path following and time-varying feedback stabilization of a wheeled mobile robot. Proc. Int. Conf. Adv. Robot. 13, 1–14 (1992)
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This material is based upon work supported by the National Science Foundation under grant no. 1949748.
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J. Scott and X. Yang contributed to the study conception and design, algorithm development, and theoretical analyses. X. Yang led the software development and simulations with assistance from B. Mu. Comparisons to CORA were run by D. Robertson. The first draft was written by X. Yang and edited by J. Scott. All authors read and approved the final manuscript.
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Yang, X., Mu, B., Robertson, D. et al. Guaranteed Safe Path and Trajectory Tracking via Reachability Analysis Using Differential Inequalities. J Intell Robot Syst 108, 78 (2023). https://doi.org/10.1007/s10846-023-01928-w
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DOI: https://doi.org/10.1007/s10846-023-01928-w