human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "guaranteed safe reachability based trajectory design for a high fidelity model of an autonomous passenger vehicle"
  Abstract: Trajectory planning is challenging for autonomous cars since they operate in unpredictable environments with limited sensor horizons. To incorporate new information as it is sensed, planning is done in a loop, with the next plan being computed as the previous plan is executed. The recent Reachability-based Trajectory Design (RTD) is a provably safe, real-time algorithm for trajectory planning. RTD consists of an offline component, where a Forward Reachable Set (FRS) is computed for the vehicle tracking parameterized trajectories; and an online part, where the FRS is used to map obstacles to constraints for trajectory optimization in a provably-safe way. In the literature, RTD has only been applied to small mobile robots. The contribution of this work is applying RTD to a passenger vehicle in CarSim, with a full powertrain model, chassis and tire dynamics. RTD produces safe trajectory plans with the vehicle traveling up to 15 m/s on a two-lane road, with randomly-placed obstacles only known to the vehicle when detected within its sensor horizon. RTD is compared with a Nonlinear Model-Predictive Control (NMPC) and a Rapidly-exploring Random Tree (RRT) approach. The experiment demonstrates RTD's ability to plan safe trajectories in real time, in contrast to the existing state-of-the-art approaches.

Connected through hyperedge HE-1 (induced by source paper "technical report safe aggressive quadrotor flight via reachability based trajectory design"):
  with members:
    - "accurate tracking of aggressive quadrotor trajectories using incremental nonlinear dynamic inversion and differential flatness"
    - "bridging the gap between safety and real time performance in receding horizon trajectory design for mobile robots"
    - "a scalable framework for real time multi robot multi human collision avoidance"
    - "fastrack a modular framework for fast and guaranteed safe motion planning"
    - "safe trajectory synthesis for autonomous driving in unforeseen environments"

Connected through hyperedge HE-2 (induced by source paper "safe aggressive quadrotor flight via reachability based trajectory design"):
  with members:
    - "towards provably not at fault control of autonomous robots in arbitrary dynamic environments"
    - "bridging the gap between safety and real time performance in receding horizon trajectory design for mobile robots"
    - "a scalable framework for real time multi robot multi human collision avoidance"
    - "fastrack a modular framework for fast and guaranteed safe motion planning"
    - "safe trajectory synthesis for autonomous driving in unforeseen environments"

Connected through hyperedge HE-3 (induced by source paper "risk assessment and planning with bidirectional reachability for autonomous driving"):
  with members:
    - "an efficient reachability based framework for provably safe autonomous navigation in unknown environments"
    - "towards provably not at fault control of autonomous robots in arbitrary dynamic environments"
    - "occlusion aware risk assessment for autonomous driving in urban environments"
    - "tackling occlusions limited sensor range with set based safety verification"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.SY(Systems and Control)