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: "control of connected and automated vehicles state of the art and future challenges"
  Abstract: Autonomous driving technology pledges safety, convenience, and energy efficiency. Challenges include the unknown intentions of other road users: communication between vehicles and with the road infrastructure is a possible approach to enhance awareness and enable cooperation. Connected and automated vehicles (CAVs) have the potential to disrupt mobility, extending what is possible with driving automation and connectivity alone. Applications include real-time control and planning with increased awareness, routing with micro-scale traffic information, coordinated platooning using traffic signals information, eco-mobility on demand with guaranteed parking. This paper introduces a control and planning architecture for CAVs, and surveys the state of the art on each functional block therein; the main focus is on techniques to improve energy efficiency. We provide an overview of existing algorithms and their mutual interactions, we present promising optimization-based approaches to CAVs control and identify future challenges.

Connected through hyperedge HE-1 (induced by source paper "overview of tools supporting planning for automated driving"):
  with members:
    - "liability ethics and culture aware behavior specification using rulebooks"
    - "self driving cars a survey"
    - "interaction dataset an international adversarial and cooperative motion dataset in interactive driving scenarios with semantic maps"
    - "the apolloscape open dataset for autonomous driving and its application"
    - "design space of behaviour planning for autonomous driving"
    - "a survey of autonomous driving common practices and emerging technologies"
    - "fiesta fast incremental euclidean distance fields for online motion planning of aerial robots"
    - "top view trajectories a pedestrian dataset of vehicle crowd interaction from controlled experiments and crowded campus"

Connected through hyperedge HE-2 (induced by source paper "behavior planning for connected autonomous vehicles using feedback deep reinforcement learning"):
  with members:
    - "multi agent reinforcement learning a selective overview of theories and algorithms"
    - "model predictive policy learning with uncertainty regularization for driving in dense traffic"
    - "multi agent reinforcement learning via double averaging primal dual optimization"
    - "virtual to real reinforcement learning for autonomous driving"
    - "end to end driving via conditional imitation learning"
    - "safe multi agent reinforcement learning for autonomous driving"

Connected through hyperedge HE-3 (induced by source paper "formation and reconfiguration of tight multi lane platoons"):
  with members:
    - "vehicle localization and control on roads with prior grade map"
    - "safe adaptive cruise control with road grade preview and v2v communication"

Connected through hyperedge HE-4 (induced by source paper "zero shot autonomous vehicle policy transfer from simulation to real world via adversarial learning"):
  with members:
    - "demonstration of a time efficient mobility system using a scaled smart city"
    - "dissipation of stop and go waves via control of autonomous vehicles field experiments"
    - "simulation to scaled city zero shot policy transfer for traffic control via autonomous vehicles"
    - "flow a modular learning framework for autonomy in traffic"
    - "expert level control of ramp metering based on multi task deep reinforcement learning"
    - "robust adversarial reinforcement learning"
    - "rllib abstractions for distributed reinforcement learning"
    - "domain randomization for transferring deep neural networks from simulation to the real world"

Connected through hyperedge HE-5 (induced by source paper "thermal responses of connected hevs engine and aftertreatment systems to eco driving"):
  with members:
    - "sequential optimization of speed thermal load and power split in connected hevs"
    - "integrated optimization of power split engine thermal management and cabin heating for hybrid electric vehicles"
    - "two layer model predictive battery thermal and energy management optimization for connected and automated electric vehicles"

Connected through hyperedge HE-6 (induced by source paper "mpc based precision cooling strategy pcs for efficient thermal management of automotive air conditioning system"):
  with members:
    - "sequential optimization of speed thermal load and power split in connected hevs"
    - "model predictive climate control of connected and automated vehicles for improved energy efficiency"

Connected through hyperedge HE-7 (induced by source paper "demonstration of a time efficient mobility system using a scaled smart city"):
  with members:
    - "a fleet of miniature cars for experiments in cooperative driving"
    - "on the traffic impacts of optimally controlled connected and automated vehicles"

Connected through hyperedge HE-8 (induced by source paper "sequential optimization of speed thermal load and power split in connected hevs"):
  with members:
    - "model predictive climate control of connected and automated vehicles for improved energy efficiency"
    - "two layer model predictive battery thermal and energy management optimization for connected and automated electric vehicles"

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)