human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "autonomous vehicles meet the physical world rss variability uncertainty and proving safety expanded version"):
  Abstract: The Responsibility-Sensitive Safety (RSS) model offers provable safety for vehicle behaviors such as minimum safe following distance. However, handling worst-case variability and uncertainty may significantly lower vehicle permissiveness, and in some situations safety cannot be guaranteed. Digging deeper into Newtonian mechanics, we identify complications that result from considering vehicle status, road geometry and environmental parameters. An especially challenging situation occurs if these parameters change during the course of a collision avoidance maneuver such as hard braking. As part of our analysis, we expand the original RSS following distance equation to account for edge cases involving potential collisions mid-way through a braking process. We additionally propose a Micro-Operational Design Domain ({\mu}ODD) approach to subdividing the operational space as a way of improving permissiveness. Confining probabilistic aspects of safety to {\mu}ODD transitions permits proving safety (when possible) under the assumption that the system has transitioned to the correct {\mu}ODD for the situation. Each {\mu}ODD can additionally be used to encode system fault responses, take credit for advisory information (e.g., from vehicle-to-vehicle communication), and anticipate likely emergent situations.

Includes members:
  Member "towards a framework to manage perceptual uncertainty for safe automated driving":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adapting square for quality assessment of artificial intelligence systems")
  Member "tackling occlusions limited sensor range with set based safety verification":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "tackling existence probabilities of objects with motion planning for automated urban driving")
  Member "ontology based scene creation for the development of automated vehicles":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning modulated loss for rotated object detection")
  Member "on a formal model of safe and scalable self driving cars":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "training adversarial agents to exploit weaknesses in deep control policies")
  Member "a sequential two step algorithm for fast generation of vehicle racing trajectories":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "adaptive trajectory planning and optimization at limits of handling")
  Member "visualizing deep convolutional neural networks using natural pre images":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "grad cam visual explanations from deep networks via gradient based localization")

Question: Please tell me which class the source paper 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.RO(Robotics)