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 "a look at motion planning for autonomous vehicles at an intersection"):
  Abstract: Autonomous Vehicles are currently being tested in a variety of scenarios. As we move towards Autonomous Vehicles, how should intersections look? To answer that question, we break down an intersection management into the different conundrums and scenarios involved in the trajectory planning and current approaches to solve them. Then, a brief analysis of current works in autonomous intersection is conducted. With a critical eye, we try to delve into the discrepancies of existing solutions while presenting some critical and important factors that have been addressed. Furthermore, open issues that have to be addressed are also emphasized. We also try to answer the question of how to benchmark intersection management algorithms by providing some factors that impact autonomous navigation at intersection.

Includes members:
  Member "distributed algorithm for collision avoidance at road intersections in the presence of communication failures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "analyzing traffic delay at unmanaged intersections")
  Member "high speed trajectory planning for autonomous vehicles using a simple dynamic model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "continuous time trajectory optimization for decentralized multi robot navigation")
  Member "trajectory planning under vehicle dimension constraints using sequential linear programming":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "path planning for autonomous bus driving in urban environments")
  Member "trajectory planning of automated vehicles in tube like road segments":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "automating vehicles by deep reinforcement learning using task separation with hill climbing")
  Member "optimal cooperative motion planning for vehicles at intersections":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robust multirobot coordination using priority encoded homotopic constraints")

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)