Conflict Resolution in Free-Ranging Multivehicle Systems: A Resource Allocation Paradigm

We propose a novel paradigm for conflict resolution in multivehicle traffic systems, where a number of mobile agents move freely in a finite area, with each agent following a prespecified-motion profile. The key idea behind the proposed method is the tessellation of the underlying motion area in a number of cells and the treatment of these cells as resources that must be acquired by the mobile agents for the execution of their motion profiles, according to an appropriate resource allocation protocol. We capitalize upon the existing literature on the real-time management of sequential resource allocation systems (RASs) and develop such protocols that can formally guarantee the safe and live operation of the underlying traffic system, while they remain scalable with respect to the number of the moving agents. Collective past experience with the considered policies indicates that they also provide a pretty large coverage of the RAS behavioral space that characterizes its safe and live operation. Finally, we also establish that the aforementioned approach is applicable even in traffic systems where all vehicles must be in perpetual motion until their retirement.

[1]  Howie Choset,et al.  Flow-Through Policies for Hybrid Controller Synthesis Applied to Fully Actuated Systems , 2009, IEEE Transactions on Robotics.

[2]  Javier Martínez,et al.  A Petri net based deadlock prevention policy for flexible manufacturing systems , 1995, IEEE Trans. Robotics Autom..

[3]  Fabrice R. Noreils.  Integrating multirobot coordination in a mobile-robot control system , 1990, EEE International Workshop on Intelligent Robots and Systems, Towards a New Frontier of Applications.

[4]  Spyros A. Reveliotis,et al.  On the Liveness of Guidepath-Based, Zone-Controlled Dynamically Routed, Closed Traffic Systems , 2008, IEEE Transactions on Automatic Control.

[5]  Jing Wang,et al.  Distributed traffic regulation and control for multiple autonomous mobile robots operating in discrete space , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[6]  Spyros A. Reveliotis,et al.  Conflict resolution in multi-vehicle systems: A resource allocation paradigm , 2008, 2008 IEEE International Conference on Automation Science and Engineering.

[7]  Spyros A. Reveliotis,et al.  Deadlock avoidance policies for automated manufacturing cells , 1996, IEEE Trans. Robotics Autom..

[8]  James K. Kuchar,et al.  A review of conflict detection and resolution modeling methods , 2000, IEEE Trans. Intell. Transp. Syst..

[9]  Elzbieta Roszkowska.  Provably Correct Closed-Loop Control for Multiple Mobile Robot Systems , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[10]  Steven M. LaValle,et al.  Optimal motion planning for multiple robots having independent goals , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[11]  Jonghun Park.  A deadlock and livelock free protocol for decentralized Internet resource coallocation , 2004, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[12]  Spyros A. Reveliotis,et al.  On the Complexity of Maximally Permissive Deadlock Avoidance in Multi-Vehicle Traffic Systems , 2010, IEEE Transactions on Automatic Control.

[13]  Kees M. van Hee,et al.  Workflow Management: Models, Methods, and Systems , 2002, Cooperative information systems.

[14]  Elzbieta Roszkowska,et al.  A Maximally Permissive Distributed Protocol for Motion Coordination in Free-Range Vehicular Systems , 2011 .

[15]  C. Tomlin,et al.  Decentralized optimization, with application to multiple aircraft coordination , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[16]  Avenir Kobetski.  Optimal Coordination of Flexible Manufacturing Systems, with Automatic Generation of Collision- and Dealock-Free Working Schedule , 2008 .

[17]  Arie Shoshani,et al.  System Deadlocks , 1971, CSUR.

[18]  Christos G. Cassandras,et al.  Introduction to Discrete Event Systems , 1999, The Kluwer International Series on Discrete Event Dynamic Systems.

[19]  Dimos V. Dimarogonas,et al.  A feedback stabilization and collision avoidance scheme for multiple independent non-point agents, , 2006, Autom..

[20]  Richard C. Holt,et al.  Some deadlock properties of computer systems , 1971, SOSP '71.

[21]  Elzbieta Roszkowska.  High-Level Motion Control for Workspace Sharing Mobile Robots , 2007, RoMoCo.

[22]  Spyros Reveliotis.  Real-time management of resource allocation systems : a discrete event systems approach , 2004 .

[23]  Antonio Bicchi,et al.  Decentralized Cooperative Policy for Conflict Resolution in Multivehicle Systems , 2007, IEEE Transactions on Robotics.

[24]  Bruce H. Krogh,et al.  Deadlock avoidance in flexible manufacturing systems with concurrently competing process flows , 1990, IEEE Trans. Robotics Autom..

[25]  Bernhard Nebel,et al.  Decentralized collision avoidance, deadlock detection, and deadlock resolution for multiple mobile robots , 2001, Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180).

[26]  Calin Belta,et al.  Discrete abstractions for robot motion planning and control in polygonal environments , 2005, IEEE Transactions on Robotics.

[27]  Yunhui Liu,et al.  A practical algorithm for planning collision-free coordinated motion of multiple mobile robots , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[28]  John Lygeros,et al.  Verified hybrid controllers for automated vehicles , 1998, IEEE Trans. Autom. Control..

[29]  S. Shankar Sastry,et al.  Conflict resolution for air traffic management: a study in multiagent hybrid systems , 1998, IEEE Trans. Autom. Control..

[30]  Maria Pia Fanti,et al.  Event-based feedback control for deadlock avoidance in flexible production systems , 1997, IEEE Trans. Robotics Autom..

[31]  S. Reveliotis.  Conflict resolution in AGV systems , 2000 .

[32]  Yi Li,et al.  Motion Planning of Multiple Agents in Virtual Environments using Coordination Graphs , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[33]  Antonio Bicchi,et al.  On optimal cooperative conflict resolution for air traffic management systems , 2000, IEEE Trans. Intell. Transp. Syst..

[34]  Edsger W. Dijkstra,et al.  Cooperating sequential processes , 2002 .

[35]  Steven M. LaValle,et al.  Optimal motion planning for multiple robots having independent goals , 1998, IEEE Trans. Robotics Autom..

[36]  S. Lafortune.  Supervisory Control Of Discrete Event Systems , 2011 .

[37]  Maria Pia Fanti,et al.  Event-based controller to avoid deadlock and collisions in zone-control AGVS , 2002 .