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Jonne Zutt Delft University of Technology Information Technology and Systems

TRAIL/TNO Project 16. Fault detection and recovery in multi-modal transportation networks with autonomous mobile actors. Jonne Zutt Delft University of Technology Information Technology and Systems Collective Agent Based Systems Group. Supervisors Dr. C. Witteveen Dr. ir. Z. Papp

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Jonne Zutt Delft University of Technology Information Technology and Systems

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  1. TRAIL/TNO Project 16 Fault detection and recovery in multi-modaltransportation networks with autonomous mobile actors Jonne Zutt Delft University of Technology Information Technology and Systems Collective Agent Based Systems Group Supervisors Dr. C. Witteveen Dr. ir. Z. Papp Dr. ir. A.J.C. van Gemund 12/9/04 – Review TNO/TRAIL project #16

  2. Contents • Transportation planning • Problem description • Progress • Methods and hypotheses • Experiments 12/9/04 – Review TNO/TRAIL project #16

  3. Issues in design and control of MHS • Guide-path design • Estimating optimal number of vehicles • Vehicle maintenance • Order allocation • Idle-vehicle positioning • Vehicle routing • Conflict-resolution 12/9/04 – Review TNO/TRAIL project #16

  4. Layers • Guide-path design • Estimating optimal number of vehicles • Vehicle maintenance • Order allocation • Idle-vehicle positioning • Vehicle routing • Conflict-resolution Strategic months Tactic hours Operational minutes 12/9/04 – Review TNO/TRAIL project #16

  5. Problem description • Design a model for operational transport planning, • Develop multi-agent routing and scheduling methods that can take into account incidents, • Search suitable performance indicators to be used in experiments for comparing the quality of different methods taking into account properties of the environment. 12/9/04 – Review TNO/TRAIL project #16

  6. Progress – previous years • Model for operational transport planning • Methods for operational transport planning taking into account incidents • Transport planning simulator 12/9/04 – Review TNO/TRAIL project #16

  7. Progress – last year • Test set • Performance indicators • Experimental results • Thesis structure • Approximately two chapters written 12/9/04 – Review TNO/TRAIL project #16

  8. Progress – future work • Complete single-agent experiments [December’04] • Coordination experiments [February’05] • Writing [June’05] 12/9/04 – Review TNO/TRAIL project #16

  9. Overview methods LPA* HNZ rerouting hi bj rk loose commitments/ decommitments HNZ-0 HN hi bj fixed routing Arb-ci strictcommitments no planning look-ahead 12/9/04 – Review TNO/TRAIL project #16

  10. Conflicts 1. Resources have limited capacity A B C D B A Time 2. Instantaneous exchange A B C B A D Time 12/9/04 – Review TNO/TRAIL project #16

  11. About cycles and deadlocks K(A)=1 A A B C B History: F,E,D,CCurrent: B,A P(K_sema_C)V(K_sema_B) 12/9/04 – Review TNO/TRAIL project #16

  12. Methods – Simple/plan-based arbiter policies • First-In-First-Out • Agent priority • Longest-Queue-First • Longest-Queue-First-Inc • Longest-Plan-First • Most-Urgent-Deadline-First • Max-Reward-Decrease-First • Max-Reward-Decrease-Queue-First Hypothesis:No/very smalldifference Hypothesis:Plan-based policies outperform the simple policies 12/9/04 – Review TNO/TRAIL project #16

  13. Methods – HNZ • Wait for a change in plan(s) • While agents are not ready • Compute traffic-aware shortest path • Agent compete who schedules first (P1) • Winner schedules n resources (P2) • If current order rewards are below threshold, agent tries to reroute (P3) Hypothesis: Much better than no planning Hypothesis:Rerouting most important par 12/9/04 – Review TNO/TRAIL project #16

  14. Method: agent selection functions (P1) • RandomProvides a baseline for the others • DelaysAgent with maximum wait time first • DeadlinesAgent with most strict deadlines first • PenaltiesAgent with lowest planned reward first Hypo: All agent selection functions will outperform random 12/9/04 – Review TNO/TRAIL project #16

  15. Method: resource block-size (P2) • How many resources (fraction of route) are scheduled after the agent is selected by the agent selection function? Hypothesis:A smaller block-size slightly increasesperformance but also increases computation time 12/9/04 – Review TNO/TRAIL project #16

  16. Tardiness Average % of delay Number of alternatives Number of alternatives Number of reroute opportunities Delay  { aA (Ca – Ma) / Ca } / |A| Tardiness aA Ca - a if Ca> a 12/9/04 – Review TNO/TRAIL project #16

  17. Agent selection • Random • Delays • Deadlines • Penalties 0 500 1000 1500 2000 2500 3000 3500 Average sum of delivery penalties 0 reroutes 1 reroute 0 reroutes 1 reroute 0 reroutes 1 reroute No incidents Pfail = 0.1 Pfail = 0.2 12/9/04 – Review TNO/TRAIL project #16

  18. Block size • max. number of reroutes • block size Average sum of delivery penalties 0 1000 2000 3000 0 0 1 1 1 1 0 0 1 1 1 1 0 0 1 1 1 1 2 ∞ 2 4 6 ∞ 2 ∞ 2 4 6 ∞ 2 ∞ 2 4 6 ∞ No incidents Pfail = 0.1 Pfail = 0.2 12/9/04 – Review TNO/TRAIL project #16

  19. Time for different block sizes • max. number of reroutes • block size 0 1 2 3 4 5 6 7 Average cpu time 0 0 1 1 1 1 0 0 1 1 1 1 0 0 1 1 1 1 2 ∞ 2 4 6 ∞ 2 ∞ 2 4 6 ∞ 2 ∞ 2 4 6 ∞ No incidents Pfail = 0.1 Pfail = 0.2 12/9/04 – Review TNO/TRAIL project #16

  20. Coordination – Coalition Formation • Static • Different companies • Dynamic • Based on current position • Based on source/destination locations, or plan distance function • Grouped orders Hypothesis:Dynamic coalitions are preferable, though staticcoalitions already improve the coalition’s welfare 12/9/04 – Review TNO/TRAIL project #16

  21. Coordination – How to improve welfare? • Exchange orders with coalition members (cf. simulated trading) • Conflict-resolution:In case of a conflict, determine Δ(C) instead of Δ(A) to determine who wins. 12/9/04 – Review TNO/TRAIL project #16

  22. Questions • CABS project:http://cabs.ewi.tudelft.nl • My homepage: http://dutiih.twi.tudelft.nl/~jonne • My email: j.zutt@ewi.tudelft.nl 12/9/04 – Review TNO/TRAIL project #16

  23. Introduction Challenges in transportation Problem description Approach Research contributions Overview A model and formalism for multi-agent transport planning Introduction Building blocks Correctness criteria Performance criteria Single-agent methods for transport planning Order allocation Operational planning Route planning Simple arbiter policies Revising priorities Revising route Lifelong Planning A* Experiments on single-agent methods Experimental setting Description of the test set Experimental results Multi-agent methods for transport planning Introduction Coalition formation Exchanging transportation orders Conflict solving Experiments on multi-agent methods Experimental setting Experimental results Conclusions Mathematical preliminaries Complexity of transport planning Thesis 12/9/04 – Review TNO/TRAIL project #16

  24. Model Customeragent Auctioneeragent max. speed capacity distance Transportagent Transportagent Transportagent cooperative competitive Transportresource Transportresource Transportresource speed capacity 12/9/04 – Review TNO/TRAIL project #16

  25. Model: incidents • Events that disrupt regular plan execution and generally require re-planning • Examples: customers that change or retract transportation orders, unpredictable congestion, vehicle break-down, communication failure • Incidents are generated proportional to the resources. Pfail = 0.x means each resources is expected to fail x·10% of the time. 12/9/04 – Review TNO/TRAIL project #16

  26. Method: traffic-aware shortest path • Agents know which time-windows are in use by other agents per resource • Run an A* algorithm: store routes on open list, check for conflict when appending to candidate route • Process is guaranteed to terminate and find the traffic-aware shortest path 12/9/04 – Review TNO/TRAIL project #16

  27. Experiments • 10 transport networks with 25 resources, ‘random’ topology. • 10 sets of transportation orders with 250 random orders each • 2 different sets of agents with 25 randomly located agents each • Incidents with failure probability 0, 0.1, …, 1.0 and impact 0.1. 12/9/04 – Review TNO/TRAIL project #16

  28. Blocktime 12/9/04 – Review TNO/TRAIL project #16

  29. Simple arbiter policies 12/9/04 – Review TNO/TRAIL project #16

  30. HNZ-0/1 150 orders 12/9/04 – Review TNO/TRAIL project #16

  31. HNZ-0/1 250 orders 12/9/04 – Review TNO/TRAIL project #16

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