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

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

3. 3 12/9/04 – Review TNO/TRAIL project #16 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

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

5. 5 12/9/04 – Review TNO/TRAIL project #16 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.

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

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

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

9. 9 12/9/04 – Review TNO/TRAIL project #16 Overview methods fixed routing rerouting Arb-c i HNZ-0 HN LPA* HNZ no planninglook-ahead strict commitments loose commitments / decommitments h i b j h i b j r k

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

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

12. 12 12/9/04 – Review TNO/TRAIL project #16 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 small difference Hypothesis: Plan-based policies outperform the simple policies

13. 13 12/9/04 – Review TNO/TRAIL project #16 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

14. 14 12/9/04 – Review TNO/TRAIL project #16 Method: agent selection functions (P1) Random Provides a baseline for the others Delays Agent with maximum wait time first Deadlines Agent with most strict deadlines first Penalties Agent with lowest planned reward first Hypo: All agent selection functions will outperform random

15. 15 12/9/04 – Review TNO/TRAIL project #16 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 increases performance but also increases computation time

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

17. 17 12/9/04 – Review TNO/TRAIL project #16 Agent selection Average sum of delivery penalties No incidents Pfail = 0.1Pfail = 0.2 0 reroutes1 reroute 0 reroutes1 reroute0 reroutes1 reroute 1.Random 2.Delays 3.Deadlines 4.Penalties 0 500 1000 1500 2000 2500 3000 3500

18. 18 12/9/04 – Review TNO/TRAIL project #16 Block size No incidents Pfail = 0.1Pfail = 0.2 011111100000111111 Average sum of delivery penalties 2246∞24∞2∞2∞6∞246∞ 1.max. number of reroutes 2.block size 0 1000 2000 3000

19. 19 12/9/04 – Review TNO/TRAIL project #16 Time for different block sizes No incidents Pfail = 0.1Pfail = 0.2 2246∞24∞2∞2∞6∞246∞ 011111100000111111 Average cpu time 0 1 2 3 4 5 6 7 1.max. number of reroutes 2.block size

20. 20 12/9/04 – Review TNO/TRAIL project #16 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 static coalitions already improve the coalition’s welfare

21. 21 12/9/04 – Review TNO/TRAIL project #16 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.

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

23. 23 12/9/04 – Review TNO/TRAIL project #16 Thesis 1.Introduction –Challenges in transportation –Problem description –Approach –Research contributions –Overview 2.A model and formalism for multi- agent transport planning –Introduction –Building blocks –Correctness criteria –Performance criteria 3.Single-agent methods for transport planning –Order allocation –Operational planning –Route planning –Simple arbiter policies –Revising priorities –Revising route –Lifelong Planning A* 4.Experiments on single-agent methods –Experimental setting –Description of the test set –Experimental results 5.Multi-agent methods for transport planning –Introduction –Coalition formation –Exchanging transportation orders –Conflict solving 6.Experiments on multi-agent methods –Experimental setting –Experimental results 7.Conclusions A.Mathematical preliminaries B.Complexity of transport planning

24. 24 12/9/04 – Review TNO/TRAIL project #16 Model Auctioneer agent Transport agent Customer agent Transport resource speed capacity max. speed capacity distance cooperative competitive

25. 25 12/9/04 – Review TNO/TRAIL project #16 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.

26. 26 12/9/04 – Review TNO/TRAIL project #16 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

27. 27 12/9/04 – Review TNO/TRAIL project #16 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.

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

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

30. 30 12/9/04 – Review TNO/TRAIL project #16 HNZ-0/1150 orders

31. 31 12/9/04 – Review TNO/TRAIL project #16 HNZ-0/1250 orders