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Transcript of Vehicle breakdown Change in transportation requests Arrival of new transportation requests...
• Vehicle breakdown• Change in transportation requests• Arrival of new transportation requests• Disruption on infrastructure
• impact of incident• duration of incident
• Set of autonomous vehicles• Transportation infrastructure of resources• Set of transportation requests:
for each request, find a conflict-free shortest path• head-on conflicts• catching-up conflicts
• Taking into account malfunctioning vehicles and resources
Problem description
Incidents
before / after CPU Speed Performance Robustness
TR + - -
FPS + 0 -
TWGR - / 0 + - / 0• Traffic rules and zone control (TR)
• Only allow actions that can never lead to a conflict
• Fixed path scheduling (FPS)• Insert waiting times for best schedule
along pre-determined path• Job Shop Scheduling with blocking
• Time window graph routing (TWGR)• Search through graph of free time windows• Avoiding planned movements of others
• Introduce slack into routing schedules• Multi-objective routing:
• efficiency• reliability
• Robustness of planning and execution method combined
• Impact of bi-directional resources
Dest.
• Factory shop floor• Transportation order from one
machine to another• bi-directional lanes• dynamic environment
• AGV container terminal• Highly structured infrastructure• Transportation orders in large batches
• Airport taxiing• Congestion in peak hours and exceptional
weather conditions• Multi-stage routing problem• Mostly uni-directional taxiways
• Smart conflict prevention: from explicit constraintchecking to off-line encoding of constraints into freetime windows
• Complexity: from O(n2v4) to O(nv · log(nv) + n2v)• Better spread of agents over space and time results
in better performance• A*-search through graph of free time windows
Fixed Path Scheduling is very fast, but Time Window Graph Routing also finds a solution within 0.5s.
Repeated use of Fixed Path algorithms leads to overuse of key resources.Time Window Graph routing provides spread of agents over space and time.
TWGR is an optimal planning algorithm for a single-agent.
Order in which agents plan is important for individual plan quality.
For the Schiphol airport experiments, the order in which agents plan is not of great importance to system performance.
The red truck has reserved its plan. Now, the blue truck wants to plan a routeto its destination e4.
Context-Aware Logistic Routing and SchedulingAdriaan ter Mors, AlmendeJonne Zutt, Cees Witteveen, Algorithmics, Faculty of EEMCS, TU Delft
Adriaan ter Mors Jonne ZuttCees Witteveen
[email protected]@[email protected]
Gridlock
From a2 two free time windows in b2 can be reached. Only the later window can reach a free time window in c2.
a b c d e
1
2
3
4
5
The shortest-time path is to go via a5.
TWGR with heuristicTWGR no heuristicTWGR no cyclesFPS
TWGR with heuristicTWGR no heuristicTWGR no cyclesFPS
TWGR with heuristicTWGR no heuristicTWGR no cyclesFPS
TWGR with heuristicTWGR no heuristicTWGR no cyclesFPS
Example time window graph
TWGR versus FPS
Total vs. single plan quality
Example time window graph
Coping with incidents
Time window graph routing
Methods