Open ArmelliniMG opened 3 years ago
Hello,
did this tool got inhanced to solve the problem of a feeder bus for a public transport system?
Hi, as far as I know, it has not yet been implemented. @palvarezlopez please correct me if I'm wrong.
@pearlahajjar I'm not sure. @namdre can you confirm it?
No additional work has been done on the tool since @ArmelliniMG last worked on it.
@namdre @ArmelliniMG @palvarezlopez are you interested in extending this tool? We can cooperate together
Hey @pearlahajjar , I would be very interested, but I sadly no longer work in the SUMO team, so unfortunately I wouldn't be able to work on it intensively. But we can maybe find a good way of cooperating and I would be happy to support as time permits.
Thanks for making this awesome tool, and I'm looking forward to contributing to it!
Just a small note for anyone looking to run the examples:
The run.bat
file won't work on *NIX systems, you can use this instead.
python3 $SUMO_HOME/tools/drt/drtOnline.py -c test_grid_basic.sumocfg -s sumo-gui
hi python3 /usr/share/sumo/tools/drt/drtOnline.py -c test_grid_basic.sumocfg -s sumo-g ui usage: drtOnline.py [-h] [-c FILE] [-C FILE] [--save-template FILE] [-n FILE] [-r FILE] [--taxis FILE] [--sumocfg FILE] [-s {sumo,sumo-gui}] [-g FILE] [-o OUTPUT] [--darp-solver DARP_SOLVER] [--rtv-time RTV_TIME] [--ilp-time ILP_TIME] [--c-ko C_KO] [--cost-per-trip COST_PER_TRIP] [--drf DRF] [--drf-min DRF_MIN] [--max-wait MAX_WAIT] [--max-processing MAX_PROCESSING] [--sim-step SIM_STEP] [--end-time END_TIME] [--routing-algorithm {dijkstra,astar,CH,CHWrapper}] [--routing-mode ROUTING_MODE] [--dua-times] [--tracefile TRACEFILE] [--tracegetters] [-v] drtOnline.py: error: argument -v/--verbose: ignored explicit argument 'true' it dosnt work with me
Ticket for tracking the progress of the tool drtOnline.py.
The tool needs Python 3 and the ILP solver PuLP to be installed. Example scenario: shared_drt.zip
The drtOnline.py script is defined as a general scheduling module. It starts the simulation via TraCI and manages the DRT requests and fleet. This means that the module detects when a new request arrives or there are requests waiting to be served and calls the DARP solver (from darpSolver.py) to find the best route for each DRT vehicle. What makes a route the best, depends on the model of the DARP solver. The solver returns the routes to the scheduling module and it dispatches the DRT vehicles with them. If the given routes should be optimized, an ILP can be solved with the python LP solver PuLP.
Features (urgent):
[ ] Service:
[ ] Stop definition:
[ ] Vehicles attributes:
[ ] Requests attributes:
[ ] Requests time definition:
[ ] Rejection of requests
[ ] Dispatch algorithm:
[ ] Optimization:
[X] Calculation of travel times: