Hi Jakon, is it possible to change the algorithm used by cars to find the destination path?
Thanks. 2018-02-09 7:50 GMT-02:00 Jakob Erdmann <[email protected]>: > It may be helpful to read this documentation for a comprehensive > explanation of the different routing and rerouting facilities: > http://sumo.dlr.de/wiki/Simulation/Routing > > 2018-01-16 21:40 GMT+01:00 Michael Behrisch <[email protected]>: > >> Hi Pedro, >> if you are using TraCI then you can set the weight (traveltime) for the >> edge directly >> http://sumo.dlr.de/pydoc/traci._edge.html#EdgeDomain-adaptTraveltime but >> then you would also need to trigger the rerouting via TraCI. But if you >> need to run a lot of simulations (as you probably will when doing ML) >> you might not wish to use TraCI because it slows down the simulation >> considerably. >> >> Best regards >> Michael >> >> Am 16.01.2018 um 15:32 schrieb Pedro Matuck: >> > Hi Michael, >> > >> > I believe that you answered my question unintentionally. >> > >> > In summary the cars will always looking for the fastast way, correct? >> > So, everything that affect this will change the car decision: >> > Traffic Jam >> > Lane Max Speed >> > Edge Length >> > >> > There're anything else that I could change via TraCi to affect this >> > situation? >> > >> > For my pourposes, the car sensitiveness is helpful because I don't need >> > to worry with them, just change the network status in order to increase >> > the number of arrived cars. The Machine Learn should learn the best >> > situation by itself, considering all variables. However, in order the >> > accelerate the learning process, I can use some heuristics to help the >> > ML choose better actions faster. >> > >> > Thank you again. >> > >> > >> > 2018-01-16 4:15 GMT-02:00 Michael Behrisch <[email protected] >> > <mailto:[email protected]>>: >> > >> > Hi Pedro, >> > yes the cars use Dijkstra. The grid may be not the best network to >> test >> > this because all the edges have the same length and it is thus very >> > sensitive already to small changes. >> > >> > Best regards, >> > Michael >> > >> > Am 15.01.2018 um 15:52 schrieb Pedro Matuck: >> > > Hi Michael, thank you for the return. I'll try to be more clear >> and >> > > specific. >> > > >> > > I'm working in a Machine Learning that should help the traffic >> flow. In >> > > summary, I configured a flow to start at some point of network >> and the >> > > cars should arrive at the destination. In the middle of that, I >> > > calculate the number of arrived cars and take an action after >> some fixed >> > > number of steps. >> > > >> > > What I'm trying to do, is (as you said before) influence the >> travel time >> > > changing the network aspects. For instance: At some point of >> simulation, >> > > if some lane is with high occupancy, I decrease it 'MaxSpeed' in >> order >> > > to make other lanes more interesting for the new inserted cars. >> > > >> > > Correct me if I missunderstood, but cars use dijkstra to >> calculate the >> > > fastest way, right? I just need to understand the conditions that >> affect >> > > the weight of lanes to train my ML in a simple scenario: it >> involves >> > > just single lanes, one type of cars and a grid network generated >> by >> > > 'netgenerate' (3x3 or 4x4 nodes). >> > > >> > > Thank you again. >> > > >> > > 2018-01-14 17:44 GMT-02:00 Michael Behrisch <[email protected] >> <mailto:[email protected]> >> > > <mailto:[email protected] <mailto:[email protected]>>>: >> > > >> > > Hi, >> > > the short answer is it takes the fastest route based on the >> > current >> > > travel times in the network (this describes the edge part, the >> > lane part >> > > is handled by the lane changing algorithm). There are multiple >> > ways to >> > > influence which travel times it assumes when calculating the >> > fastest >> > > path but maybe you can ask a more specific question here. >> > > >> > > Best regards, >> > > Michael >> > > >> > > Am 13.01.2018 um 03:02 schrieb Pedro Matuck: >> > > > Hello, >> > > > >> > > > Please, someone could indicate me the documentation where >> > explain how >> > > > cars make a decision when we just declare a flow? >> > > > >> > > > For example: >> > > > I have the following declaration on my *.rou.xml file >> > > > >> > > > <routes xmlns:xsi="http://www.w3.org/2 >> 001/XMLSchema-instance >> > <http://www.w3.org/2001/XMLSchema-instance> >> > > <http://www.w3.org/2001/XMLSchema-instance >> > <http://www.w3.org/2001/XMLSchema-instance>>" >> > > > >> > xsi:noNamespaceSchemaLocation="http://sumo.dlr.de/xsd/routes_ >> file.xsd <http://sumo.dlr.de/xsd/routes_file.xsd> >> > > <http://sumo.dlr.de/xsd/routes_file.xsd >> > <http://sumo.dlr.de/xsd/routes_file.xsd>>"> >> > > > <vType id="normal car" vClass="passenger" maxSpeed="40" >> > > > speedFactor="0.9" speedDev="0.2" sigma="0.5" color="1,0,0"/> >> > > > *<flow id="normal" type="normal car" begin="0" >> probability="0.2" >> > > > from="0/0to1/0" to="1/2to2/2"/>* >> > > > </routes> >> > > > >> > > > After a car is inserted on network, how it makes a decision >> > for which >> > > > edge/lane it should take in order to get the destination? >> > > > >> > > > I read about weights, routing and randomness but nothing >> > were clear enough. >> > > > >> > > > Thanks. >> > > > >> > > > -- >> > > > */Pedro J. Matuck/* >> > > > Github <https://github.com/pjmatuck> - Linkedin >> > > > <https://www.linkedin.com/in/pedro-matuck-79324323 >> > <https://www.linkedin.com/in/pedro-matuck-79324323> >> > > <https://www.linkedin.com/in/pedro-matuck-79324323 >> > <https://www.linkedin.com/in/pedro-matuck-79324323>>> - Youtube >> > > > <http://www.youtube.com/c/AbreChaves >> > <http://www.youtube.com/c/AbreChaves> >> > > <http://www.youtube.com/c/AbreChaves >> > <http://www.youtube.com/c/AbreChaves>>> >> > > > >> > > > "The hardest battle lies within." >> > > > >> > > > >> > > > _______________________________________________ >> > > > sumo-user mailing list >> > > > [email protected] <mailto:[email protected]> >> > <mailto:[email protected] <mailto:[email protected]>> >> > > > To change your delivery options, retrieve your password, or >> > > unsubscribe from this list, visit >> > > > https://dev.eclipse.org/mailman/listinfo/sumo-user >> > <https://dev.eclipse.org/mailman/listinfo/sumo-user> >> > > <https://dev.eclipse.org/mailman/listinfo/sumo-user >> > <https://dev.eclipse.org/mailman/listinfo/sumo-user>> >> > > > >> > > >> > > >> > > >> > > >> > > >> > > -- >> > > */Pedro J. Matuck/* >> > > Github <https://github.com/pjmatuck> - Linkedin >> > > <https://www.linkedin.com/in/pedro-matuck-79324323 >> > <https://www.linkedin.com/in/pedro-matuck-79324323>> - Youtube >> > > <http://www.youtube.com/c/AbreChaves >> > <http://www.youtube.com/c/AbreChaves>> >> > > >> > > "The hardest battle lies within." >> > >> > >> > >> > >> > >> > -- >> > */Pedro J. Matuck/* >> > Github <https://github.com/pjmatuck> - Linkedin >> > <https://www.linkedin.com/in/pedro-matuck-79324323> - Youtube >> > <http://www.youtube.com/c/AbreChaves> >> > >> > "The hardest battle lies within." >> >> >> >> _______________________________________________ >> sumo-user mailing list >> [email protected] >> To change your delivery options, retrieve your password, or unsubscribe >> from this list, visit >> https://dev.eclipse.org/mailman/listinfo/sumo-user >> >> > -- *Pedro J. Matuck* Github <https://github.com/pjmatuck> - Linkedin <https://www.linkedin.com/in/pedro-matuck-79324323> - Youtube <http://www.youtube.com/c/AbreChaves> "The hardest battle lies within."
_______________________________________________ sumo-user mailing list [email protected] To change your delivery options, retrieve your password, or unsubscribe from this list, visit https://dev.eclipse.org/mailman/listinfo/sumo-user
