Jakob, Grateful with the support so far. :)
these two parameters are enought to guarantee that all cars will have the reroute devices and the "edges choice" will be randomly? <routing> <weights.random-factor value="10"/> <device.rerouting.probability value="1.0"/> </routing> Another question... I didn't understand the parameter for weights.random-factor. What is the difference if I set '10' or '1000'? Thank you. 2018-03-08 4:37 GMT-03:00 Jakob Erdmann <namdre.s...@googlemail.com>: > you can get stochasticity into the routing decisions by setting the option > --weights.randomFactor. > If you make that value large you should be able to elicit aribtrary turns. > The option only takes effect when vehicles are equipped with a rerouting > device and perform periodic rerouting. See http://sumo.dlr.de/wiki/ > Demand/Automatic_Routing > > 2018-03-08 0:01 GMT+01:00 Pedro Matuck <pjmat...@gmail.com>: > >> Jakob, >> >> there're any option where I can set the cars to choose the route based on >> a stochastic way (or randomly)? (Example: As soon as it reach some >> junction, the car could pick any way.) >> >> I can't assume that cars knows all the network status. >> >> Thanks >> >> 2018-03-02 3:41 GMT-03:00 Jakob Erdmann <namdre.s...@googlemail.com>: >> >>> Yes. >>> - you can change the algorithm using option --routing.algorithm ( >>> http://sumo.dlr.de/wiki/Simulation/Routing#Routing_Algorithms) >>> - you can change the assumed travel time values for each edge to affect >>> the choice of fastest route (http://sumo.dlr.de/wiki/Simul >>> ation/Routing#Travel-time_values_for_routing) >>> - you can set another objective function (i.e. routing to minimize CO2 >>> emissions) (http://sumo.dlr.de/wiki/Simulation/Routing#Routing_by_effort >>> ) >>> >>> regards, >>> Jakob >>> >>> 2018-03-02 0:11 GMT+01:00 Pedro Matuck <pjmat...@gmail.com>: >>> >>>> 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 <namdre.s...@googlemail.com>: >>>> >>>>> 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 <o...@behrisch.de>: >>>>> >>>>>> 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 <o...@behrisch.de >>>>>> > <mailto:o...@behrisch.de>>: >>>>>> > >>>>>> > 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 <o...@behrisch.de >>>>>> <mailto:o...@behrisch.de> >>>>>> > > <mailto:o...@behrisch.de <mailto:o...@behrisch.de>>>: >>>>>> > > >>>>>> > > 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/route >>>>>> s_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 >>>>>> > > > sumo-user@eclipse.org <mailto:sumo-user@eclipse.org> >>>>>> > <mailto:sumo-user@eclipse.org <mailto:sumo-user@eclipse.org>> >>>>>> > > > 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 >>>>>> sumo-user@eclipse.org >>>>>> 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." >>>> >>> >>> >> >> >> -- >> *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." >> > > -- *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."
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