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/Simulation/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 <[email protected]>: > 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." >
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