|
Hi Bijal,
as I understand your code graph is
initialized like
graph =
sumolib.net.readNet('Dijkstra1.net.xml')
you can asked either for the numbers of
edges like
len(graph.getEdges())
or for the numbers of nodes like
len(graph.getNodes())
See the SUMO wiki for methods of Net
Best regards, Harald
Am 17.03.19 um 05:46 schrieb Bijal:
Thanks for answer Harald & Jakob
Actually I am trying to build adjecency matrix
using this code.
Graph class has add vertex and add edge
function.
I have added first edges and then vertex.
Plz help me to resolve the issue.
Jakob I can solve this issue by myself,But for
me python is little new.
But as per your suggestion i have tried hard to
solve issue by my self. But unfortunatly failed.
Thanks for reply once again.
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Today's Topics:
1. Re: Problem with changing lanes (Jakob Erdmann)
2. Re: Error In SumoLib Graph traversing (Harald Schaefer)
----------------------------------------------------------------------
Message: 1
Date: Sat, 16 Mar 2019 17:45:03 +0100
From: Jakob Erdmann <namdre.sumo@xxxxxxxxx>
To: Sumo project User discussions <sumo-user@xxxxxxxxxxx>
Subject: Re: [sumo-user] Problem with changing lanes
Message-ID:
<CAMbUcbxbSgB8tGkWD6VPhW+qhP68J1HSOredi83NxeON063U2w@xxxxxxxxxxxxxx>
Content-Type: text/plain; charset="utf-8"
Hello,
the issue is now fixed (https://github.com/eclipse/sumo/issues/5309).
Thanks for reporting.
Regarding the effect of the duration:
The longer duration does not change the urgency of the lane
change attempt.
Rather it controls the time after which the change attempt is
aborted if
unsuccessful.
The urgency currently only has two levels (urgent and
non-urgent) which can
be controlled using setLaneChangeMode
https://sumo.dlr.de/wiki/TraCI/Change_Vehicle_State#lane_change_mode_.280xb6.29
(bits 8 and 9 both set to 1)
regards,
Jakob
Am Fr., 15. M?rz 2019 um 18:00 Uhr schrieb H?bner, Karl <
karl.huebner@xxxxxxxxxxxxxxxxxxx>:
> Dear SUMO devs,
>
>
>
> I use changeLaneRelative(1, 3) for a vehicle for changing
its lane to the
> left. If I would do this right before an edge with more
lanes than my
> current edge, the vehicle would switch to the left as
expected but right
> after driving onto the next edge it switches back again
to the next right
> lane, since the lane index has changed. I attached an
example script
> demonstrating this behavior.
>
>
>
> This is currently a huge problem for us, do you have any
idea how to solve
> this?
>
>
>
> Another problem I have with the changeLane-command is
that with short
> durations the lane change tends to be more aggressive and
distorts upstream
> traffic. Therefore I thought I choose longer durations in
the hope that the
> lane change model has more time to do necessary safety
checks. Is this even
> the case?
>
>
>
> Thanks in advance and kind regards,
>
> Karl
>
>
> _______________________________________________
> sumo-user mailing list
> sumo-user@xxxxxxxxxxx
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Message: 2
Date: Sat, 16 Mar 2019 23:17:50 +0100
From: Harald Schaefer <fechsaer@xxxxxxxxx>
To: sumo-user@xxxxxxxxxxx
Subject: Re: [sumo-user] Error In SumoLib Graph traversing
Message-ID: <baebc87b-5d7d-39d8-f573-899893a621b6@xxxxxxxxx>
Content-Type: text/plain; charset="utf-8"
Hello Bijal
you asked for the len of a graph.
A graph consists of edges and nodes, I think you need to
specify whether
you want to get the number of edges or nodes.
Regards? Harald
Am 16.03.19 um 15:39 schrieb Jakob Erdmann:
> The error does not come from sumo but from your own
classes and I
> cannot help you with those. I advise you to find a
programmer locally
> who can guide your efforts.
> regards,
> Jakob
>
> Am Sa., 16. M?rz 2019 um 13:30?Uhr schrieb Bijal
> <bijal.varia88@xxxxxxxxx
<mailto:bijal.varia88@xxxxxxxxx>>:
>
> Dear Sir,
>
> I am trying to set graph for Ant colony algorithm
implementation.
> But I am getting Error says :?
>
> Traceback (most recent call last):
>
> ? File "hay4_ACO.py", line 317, in <module>
>
> ? ? main()
>
> ? File "hay4_ACO.py", line 278, in main
>
> ? ? aco.set_graph(Objgraph_mat)
>
> ? File "hay4_ACO.py", line 111, in set_graph
>
> ? ? self.size = len(graph)
>
> AttributeError: Graph_mat instance has no
attribute '__len__'
>
>
>
> Please help me to resolve this issue. I am new bee in
this & Some
> how i have managed to get myself up to this.
>
> *Code Is :*
> *
> *
>
>
> import os, sys
>
> import optparse
>
> import subprocess
>
> import random
>
> from Queue import PriorityQueue
>
> import xml.sax
>
> from xml.sax import saxutils, parse, make_parser,
handler
>
> from copy import copy
>
> from itertools import *
>
>
> SUMO_HOME = "/home/dhaval/sumo-1.0.0/"
>
>
> try:
>
> ? ? sys.path.append(os.path.join(SUMO_HOME,
"tools"))
>
> ? ? # import the library
>
> ? ? import sumolib
>
> ? ? from sumolib import checkBinary
>
> ? ? from sumolib.net <http://sumolib.net>
import Net
>
> ? ? from sumolib.net <http://sumolib.net>
import NetReader
>
> ? ? from sumolib.net <http://sumolib.net>
import Lane
>
> ? ? from sumolib.net <http://sumolib.net>
import Edge
>
> ? ? from sumolib.net <http://sumolib.net>
import Node
>
> ? ? from sumolib.net <http://sumolib.net>
import Connection
>
> ? ? from sumolib.net <http://sumolib.net>
import Roundabout
>
> ? ? ? ?
>
> except ImportError:
>
> ? ? sys.exit("please declare environment variable
'SUMO_HOME'
> as the root directory of your sumo installation
(it should
> contain folders 'bin', 'tools' and 'docs')")
>
>
> import random
>
> graph = sumolib.net.readNet('Dijkstra1.net.xml')
>
>
> import traci
>
> # the port used for communicating with your sumo
instance
>
> PORT = 8873
>
>
> # implementation of an undirected graph using
Adjacency
> Matrix, with weighted or unweighted edges
>
> class Vertex:
>
> def __init__(self, n):
>
> self.name
<http://self.name>
= n
>
>
> class Graph_mat:
>
> vertices = {}
>
> edges = []
>
> edge_indices = {}
>
>
> def add_vertex(self, vertex):
>
> if isinstance(vertex, Vertex) and vertex.name
> <http://vertex.name>
not in self.vertices:
>
> self.vertices[vertex.name <http://vertex.name>]
= vertex
>
> for row in self.edges:
>
> row.append(0)
>
> self.edges.append([0] * (len(self.edges)+1))
>
> self.edge_indices[vertex.name <http://vertex.name>]
=
> len(self.edge_indices)
>
> return True
>
> else:
>
> return False
>
>
> def add_edge(self, u, v, weight=1):
>
> if u in self.vertices and v in self.vertices:
>
>
self.edges[self.edge_indices[u]][self.edge_indices[v]] =
weight
>
>
self.edges[self.edge_indices[v]][self.edge_indices[u]] =
weight
>
> return True
>
> else:
>
> return False
>
> def print_graph(self):
>
> for v, i in sorted(self.edge_indices.items()):
>
> print(v + ' ')
>
> for j in range(len(self.edges)):
>
> print(self.edges[i][j])
>
> print(' ')
>
>
> class Ant():
>
>
> ? ? def __init__(self):
>
> ? ? ? ? self.cost = 0
>
> ? ? ? ? self.trace = [0]
>
>
> ? ? def start_travel(self):
>
> ? ? ? ? self.cost = 0
>
> ? ? ? ? self.trace = [0]
>
>
> ? ? def add_vertex(self, _vertex, _cost):
>
> ? ? ? ? self.trace.append(_vertex)
>
> ? ? ? ? self.cost += _cost
>
>
> ? ? def get_position(self):
>
> ? ? ? ? return self.trace[-1]
>
>
> ? ? def get_cost(self):
>
> ? ? ? ? return self.cost
>
>
> ? ? def get_path(self):
>
> ? ? ? ? path = []
>
> ? ? ? ? for i in range(len(self.trace) - 1):
>
> ? ? ? ? ? ? path.append((self.trace[i],
self.trace[i + 1]))
>
>
> ? ? ? ? return path
>
>
>
> class ACOAlgorithm():
>
> ? ? '''
>
> ? ? Ant colony optimization algorithms to find
shortest path
>
> ? ? '''
>
>
> ? ? def __init__(self):
>
> ? ? ? ? self.evaporation_rate = 0.8
>
> ? ? ? ? self.threshhold = 0.5
>
> ? ? ? ? self.remain_path = 0
>
>
> ? ? def set_graph(self, graph):
>
> ? ? ? ? self.size = len(graph)
>
>
> ? ? ? ? self.num_ant = 20*self.size ** 2
>
> ? ? ? ? self.ant = [Ant() for _ in
range(self.num_ant)]
>
>
>
> ? ? ? ? self.distance = graph
>
> ? ? ? ? self.pheromones = [[1.0]* self.size for _
in
> range(self.size)]
>
>
> ? ? ? ? max_distance = 0
>
> ? ? ? ? for i in range(len(self.distance)):
>
> ? ? ? ? ? ? for j in
range(len(self.distance[0])):
>
> ? ? ? ? ? ? ? ? if self.distance[i][j] >
max_distance:
>
> ? ? ? ? ? ? ? ? ? ? max_distance =
self.distance[i][j]
>
>
> ? ? ? ? for i in range(len(self.distance)):
>
> ? ? ? ? ? ? for j in
range(len(self.distance[0])):
>
> ? ? ? ? ? ? ? ? if self.distance[i][j] > 0:
>
> ? ? ? ? ? ? ? ? ? ? self.distance[i][j] /=
max_distance*1.0
>
> ? ? ? ? ? ? ? ? else:
>
> ? ? ? ? ? ? ? ? ? ? self.pheromones[i][j] = -1.0
>
>
> ? ? def process(self):
>
> ? ? ? ? while True:
>
> ? ? ? ? ? ? self._start_travel()
>
> ? ? ? ? ? ? self._find_edge()
>
> ? ? ? ? ? ? if self._finish_travel():
>
> ? ? ? ? ? ? ? ? break
>
>
> ? ? ? ? for i in range(self.num_ant):
>
> ? ? ? ? ? ? if len(self.ant[i].trace) ==
self.size:
>
> ? ? ? ? ? ? ? ? print 'trace %s' %
(self.ant[i].trace)
>
> ? ? ? ? ? ? ? ? break
>
>
> ? ? def _start_travel(self):
>
> ? ? ? ? for i in range(self.num_ant):
>
> ? ? ? ? ? ? self.ant[i].start_travel()
>
>
> ? ? def _find_edge(self):
>
> ? ? ? ? while not self._have_ant_completed():
>
> ? ? ? ? ? ? for i in range(len(self.ant)):
>
> ? ? ? ? ? ? ? ? available_edge = 0
>
> ? ? ? ? ? ? ? ? for e in range(self.size):
>
> ? ? ? ? ? ? ? ? ? ? if e not in self.ant[i].trace
and
> self.pheromones[self.ant[i].get_position()][e]
> 0:
>
> ? ? ? ? ? ? ? ? ? ? ? ? available_edge +=? (2.0 -
>
self.distance[self.ant[i].get_position()][e])*self.pheromones[self.ant[i].get_position()][e]
>
>
> ? ? ? ? ? ? ? ? last_e = -1
>
> ? ? ? ? ? ? ? ? prob_edge = 0
>
> ? ? ? ? ? ? ? ? prob_random = random.uniform(0.0,
1.0)
>
> ? ? ? ? ? ? ? ? for e in range(self.size):
>
> ? ? ? ? ? ? ? ? ? ? if e not in self.ant[i].trace
and
> self.pheromones[self.ant[i].get_position()][e]
> 0:
>
> ? ? ? ? ? ? ? ? ? ? ? ? prob_edge += (2.0 -
>
self.distance[self.ant[i].get_position()][e])*self.pheromones[self.ant[i].get_position()][e]/available_edge
>
> ? ? ? ? ? ? ? ? ? ? ? ? last_e = e
>
> ? ? ? ? ? ? ? ? ? ? ? ? if prob_edge >=
prob_random:
>
> ? ? ? ? ? ? ? ? ? ? ? ? ? ? break
>
> ? ? ? ? ? ? ? ? if last_e >= 0:
>
> ? ? ? ? ? ? ? ? ? ?
self.ant[i].add_vertex(last_e,
>
self.distance[self.ant[i].get_position()][last_e])
>
> ? ? ? ? ? ? ? ? else:
>
> ? ? ? ? ? ? ? ? ? ? self.ant[i].start_travel()
>
>
> ? ? def _finish_travel(self):
>
> ? ? ? ? # find short path
>
> ? ? ? ? avg_cost = 0
>
> ? ? ? ? ant_completed = 0
>
> ? ? ? ? for i in range(len(self.ant)):
>
> ? ? ? ? ? ? if len(self.ant[i].trace) ==
self.size:
>
> ? ? ? ? ? ? ? ? avg_cost +=
self.ant[i].get_cost()
>
> ? ? ? ? ? ? ? ? ant_completed += 1
>
> ? ? ? ? avg_cost /= ant_completed
>
>
> ? ? ? ? # update pheromones
>
> ? ? ? ? for i in range(len(self.pheromones)):
>
> ? ? ? ? ? ? for j in
range(len(self.pheromones[0])):
>
> ? ? ? ? ? ? ? ? if self.pheromones[i][j] > 0:
>
> ? ? ? ? ? ? ? ? ? ? self.pheromones[i][j] *= (1 -
> self.evaporation_rate)
>
>
> ? ? ? ? for i in range(len(self.ant)):
>
> ? ? ? ? ? ? if self.ant[i].get_cost() <
avg_cost:
>
> ? ? ? ? ? ? ? ? update_pheromones =
self.ant[i].get_path()
>
> ? ? ? ? ? ? ? ? for x,y in update_pheromones:
>
> ? ? ? ? ? ? ? ? ? ? self.pheromones[x][y]? +=
> avg_cost/self.ant[i].get_cost()
>
>
> ? ? ? ? # remove path has small pheromones
>
> ? ? ? ? if self.remain_path > 2*(self.size -
1):
>
> ? ? ? ? ? ? for i in range(len(self.pheromones)):
>
> ? ? ? ? ? ? ? ? for j in
range(len(self.pheromones[0])):
>
> ? ? ? ? ? ? ? ? ? ? if self.pheromones[i][j]
<= self.threshhold:
>
> ? ? ? ? ? ? ? ? ? ? ? ? self.pheromones[i][j] =
-1.0
>
> ? ? ? ? else:
>
> ? ? ? ? ? ? min_pheromones = 999999.99
>
> ? ? ? ? ? ? for i in range(len(self.pheromones)):
>
> ? ? ? ? ? ? ? ? for j in
range(len(self.pheromones[0])):
>
> ? ? ? ? ? ? ? ? ? ? if min_pheromones >
self.pheromones[i][j] > 0:
>
> ? ? ? ? ? ? ? ? ? ? ? ? min_pheromones =
self.pheromones[i][j]
>
>
> ? ? ? ? ? ? for i in range(len(self.pheromones)):
>
> ? ? ? ? ? ? ? ? for j in
range(len(self.pheromones[0])):
>
> ? ? ? ? ? ? ? ? ? ? if self.pheromones[i][j]
<= min_pheromones:
>
> ? ? ? ? ? ? ? ? ? ? ? ? self.pheromones[i][j] =
-1.0
>
>
> ? ? ? ? # check exist only one path
>
> ? ? ? ? self.remain_path = 0
>
> ? ? ? ? for i in range(len(self.pheromones)):
>
> ? ? ? ? ? ? for j in
range(len(self.pheromones[0])):
>
> ? ? ? ? ? ? ? ? if self.pheromones[i][j] > 0:
>
> ? ? ? ? ? ? ? ? ? ? self.remain_path += 1
>
>
> ? ? ? ? return self.remain_path < self.size
>
>
> ? ? def _have_ant_completed(self):
>
> ? ? ? ? for i in range(len(self.ant)):
>
> ? ? ? ? ? ? if len(self.ant[i].trace) ==
self.size:
>
> ? ? ? ? ? ? ? ? return True
>
> ? ? ? ? return False
>
>
>
>
>
> def AntColony(graph, start, end=None):
>
> ? ? ? ? D = {}# dictionary of final distances
>
> P = {}# dictionary of predecessors
>
>
>
>
> return (D,P)
>
> ? ? ? ??
>
> def shortestPath(graph, start, end):
>
> """
>
> Find a single shortest path from the given start
vertex to the
> given end vertex.
>
> The input has the same conventions as Dijkstra().
>
> The output is a list of the vertices in order
along the
> shortest path.
>
> """
>
> ? ? ? ? start = graph.getEdge(start)
>
> ? ? ? ? end = graph.getEdge(end)
>
>
> D,P = AntColony(graph, start, end)
>
> Path = []
>
>
> #while 1:
>
> #Path.append(end)
>
> #if end == start: break
>
> #end = P[end]
>
> #Path.reverse()
>
>
> return Path
>
>
> def generate_routefile():
>
> ? ? with open("dijkstra_000.rou.xml", "w") as
routes:
>
> ? ? ? ? print >> routes, """<routes>
>
> ? ? ? ? <vType id="vehicle1" accel="0.8"
decel="4.5"
> sigma="0.5" length="5" minGap="2.5"
maxSpeed="16.67"
> guiShape="passenger"/>
>
>
> ? ? ? ? <route id="1" edges="1 3 5 9" />
</routes>"""
>
> def main():
>
> ? ? traci.init(PORT)
>
> ? ? Objgraph_mat = Graph_mat()
>
> ? ? aco = ACOAlgorithm()
>
> ? ? for edge in graph.getEdges():
>
> ? ? ? ?
>
Objgraph_mat.add_vertex(Vertex(edge.getFromNode().getID()))
>
> ? ? ? ?
Objgraph_mat.add_vertex(Vertex(edge.getToNode().getID()))
>
>
>
> ? ? for edge in graph.getEdges():
>
> ? ? ? ?
Objgraph_mat.add_edge(edge.getFromNode().getID(),
> edge.getToNode().getID())
>
>
> ? ? Objgraph_mat.print_graph()
>
>
> ? ? aco.set_graph(Objgraph_mat)
>
> ? ? #aco.process()
>
> ? ? #route = shortestPath(graph, '1', '18')
>
> ? ? #for x in range(len(route)):
>
> ? ? ?#? ?print route[x],
>
>
> ? ? #edges = [str (edge.getID()) for edge in
route]
>
> ? ? #create the new route for vehicle
>
> ? ? #traci.route.add("0", edges)
>
> ? ? #assign the new route for vehicle with id
vehicle1
>
> ? ? #traci.vehicle.add("vehicle0","0")
>
> ? ? for i in range(1000):? ? #? or whatever
nulmber of steps
> you want to simulate
>
> ? ? ? ? traci.simulationStep()
>
> ? ? traci.close()
>
> ? ? sys.stdout.flush()
>
> ? ??
>
>
> def get_options():
>
> ? ? optParser = optparse.OptionParser()
>
> ? ? optParser.add_option("--nogui",
action="",
> default=False, help="run the commandline version
of sumo")
>
> ? ? options, args = optParser.parse_args()
>
> ? ? return options
>
>
>
> # this is the main entry point of this script
>
> if __name__ == "__main__":
>
> ? ? options = get_options()
>
> ? ? # this script has been called from the
command line. It
> will start sumo as a
>
> ? ? # server, then connect and run
>
> ? ? if options.nogui:
>
> ? ? ? ?sumoBinary = checkBinary('sumo')
>
> ? ? else:
>
> ? ? ? ?sumoBinary = checkBinary('sumo-gui')
>
>
> ? ? generate_routefile()
>
>
> ? ? # this is the normal way of using traci. sumo
is started as a
>
> ? ? # subprocess and then the python script
connects and runs
>
> ? ? sumoProcess = subprocess.Popen([sumoBinary,
"-c",
> "dijkstra.sumo.cfg", "--tripinfo-output",
"tripinfo.xml",
> "--remote-port", str(PORT)], stdout=sys.stdout,
stderr=sys.stderr)
>
> ? ? main()
>
> ? ? sumoProcess.wait()
>
>
> --
> *:)*
> Bijal Varia
> _______________________________________________
> sumo-user mailing list
> sumo-user@xxxxxxxxxxx
<mailto:sumo-user@xxxxxxxxxxx>
> To change your delivery options, retrieve your
password, or
> unsubscribe from this list, visit
> https://www.eclipse.org/mailman/listinfo/sumo-user
>
>
> _______________________________________________
> sumo-user mailing list
> sumo-user@xxxxxxxxxxx
> To change your delivery options, retrieve your password,
or unsubscribe from this list, visit
> https://www.eclipse.org/mailman/listinfo/sumo-user
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