traci_output.py

import os
import traci
import matplotlib.pyplot as plt
import sys
sys.path.append("D:/Program_WorkApplication/Eclipse/Sumo/tools")
import pandas as pd
import xml2csv


# create an output file
output_file = open("output/output.xml", "w")
# write the header of the output file
output_file.write("<fcd-export>\n")

# set the path of sumo binary
sumoBinary = "sumo-gui"
sumoCmd = [sumoBinary, "-c", "sumo.cfg"]

# start the simulation
traci.start(sumoCmd)

# get the list of all vehicles
all_vehicles = traci.vehicle.getIDList()

# create empty dictionaries to store the speed, acceleration and position of each vehicle
speed_dict = {}
accel_dict = {}
pos_dict = {}

# initialize the dictionaries with empty lists for each vehicle
for v in all_vehicles:
    speed_dict[v] = []
    accel_dict[v] = []
    pos_dict[v] = []

# set the simulation step length
step_length = 0.1

# run the simulation for 1000 steps
for i in range(1000):
    # advance the simulation by one step
    traci.simulationStep()

    # loop through all vehicles
    for v in all_vehicles:
        # get the current speed, acceleration and position of the vehicle
        speed = traci.vehicle.getSpeed(v)
        accel = traci.vehicle.getAcceleration(v)
        pos = traci.vehicle.getPosition(v)

        # append the values to the corresponding lists in the dictionaries
        speed_dict[v].append(speed)
        accel_dict[v].append(accel)
        pos_dict[v].append(pos)
    
    # get the current time step
    time = traci.simulation.getTime()
    # write the time step to the output file
    output_file.write("<timestep time=\"%s\">\n" % time)
    # get all vehicles in the simulation
    vehicles = traci.vehicle.getIDList()
    # loop over all vehicles
    for vehicle in vehicles:
        # get the vehicle's position, speed, angle, etc.
        x, y = traci.vehicle.getPosition(vehicle)
        speed = traci.vehicle.getSpeed(vehicle)
        angle = traci.vehicle.getAngle(vehicle)
        # write the vehicle's information to the output file
        output_file.write("<vehicle id=\"%s\" x=\"%s\" y=\"%s\" speed=\"%s\" angle=\"%s\"/>\n" % (vehicle, x, y, speed, angle))
    # write the end of the time step to the output file
    output_file.write("</timestep>\n")

# close the simulation
traci.close()

# create a folder to store the output files
output_folder = "output"
if not os.path.exists(output_folder):
    os.makedirs(output_folder)

# loop through all vehicles
for v in all_vehicles:
    # plot the speed, acceleration and position of the vehicle over time
    plt.figure(figsize=(10, 10))
    plt.subplot(3, 1, 1)
    plt.plot(speed_dict[v])
    plt.xlabel("Time (s)")
    plt.ylabel("Speed (m/s)")
    plt.title(f"Speed of vehicle {v}")

    plt.subplot(3, 1, 2)
    plt.plot(accel_dict[v])
    plt.xlabel("Time (s)")
    plt.ylabel("Acceleration (m/s^2)")
    plt.title(f"Acceleration of vehicle {v}")

    plt.subplot(3, 1, 3)
    plt.plot([p[0] for p in pos_dict[v]], [p[1] for p in pos_dict[v]])
    plt.xlabel("X (m)")
    plt.ylabel("Y (m)")
    plt.title(f"Position of vehicle {v}")

    # save the plot as an image file in the output folder
    plt.savefig(os.path.join(output_folder, f"{v}.png"))

    # create a data frame with the speed, acceleration and position of the vehicle over time
    df = pd.DataFrame({"speed": speed_dict[v], "acceleration": accel_dict[v], "x": [p[0] for p in pos_dict[v]], "y": [p[1] for p in pos_dict[v]]})

    # save the data frame as a csv file in the output folder
    df.to_csv(os.path.join(output_folder, f"{v}.csv"), index=False)

# write the end of the output file
output_file.write("</fcd-export>\n")
# close the output file
output_file.close()
xml2csv(output,output,1)