22 Aug Reply 1: EMA model for Traffic management
Reply 1:
EMA model for Traffic management
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Exploratory Modelling and Analysis (EMA) Workbench helps in developing the computational software on complex systems so that various possible outcomes can be derived at early stage. I would like to discuss few features in smart city policy making and develop a algorithm using EMA model in Python
Smart City policy Making: Must implement latest wireless technology and utilize various internet of thing (IoT) in its development. List of services to include in policy making are Transportation, Emergency Health services, Traffic management, Schools, Shopping centers, Crime Detection, Power and Water supply, Waste management.
Python Model on Traffic management: Traffic lights will change the signal light by collecting data from GPS. GPS will help in giving real-time data feed to traffic signals so that signals can go Green as per the traffic on each side of the Road. One pre-requisite is vehicles having GPS system. While manufacturing vehicles, GPS should be included in basic model of vehicles so as to reach smart city Goals
from __future__ import (absolute_import, print_function, division,
unicode_literals)
from ema_workbench import (Model, RealParameter, ScalarOutcome, ema_logging,
perform_experiments, GPS)
#traffic signal lights use x1, x2, x3 to print traffic light
def traffic_signal(x1=None, x2=None, x3=None):
return {‘y’: x1 * x2 + x3}
if __name__ == ‘__main__’:
ema_logging.LOG_FORMAT = ‘[%(name)s/%(levelname)s/%(processName)s] %(message)s‘
ema_logging.log_to_stderr(ema_logging.INFO)
model = Model(‘simpleModel’, function=traffic_signal) # instantiate the model
# Location, speedOfVehicle, NoOfVehicles depends on Live data collected from GPS
model.uncertainties = [Location(“x1”, -0.1, 10),
SpeedOfVehicles(“x2”, 0, 100)
NoOfVehicles(“x3”, 0, 500)]
# y would be Yellow, Green or Red
model.outcomes = [ScalarOutcome(‘y’)]
results = perform_experiments(model, 100)
Expected Result: Traffic signal turns to Green by calculating the number of vehicles (NoOfVehicles), SpeedOfVehicles, Location depending on the GPS data.
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