Transportation model: defining the generator
Well done; you have defined your model inputs and outputs and the model processes you characterized using Python methods. Now, it's time to put a generator together that will sequence all your model processes.
Este exercício faz parte do curso
Discrete Event Simulation in Python
Instruções do exercício
- Call the function
road_travel()created before, which calculates the road travel time, and clock in the time it takes to complete it. - Call the function
wait_traffic_light()created before, which calculates the waiting time at traffic lights, and clock in the time it takes to complete it.
Exercício interativo prático
Experimente este exercício completando este código de exemplo.
def all_processes(env, inputs):
road_stretch, distance_total, traffic_light = 0, 0, 0
while True:
road_stretch += 1
# Call function calculates road travel time
distance, distance_total = ____(inputs, distance_total)
yield env.____(distance/inputs['Speed_limit_ms'])
print(f"> Road Stretch #{road_stretch} \nLength = {distance} m , Cumulative distance travelled = {distance_total} m , Total time elapsed = {env.now} sec")
traffic_light += 1
# Call function that calculates waiting time at a traffic light
waitTime_traffic_light_sec = ____(inputs, distance_total)
yield env.____(waitTime_traffic_light_sec)
print(f"> Traffic Light #{traffic_light} \nWait time = {waitTime_traffic_light_sec} sec, Time lapsed = {env.now} sec")