Cleaned up

examples/intersection/main.py

@@ -79,11 +79,10 @@ def main(scene):
 if __name__ == "__main__":
 
     # First of first, choose the scenario
-    scene = 0       # 0 for no awareness
+    scene = 1       # 0 for no awareness
                     # 1 for intention-aware
     # Choose the instant of the view
-    step = 20       # 16: the step to show relation with the OV
+    step = 16       # 16: the step to show relation with the OV
                     # 20: the step to show relation with the pedestrian
     agents = main(scene)
-
     draw(agents, scene, step)

examples/overtaking/draw.py

@@ -1,27 +1,5 @@
 import numpy as np
-from config import initialize, visualize, record, complexity, data_dir
-
-
-def main(scene):
-
-    N = 15      # Control horizon
-
-    print("---------------------------------------------------------")
-    print('Initializing...')
-    print("---------------------------------------------------------")
-    # Initialize system and specification
-    agents, _ = initialize(scene, N)
-                # agents: the dictionary of agents
-                    # agents['ego']: ego vehicle (EV)
-                    # agents['oppo']: opponent vehicle (OV)
-
-    # Load the data of the ego agent
-    print("---------------------------------------------------------")
-    print('Loading data from' + data_dir)
-    print("---------------------------------------------------------")
-    agents['ego'].states = np.load(data_dir + '/xe_scene_' + str(scene) + '.npy')
-
-    return agents
+from config import visualize
 
 
 def draw(agents, scene):
@@ -40,27 +18,4 @@ def draw(agents, scene):
         oppo.predict(0, N)
         xo[j] = oppo.states
 
-    if True:
-        # Visualize the result
-        visualize(agents, xe[:, :N-1], xo[:, :, :N-1], scene)
-
-    if False:
-        # Record the video
-        record(agents, xe[:, :N-1], xo[:, :, :N-1], scene, fps=24)
-
-    if False:
-        # Visualize complexity analysis
-        complexity(data_dir)
-
-
-if __name__ == "__main__":
-
-    # First of first, choose the mode
-    intent = 2    # Select the intent of OV: 
-                # 0 for switching-lane
-                # 1 for slowing-down
-                # 2 for speeding-up
-
-    agents = main(intent)
-    draw(agents, intent)
-
+    visualize(agents, xe[:, :N-1], xo[:, :, :N-1], scene)

examples/overtaking/main.py

@@ -2,6 +2,7 @@
 from config import initialize, data_dir
 import os
 from commons.pce_micp_solver import PCEMICPSolver
+from draw import draw
 
 if not os.path.exists(data_dir):
     os.makedirs(data_dir)
@@ -60,15 +61,6 @@ def main(scene):
         solver.agents['ego'].apply_control(i, u_opt)
         solver.agents['oppo'].apply_control(i, solver.agents['oppo'].useq[:, i])
 
-    # Save data
-    np.save(data_dir + '/xe_scene_' + str(scene) + '.npy', solver.agents['ego'].states)
-    np.save(data_dir + '/xo_scene_' + str(scene) + '.npy', solver.agents['oppo'].pce_coefs)
-    np.save(data_dir + '/run_time_' + str(scene) + '.npy', runtime)
-
-    print("---------------------------------------------------------")
-    print('Data saved to ' + data_dir)
-    print("---------------------------------------------------------")
-
     return solver.agents
 
 
@@ -79,4 +71,6 @@ def main(scene):
                 # 0 for switching-lane
                 # 1 for slowing-down
                 # 2 for speeding-up
-    main(intent)
+
+    agents = main(intent)
+    draw(agents, intent)