--- a/trafficintelligence/moving.py	Tue May 02 17:11:24 2023 -0400
+++ b/trafficintelligence/moving.py	Wed May 03 14:58:26 2023 -0400
@@ -398,6 +398,97 @@
             return None
 
     @staticmethod
+    def ttc_calculate(bbox_info_total_1, bbox_info_total_2):
+        """
+        :param bbox_1: list: [bbox_1 array 4*2 , v_1_x (float), v_1_y (float)]
+        :param bbox_2:  [bbox_2_x array 4*2, v_2_x (float), v_2_y (float)]
+        :return: ttc
+        """
+        from sympy import solve
+        def NewFourPoints(bbox, col_time, v_x, v_y):
+            return [i + col_time * v_x for i in bbox[0]], [j + col_time * v_y for j in bbox[1]]
+
+        bbox_1, v_1_x, v_1_y = bbox_info_total_1[0], bbox_info_total_1[1], bbox_info_total_1[2]
+        bbox_2, v_2_x, v_2_y = bbox_info_total_2[0], bbox_info_total_2[1], bbox_info_total_2[2]
+        x_bbox_1 = bbox_1[:, 0].tolist()
+        y_bbox_1 = bbox_1[:, 1].tolist()
+        bbox_1 = [x_bbox_1, y_bbox_1]
+        x_bbox_2 = bbox_2[:, 0].tolist()
+        y_bbox_2 = bbox_2[:, 1].tolist()
+        bbox_2 = [x_bbox_2, y_bbox_2]
+        t_total = []
+        line = [[0, 1], [1, 2], [2, 3], [3, 0]]
+        for i in range(4):
+            for j in range(4):
+                p0_x, p0_y = x_bbox_2[i], y_bbox_2[i]
+                p1_x, p1_y = x_bbox_1[line[j][0]], y_bbox_1[line[j][0]]
+                p2_x, p2_y = x_bbox_1[line[j][1]], y_bbox_1[line[j][1]]
+                f = (p2_x - p1_x) * (p0_y - p1_y) - (p0_x - p1_x) * (p2_y - p1_y)
+                collision_t = solve(f, t, set=True, dict=True)
+                if collision_t and collision_t[0][t] >= 0:
+                    collision_t = collision_t[0][t]
+                    print(f'collision_t: {collision_t} >>>>>>>>>')
+                    x_bbox_1_new, y_bbox_1_new = NewFourPoints(bbox_1, collision_t, v_1_x, v_1_y)
+                    x_bbox_2_new, y_bbox_2_new = NewFourPoints(bbox_2, collision_t, v_2_x, v_2_y)
+                    p0_x, p0_y = x_bbox_2_new[i], y_bbox_2_new[i]
+                    p1_x, p1_y = x_bbox_1_new[line[j][0]], y_bbox_1_new[line[j][0]]
+                    p2_x, p2_y = x_bbox_1_new[line[j][1]], y_bbox_1_new[line[j][1]]
+                    min_x, max_x = min(p1_x, p2_x), max(p1_x, p2_x)
+                    min_y, max_y = min(p1_y, p2_y), max(p1_y, p2_y)
+                    if min_x == max_x:
+                        if min_y <= p0_y <= max_y:
+                            t_total.append(collision_t)
+
+                    elif min_y == max_y:
+                        if min_x <= p0_x <= max_x:
+                            t_total.append(collision_t)
+
+                    else:
+                        if min_x <= p0_x <= max_x or min_y <= p0_y <= max_y:
+                            t_total.append(collision_t)
+                            x_temps = x_bbox_2
+                            x_bbox_2 = x_bbox_1
+                            x_bbox_1 = x_temps
+                            # print(f'Change bounding box1 and box2 >>>>>>>>>>>>>>>>>>>\n\n\n')
+        for i in range(4):
+            for j in range(4):
+                p0_x, p0_y = x_bbox_2[i], y_bbox_2[i]
+                p1_x, p1_y = x_bbox_1[line[j][0]], y_bbox_1[line[j][0]]
+                p2_x, p2_y = x_bbox_1[line[j][1]], y_bbox_1[line[j][1]]
+                f = (p2_x - p1_x) * (p0_y - p1_y) - (p0_x - p1_x) * (p2_y - p1_y)
+                collision_t = solve(f, t, set=True, dict=True)
+                if collision_t and collision_t[0][t] >= 0:
+                    collision_t = collision_t[0][t]
+                    # print(f'collision_t: {collision_t} >>>>>>>>>')
+                    x_bbox_1_new, y_bbox_1_new = NewFourPoints(bbox_1, collision_t)
+                    x_bbox_2_new, y_bbox_2_new = NewFourPoints(bbox_2, collision_t)
+                    p0_x, p0_y = x_bbox_2_new[i], y_bbox_2_new[i]
+                    p1_x, p1_y = x_bbox_1_new[line[j][0]], y_bbox_1_new[line[j][0]]
+                    p2_x, p2_y = x_bbox_1_new[line[j][1]], y_bbox_1_new[line[j][1]]
+                    min_x, max_x = min(p1_x, p2_x), max(p1_x, p2_x)
+                    min_y, max_y = min(p1_y, p2_y), max(p1_y, p2_y)
+                    if min_x == max_x:
+                        if min_y <= p0_y <= max_y:
+                            t_total.append(collision_t)
+
+                    elif min_y == max_y:
+                        if min_x <= p0_x <= max_x:
+                            t_total.append(collision_t)
+
+                    else:
+                        if min_x <= p0_x <= max_x or min_y <= p0_y <= max_y:
+                            t_total.append(collision_t)
+
+        if t_total:
+            collision_t_min = min(t_total)
+            # print(f'collision_time:')
+            # print(collision_t_min)
+        else:
+            collision_t_min = 1e7
+            # print(f'No collision')
+        return collision_t_min
+
+    @staticmethod
     def midPoint(p1, p2):
         'Returns the middle of the segment [p1, p2]'
         return Point(0.5*p1.x+0.5*p2.x, 0.5*p1.y+0.5*p2.y)

--- a/trafficintelligence/storage.py	Tue May 02 17:11:24 2023 -0400
+++ b/trafficintelligence/storage.py	Wed May 03 14:58:26 2023 -0400
@@ -1389,11 +1389,10 @@
     # ego vehicle
     t = moving.Trajectory()
     featureTrajectories = [moving.Trajectory() for i in range(4)]
-    interval = moving.TimeInterval(int(data.frame.min()), int(data.frame.max()))
+    interval = moving.TimeInterval(0, len(oxts)-1)#int(data.frame.min()), int(data.frame.max()))
     R = roty(pi/2)
-    for frame in interval:
-        _, Tr_imu_to_world = oxts[frame]
-
+    #for frame in interval:
+    for _, Tr_imu_to_world in oxts:
         l = 4.5 # m
         w = 1.8 # m
         h = 0.