diff --git a/selfdrive/boardd/boardd.cc b/selfdrive/boardd/boardd.cc
index e037555b7b..aae2b665ae 100644
--- a/selfdrive/boardd/boardd.cc
+++ b/selfdrive/boardd/boardd.cc
@@ -40,8 +40,11 @@
 #define SAFETY_FORD 5
 #define SAFETY_CADILLAC 6
 #define SAFETY_HYUNDAI 7
+#define SAFETY_TESLA 8
+#define SAFETY_TOYOTA_IPAS 0x1335
 #define SAFETY_TOYOTA_NOLIMITS 0x1336
 #define SAFETY_ALLOUTPUT 0x1337
+#define SAFETY_ELM327 0xE327
 
 namespace {
 
diff --git a/selfdrive/car/toyota/values.py b/selfdrive/car/toyota/values.py
index 1afab157ee..d4929e7bc2 100644
--- a/selfdrive/car/toyota/values.py
+++ b/selfdrive/car/toyota/values.py
@@ -52,8 +52,8 @@ STATIC_MSGS = [
   (0x365, ECU.DSU, (CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDER), 0,  20, '\x00\x00\x00\x80\xfc\x00\x08'),
   (0x366, ECU.DSU, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.HIGHLANDERH), 0,  20, '\x00\x00\x4d\x82\x40\x02\x00'),
   (0x366, ECU.DSU, (CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDER), 0,  20, '\x00\x72\x07\xff\x09\xfe\x00'),
-  (0x470, ECU.DSU, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH), 1, 100, '\x00\x00\x02\x7a'),
-  (0x470, ECU.DSU, (CAR.HIGHLANDER, CAR.HIGHLANDERH), 1,  100, '\x00\x00\x01\x79'),
+  (0x470, ECU.DSU, (CAR.PRIUS, CAR.LEXUS_RXH), 1, 100, '\x00\x00\x02\x7a'),
+  (0x470, ECU.DSU, (CAR.HIGHLANDER, CAR.HIGHLANDERH, CAR.RAV4H), 1,  100, '\x00\x00\x01\x79'),
   (0x4CB, ECU.DSU, (CAR.PRIUS, CAR.RAV4H, CAR.LEXUS_RXH, CAR.RAV4, CAR.COROLLA, CAR.HIGHLANDERH, CAR.HIGHLANDER), 0, 100, '\x0c\x00\x00\x00\x00\x00\x00\x00'),
 
   (0x292, ECU.APGS, (CAR.PRIUS), 0,   3, '\x00\x00\x00\x00\x00\x00\x00\x9e'),
@@ -83,6 +83,10 @@ FINGERPRINTS = {
   }],
   CAR.RAV4H: [{
     36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 296: 8, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 547: 8, 548: 8, 550: 8, 552: 4, 560: 7, 562: 4, 581: 5, 608: 8, 610: 5, 643: 7, 705: 8, 713: 8, 725: 2, 740: 5, 800: 8, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 918: 7, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 3, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1005: 2, 1008: 2, 1014: 8, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1184: 8, 1185: 8, 1186: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1197: 8, 1198: 8, 1199: 8, 1212: 8, 1227: 8, 1228: 8, 1232: 8, 1235: 8, 1237: 8, 1263: 8, 1264: 8, 1279: 8, 1408: 8, 1409: 8, 1410: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1596: 8, 1597: 8, 1600: 8, 1656: 8, 1664: 8, 1728: 8, 1745: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
+  },
+  # Chinese RAV4
+  {
+    36: 8, 37: 8, 170: 8, 180: 8, 186: 4, 355: 5, 426: 6, 452: 8, 464: 8, 466: 8, 467: 8, 547: 8, 548: 8, 552: 4, 562: 4, 608: 8, 610: 5, 643: 7, 705: 8, 725: 2, 740: 5, 742: 8, 743: 8, 800: 8, 830: 7, 835: 8, 836: 8, 849: 4, 869: 7, 870: 7, 871: 2, 896: 8, 897: 8, 900: 6, 902: 6, 905: 8, 911: 8, 916: 3, 921: 8, 922: 8, 933: 8, 944: 8, 945: 8, 951: 8, 955: 8, 956: 8, 979: 2, 998: 5, 999: 7, 1000: 8, 1001: 8, 1008: 2, 1017: 8, 1041: 8, 1042: 8, 1043: 8, 1044: 8, 1056: 8, 1059: 1, 1114: 8, 1161: 8, 1162: 8, 1163: 8, 1176: 8, 1177: 8, 1178: 8, 1179: 8, 1180: 8, 1181: 8, 1190: 8, 1191: 8, 1192: 8, 1196: 8, 1207: 8, 1227: 8, 1235: 8, 1263: 8, 1279: 8, 1552: 8, 1553: 8, 1554: 8, 1555: 8, 1556: 8, 1557: 8, 1561: 8, 1562: 8, 1568: 8, 1569: 8, 1570: 8, 1571: 8, 1572: 8, 1584: 8, 1589: 8, 1592: 8, 1593: 8, 1595: 8, 1596: 8, 1597: 8, 1600: 8, 1664: 8, 1728: 8, 1745: 8, 1779: 8
   }],
   CAR.PRIUS: [{
     36: 8, 37: 8, 166: 8, 170: 8, 180: 8, 295: 8, 296: 8, 426: 6, 452: 8, 466: 8, 467: 8, 550: 8, 552: 4, 560: 7, 562: 6, 581: 5, 608: 8, 610: 8, 614: 8, 643: 7, 658: 8, 713: 8, 740: 5, 742: 8, 743: 8, 800: 8, 810: 2, 814: 8, 829: 2, 830: 7, 835: 8, 836: 8, 863: 8, 869: 7, 870: 7, 871: 2, 898: 8, 900: 6, 902: 6, 905: 8, 918: 8, 921: 8, 933: 8, 944: 8, 945: 8, 950: 8, 951: 8, 953: 8, 955: 8, 956: 8, 971: 7, 975: 5, 993: 8, 998: 5, 999: 7, 1000: 8, 1001: 8, 1014: 8, 1017: 8, 1020: 8, 1041: 8, 1042: 8, 1044: 8, 1056: 8, 1057: 8, 1059: 1, 1071: 8, 1077: 8, 1082: 8, 1083: 8, 1084: 8, 1085: 8, 1086: 8, 1114: 8, 1132: 8, 1161: 8, 1162: 8, 1163: 8, 1175: 8, 1227: 8, 1228: 8, 1235: 8, 1237: 8, 1279: 8, 1552: 8, 1553: 8, 1556: 8, 1557: 8, 1568: 8, 1570: 8, 1571: 8, 1572: 8, 1595: 8, 1777: 8, 1779: 8, 1904: 8, 1912: 8, 1990: 8, 1998: 8
diff --git a/selfdrive/controls/lib/vehicle_model.py b/selfdrive/controls/lib/vehicle_model.py
index a42b8112a7..7aac7d0a99 100755
--- a/selfdrive/controls/lib/vehicle_model.py
+++ b/selfdrive/controls/lib/vehicle_model.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python
 import numpy as np
-from numpy.linalg import inv
+from numpy.linalg import solve
 
 # dynamic bycicle model from "The Science of Vehicle Dynamics (2014), M. Guiggiani"##
 # Xdot = A*X + B*U
@@ -33,7 +33,7 @@ def kin_ss_sol(sa, u, VM):
 def dyn_ss_sol(sa, u, VM):
   # Dynamic solution, useful when speed > 0
   A, B = create_dyn_state_matrices(u, VM)
-  return - np.matmul(inv(A), B) * sa
+  return - solve(A, B) * sa
 
 
 def calc_slip_factor(VM):
@@ -87,7 +87,7 @@ class VehicleModel(object):
     # U is the matrix of the controls
     # u is the long speed
     A, B = create_dyn_state_matrices(u, self)
-    return np.matmul((A * self.dt + np.identity(2)), self.state) + B * sa * self.dt
+    return np.matmul((A * self.dt + np.eye(2)), self.state) + B * sa * self.dt
 
   def yaw_rate(self, sa, u):
     return self.calc_curvature(sa, u) * u
diff --git a/selfdrive/locationd/calibrationd.py b/selfdrive/locationd/calibrationd.py
index 523302f11a..695e698cee 100755
--- a/selfdrive/locationd/calibrationd.py
+++ b/selfdrive/locationd/calibrationd.py
@@ -30,6 +30,7 @@ EXTERNAL_PATH = os.path.dirname(os.path.abspath(__file__))
 VP_VALIDITY_CORNERS = np.array([[-150., -200.], [150., 200.]])  + VP_INIT
 GRID_WEIGHT_INIT = 2e6
 MAX_LINES = 500    # max lines to avoid over computation
+HOOD_HEIGHT = H*3/4 # the part of image usually free from the car's hood
 
 DEBUG = os.getenv("DEBUG") is not None
 
@@ -72,8 +73,15 @@ def gaussian_kernel(sizex, sizey, stdx, stdy, dx, dy):
   g = np.exp(-((x - dx)**2 / (2. * stdx**2) + (y - dy)**2 / (2. * stdy**2)))
   return g / g.sum()
 
-def blur_image(img, kernel):
-  return cv2.filter2D(img.astype(np.uint16), -1, kernel)
+def gaussian_kernel_1d(kernel):
+  #creates separable gaussian filter
+  u,s,v = np.linalg.svd(kernel)
+  x = u[:,0]*np.sqrt(s[0])
+  y = np.sqrt(s[0])*v[0,:]
+  return x, y
+
+def blur_image(img, kernel_x, kernel_y):
+  return cv2.sepFilter2D(img.astype(np.uint16), -1, kernel_x, kernel_y)
 
 def is_calibration_valid(vp):
   return vp[0] > VP_VALIDITY_CORNERS[0,0] and vp[0] < VP_VALIDITY_CORNERS[1,0] and \
@@ -89,6 +97,7 @@ class Calibrator(object):
     self.l100_last_updated = 0
     self.prev_orbs = None
     self.kernel = gaussian_kernel(11, 11, 2.35, 2.35, 0, 0)
+    self.kernel_x, self.kernel_y = gaussian_kernel_1d(self.kernel)
 
     self.vp = copy.copy(VP_INIT)
     self.cal_status = Calibration.UNCALIBRATED
@@ -127,7 +136,12 @@ class Calibrator(object):
       return
     rot_speeds = np.array([0.,0.,-yaw_rate])
     uvs[:,1,:] = denormalize(correct_pts(normalize(uvs[:,1,:]), rot_speeds, self.dt))
-    good_tracks = np.linalg.norm(uvs[:,1,:] - uvs[:,0,:], axis=1) > 10
+    # exclude tracks where:
+    # - pixel movement was less than 10 pixels
+    # - tracks are in the "hood region"
+    good_tracks = np.all([np.linalg.norm(uvs[:,1,:] - uvs[:,0,:], axis=1) > 10,
+                  uvs[:,0,1] < HOOD_HEIGHT,
+                  uvs[:,1,1] < HOOD_HEIGHT], axis = 0)
     uvs = uvs[good_tracks]
     if uvs.shape[0] > MAX_LINES:
       uvs = uvs[np.random.choice(uvs.shape[0], MAX_LINES, replace=False), :]
@@ -136,7 +150,7 @@ class Calibrator(object):
     increment_grid_c(self.grid, lines, len(lines))
     self.frame_counter += 1
     if (self.frame_counter % FRAMES_NEEDED) == 0:
-      grid = blur_image(self.grid, self.kernel)
+      grid = blur_image(self.grid, self.kernel_x, self.kernel_y)
       argmax_vp = np.unravel_index(np.argmax(grid), grid.shape)[::-1]
       self.rescale_grid()
       self.vp_unfilt = np.array(argmax_vp)
@@ -189,7 +203,7 @@ class Calibrator(object):
     self.yaw_rate = log.live100.curvature * self.speed
 
   def handle_debug(self):
-    grid_blurred = blur_image(self.grid, self.kernel)
+    grid_blurred = blur_image(self.grid, self.kernel_x, self.kernel_y)
     grid_grey = np.clip(grid_blurred/(0.1 + np.max(grid_blurred))*255, 0, 255)
     grid_color = np.repeat(grid_grey[:,:,np.newaxis], 3, axis=2)
     grid_color[:,:,0] = 0
diff --git a/selfdrive/locationd/get_vp.c b/selfdrive/locationd/get_vp.c
index 3e98f995e8..8a48c88150 100644
--- a/selfdrive/locationd/get_vp.c
+++ b/selfdrive/locationd/get_vp.c
@@ -11,7 +11,7 @@ int get_intersections(double *lines, double *intersections, long long n) {
       Dx = L1[2] * L2[1] - L1[1] * L2[2];
       Dy = L1[0] * L2[2] - L1[2] * L2[0];
       // only intersect lines from different quadrants and only left-right crossing
-      if ((D != 0) && (L1[0]*L2[0]*L1[1]*L2[1] < 0) && (L1[0]*L2[0] < 0)){
+      if ((D != 0) && (L1[0]*L2[0]*L1[1]*L2[1] < 0) && (L1[1]*L2[1] < 0)){
         x = Dx / D;
         y = Dy / D;
         if ((0 < x) &&