--- a/python/prediction.py	Tue Mar 06 23:54:10 2018 -0500
+++ b/python/prediction.py	Wed Mar 07 23:37:00 2018 -0500
@@ -264,37 +264,6 @@
         prototypeTrajectories=findPrototypes(prototypes,nMatching,objects,route,partialObjPositions,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched)
     return prototypeTrajectories
 
-def computeCrossingsCollisionsAtInstant(predictionParams,currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False):
-    '''returns the lists of collision points and crossing zones'''
-    predictedTrajectories1 = predictionParams.generatePredictedTrajectories(obj1, currentInstant)
-    predictedTrajectories2 = predictionParams.generatePredictedTrajectories(obj2, currentInstant)
-
-    collisionPoints = []
-    crossingZones = []
-    for et1 in predictedTrajectories1:
-        for et2 in predictedTrajectories2:
-            collision, t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
-            if collision:
-                collisionPoints.append(SafetyPoint((p1+p2)*0.5, et1.probability*et2.probability, t))
-            elif computeCZ: # check if there is a crossing zone
-                # TODO same computation as PET with metric + concatenate past trajectory with future trajectory
-                cz = None
-                t1 = 0
-                while not cz and t1 < timeHorizon: # t1 <= timeHorizon-1
-                    t2 = 0
-                    while not cz and t2 < timeHorizon:
-                        cz = moving.segmentIntersection(et1.predictPosition(t1), et1.predictPosition(t1+1), et2.predictPosition(t2), et2.predictPosition(t2+1))
-                        if cz is not None:
-                            deltaV= (et1.predictPosition(t1)- et1.predictPosition(t1+1) - et2.predictPosition(t2)+ et2.predictPosition(t2+1)).norm2()
-                            crossingZones.append(SafetyPoint(cz, et1.probability*et2.probability, abs(t1-t2)-(float(collisionDistanceThreshold)/deltaV)))
-                        t2 += 1
-                    t1 += 1                        
-
-    if debug:
-        savePredictedTrajectoriesFigure(currentInstant, obj1, obj2, predictedTrajectories1, predictedTrajectories2, timeHorizon)
-
-    return currentInstant, collisionPoints, crossingZones
-
 
 class PredictionParameters(object):
     def __init__(self, name, maxSpeed):
@@ -305,33 +274,60 @@
         return '{0} {1}'.format(self.name, self.maxSpeed)
 
     def generatePredictedTrajectories(self, obj, instant):
-        return []
+        return None
+
+    def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False):
+        '''returns the lists of collision points and crossing zones'''
+        predictedTrajectories1 = self.generatePredictedTrajectories(obj1, currentInstant)
+        predictedTrajectories2 = self.generatePredictedTrajectories(obj2, currentInstant)
+
+        collisionPoints = []
+        if computeCZ:
+            crossingZones = []
+        else:
+            crossingZones = None
+        for et1 in predictedTrajectories1:
+            for et2 in predictedTrajectories2:
+                collision, t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
+                if collision:
+                    collisionPoints.append(SafetyPoint((p1+p2)*0.5, et1.probability*et2.probability, t))
+                elif computeCZ: # check if there is a crossing zone
+                    # TODO same computation as PET with metric + concatenate past trajectory with future trajectory
+                    cz = None
+                    t1 = 0
+                    while not cz and t1 < timeHorizon: # t1 <= timeHorizon-1
+                        t2 = 0
+                        while not cz and t2 < timeHorizon:
+                            cz = moving.segmentIntersection(et1.predictPosition(t1), et1.predictPosition(t1+1), et2.predictPosition(t2), et2.predictPosition(t2+1))
+                            if cz is not None:
+                                deltaV= (et1.predictPosition(t1)- et1.predictPosition(t1+1) - et2.predictPosition(t2)+ et2.predictPosition(t2+1)).norm2()
+                                crossingZones.append(SafetyPoint(cz, et1.probability*et2.probability, abs(t1-t2)-(float(collisionDistanceThreshold)/deltaV)))
+                            t2 += 1
+                        t1 += 1                        
+
+        if debug:
+            savePredictedTrajectoriesFigure(currentInstant, obj1, obj2, predictedTrajectories1, predictedTrajectories2, timeHorizon)
+
+        return collisionPoints, crossingZones
 
     def computeCrossingsCollisions(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, timeInterval = None):#, nProcesses = 1):
         '''Computes all crossing and collision points at each common instant for two road users. '''
-        collisionPoints={}
-        crossingZones={}
+        collisionPoints = {}
+        if computeCZ:
+            crossingZones = {}
+        else:
+            crossingZones = None
         if timeInterval:
             commonTimeInterval = timeInterval
         else:
             commonTimeInterval = obj1.commonTimeInterval(obj2)
         #if nProcesses == 1:
         for i in list(commonTimeInterval)[:-1]: # do not look at the 1 last position/velocities, often with errors
-            i, cp, cz = computeCrossingsCollisionsAtInstant(self, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug)
+            cp, cz = self.computeCrossingsCollisionsAtInstant(i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug)
             if len(cp) != 0:
                 collisionPoints[i] = cp
-            if len(cz) != 0:
+            if computeCZ and len(cz) != 0:
                 crossingZones[i] = cz
-        # else:
-        #     pool = Pool(processes = nProcesses)
-        #     jobs = [pool.apply_async(computeCrossingsCollisionsAtInstant, args = (self, i, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ, debug)) for i in list(commonTimeInterval)[:-1]]
-        #     for j in jobs:
-        #         i, cp, cz = j.get()
-        #         if len(cp) != 0:
-        #             collisionPoints[i] = cp
-        #         if len(cz) != 0:
-        #             crossingZones[i] = cz
-        #     pool.close()
         return collisionPoints, crossingZones
 
     def computeCollisionProbability(self, obj1, obj2, collisionDistanceThreshold, timeHorizon, debug = False, timeInterval = None):
@@ -475,7 +471,10 @@
 
     def computeCrossingsCollisionsAtInstant(self, currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, *kwargs):
         collisionPoints = []
-        crossingZones = []
+        if computeCZ:
+            crossingZones = []
+        else:
+            crossingZones = None
 
         p1 = obj1.getPositionAtInstant(currentInstant)
         p2 = obj2.getPositionAtInstant(currentInstant)
@@ -518,7 +517,7 @@
             title('instant {0}'.format(currentInstant))
             axis('equal')
 
-        return currentInstant, collisionPoints, crossingZones
+        return collisionPoints, crossingZones
 
 class CVExactPredictionParameters(PredictionParameters):
     '''Prediction parameters of prediction at constant velocity
@@ -537,16 +536,16 @@
         p2 = obj2.getPositionAtInstant(currentInstant)
         v1 = obj1.getVelocityAtInstant(currentInstant)
         v2 = obj2.getVelocityAtInstant(currentInstant)
-        intersection = moving.intersection(p1, p1+v1, p2, p2+v2)
+        #intersection = moving.intersection(p1, p1+v1, p2, p2+v2)
 
-        if intersection is not None:
+        if not moving.Point.parallel(v1, v2):
             ttc = moving.Point.timeToCollision(p1, p2, v1, v2, collisionDistanceThreshold)
             if ttc is not None:
-                collisionPoints = [SafetyPoint(intersection, 1., ttc)]
+                collisionPoints = [SafetyPoint((p1+(v1*ttc)+p2+(v2*ttc))*0.5, 1., ttc)]
             else:
                 pass # compute pPET
 
-        return currentInstant, collisionPoints, crossingZones
+        return collisionPoints, crossingZones
 
 class PrototypePredictionParameters(PredictionParameters):
     def __init__(self, prototypes, nPredictedTrajectories, pointSimilarityDistance, minSimilarity, lcssMetric = 'cityblock', minFeatureTime = 10, constantSpeed = False, useFeatures = True):