--- a/python/prediction.py	Mon May 18 13:53:25 2015 +0200
+++ b/python/prediction.py	Mon May 18 17:17:06 2015 +0200
@@ -140,15 +140,21 @@
         return sum([p.indicator*p.probability for p in points])/sum([p.probability for p in points])
 
 def computeCollisionTime(predictedTrajectory1, predictedTrajectory2, collisionDistanceThreshold, timeHorizon):
-    '''Computes the first instant at which two predicted trajectories are within some distance threshold'''
+    '''Computes the first instant 
+    at which two predicted trajectories are within some distance threshold
+    Computes all the times including timeHorizon
+    
+    User has to check the first variable collision to know about a collision'''
     t = 1
     p1 = predictedTrajectory1.predictPosition(t)
     p2 = predictedTrajectory2.predictPosition(t)
-    while t <= timeHorizon and (p1-p2).norm2() > collisionDistanceThreshold:
+    collision = (p1-p2).norm2() <= collisionDistanceThreshold
+    while t < timeHorizon and not collision:
+        t += 1
         p1 = predictedTrajectory1.predictPosition(t)
         p2 = predictedTrajectory2.predictPosition(t)
-        t += 1
-    return t, p1, p2
+        collision = (p1-p2).norm2() <= collisionDistanceThreshold
+    return collision, t, p1, p2
 
 def savePredictedTrajectoriesFigure(currentInstant, obj1, obj2, predictedTrajectories1, predictedTrajectories2, timeHorizon):
     from matplotlib.pyplot import figure, axis, title, close, savefig
@@ -248,8 +254,8 @@
 def computeCrossingsCollisionsAtInstant(predictionParams,currentInstant, obj1, obj2, collisionDistanceThreshold, timeHorizon, computeCZ = False, debug = False, usePrototypes = False,route1= (-1,-1),route2=(-1,-1),prototypes={},secondStepPrototypes={},nMatching={},objects=[],noiseEntryNums=[],noiseExitNums=[],minSimilarity=0.1,mostMatched=None,useDestination=True,useSpeedPrototype=True):  
     '''returns the lists of collision points and crossing zones'''
     if usePrototypes:
-        prototypeTrajectories1=getPrototypeTrajectory(obj1,route1,currentInstant,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype)
-        prototypeTrajectories2= getPrototypeTrajectory(obj2,route2,currentInstant,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype)
+        prototypeTrajectories1 = getPrototypeTrajectory(obj1,route1,currentInstant,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype)
+        prototypeTrajectories2 = getPrototypeTrajectory(obj2,route2,currentInstant,prototypes,secondStepPrototypes,nMatching,objects,noiseEntryNums,noiseExitNums,minSimilarity,mostMatched,useDestination,useSpeedPrototype)
         predictedTrajectories1 = predictionParams.generatePredictedTrajectories(obj1, currentInstant,prototypeTrajectories1)
         predictedTrajectories2 = predictionParams.generatePredictedTrajectories(obj2, currentInstant,prototypeTrajectories2)     
     else:
@@ -260,9 +266,9 @@
     crossingZones = []
     for et1 in predictedTrajectories1:
         for et2 in predictedTrajectories2:
-            t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
+            collision, t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
 
-            if t <= timeHorizon:
+            if collision:
                 collisionPoints.append(SafetyPoint((p1+p2).multiply(0.5), et1.probability*et2.probability, t))
             elif computeCZ: # check if there is a crossing zone
                 # TODO? zone should be around the points at which the traj are the closest
@@ -368,8 +374,8 @@
             predictedTrajectories2 = self.generatePredictedTrajectories(obj2, i)
             for et1 in predictedTrajectories1:
                 for et2 in predictedTrajectories2:
-                    t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
-                    if t <= timeHorizon:
+                    collision, t, p1, p2 = computeCollisionTime(et1, et2, collisionDistanceThreshold, timeHorizon)
+                    if collision:
                         nCollisions += 1
             # take into account probabilities ??
             nSamples = float(len(predictedTrajectories1)*len(predictedTrajectories2))