### Table 2. The effect of a 300 msec delay at 35 mph and 55 mph for lead vehicle decelerations from 0.40 g to 0.85 g and for headways from 1.0 to 3.0 seconds. Initial Speed Percent increase in collisions Percent increase in collision velocity 35 mph 38.5% 80.7%

2001

"... In PAGE 8: ... For each of these reaction times, the model output was examined to determine whether the vehicles collided, and if they did, at what velocity. Table2 shows how a 300 msec delay increases the number of collisions and the collision velocity for the speeds of 35 and 55 mph. The 1.... ..."

Cited by 16

### Table 1: computation time of the local planners. Including collision checking to local planning increases similarly the time needed in both case: the computation time ratio is the same with or without collision checking (cf. Table 2). But, if the standard deviation is near 0.06 for both plan- ners without collision checking, it is increased with collision

1998

"... In PAGE 6: ...5 to 2 times longer than the computation of a Dubins apos; path (cf. Table1 , presenting the results of a... ..."

Cited by 5

### Table 3.4.1 Collision statistics with increasing number of neighboring piconets

### Table 1: Comparison with other methods. Times are expressed in milliseconds. Increasing the number of multiresolution levels speeds up the collision process.

"... In PAGE 19: ... OBB could not fit in the 512Mb of memory on the dragon-bunny example. Table1 demonstrates that the presented method, although more general, performs faster than the two other ones. This is probably due to the fact that it is collision dependent and not geometry dependent like classical hierarchical volumes structures.... ..."

### Table 2. Average Time to Detect a Collisions, in Seconds

2005

"... In PAGE 7: ... It is desirable to detect collisions as soon as possible to minimize the im- pact of collisions. Table2 shows that the average time to de- tect collisions increases as p increases. From the results, the ratio of the collision detection time to the stabilization in- terval (p) is more than ten times.... ..."

Cited by 1

### Table 2: Collision detection times (in Seconds)

"... In PAGE 10: ...14 Complexity of the Scene It can be noticed that the performance of optimized version increases relative to unoptimized version with increasing complexity of the scene. Table2 gives statistics for amounts of time spent in collision detection for both versions. For the unoptimized version, this includes bounding box tests, intersection handling and other memory overheads.... ..."

### Table 4. Collision numbers for excitation, Bird apos;s method

1991

"... In PAGE 9: ... This indicates a relaxation collision number of about 10. Bird argued that, because a successful eventwas assumed to yield a distribution of states instead of a single state, a reduction in the cross sections #28or an increase in the collision number#29 was necessary. Table4 shows the relaxation collision numbers whichwere used for electron and ion impact reactions. The values were increased by a factor of 10 for collisions with neutrals.... In PAGE 11: ... In this study the collision numbers for neutral particles have been determined from this relationship, although further investigation of the accuracy of this assumption is recommended. In order to compare with Table4 , sample collision numbers for the test case are given in Table 5. These collision numbers represent the values obtained when the average temperature and species densities from the signi#0Ccantly radiating portion of the #0Dow#0Celd were used to evaluate the rate coe#0Ecient and transition probabilities of equations 6 - 9.... ..."

Cited by 1

### Table III summarizes how many repetitions h of a bitstate search are minimally necessary to reduce the expected number of missed states due to hash collisions to less than 1 (that is to increase the expected coverage to 100%), for a given probability of collision for a single run of p1 ranging from 0.0 to 0.9, and assuming a state space size equal to 427,567 states, as in

1998

Cited by 63

### Table III summarizes how many repetitions h of a bitstate search are minimally necessary to reduce the expected number of missed states due to hash collisions to less than 1 (that is to increase the expected coverage to 100%), for a given probability of collision for a single run of p 1 ranging from 0.0 to 0.9, and assuming a state space size equal to 427,567 states, as in Table II. The requirement for h translates into:

### Table 2. The collision profile of hash functions. Packing

"... In PAGE 3: ... After training the network, NH25 has 460 hidden nodes and NH50 has 430 hidden nodes. Table2 shows the collision profile of each hash function: the figures under the hash function column correspond to the number of hash table slots to which a certain number of records, in the first column in the same row, are hashed. As can be seen in Table 2, the Mid-square performed the worst among the hash functions; NH25 has a similar result to that of the Division; and NH50 performed the best: it has the least number of unassigned slots and most slots with only one hash value assigned.... In PAGE 3: ... Table 2 shows the collision profile of each hash function: the figures under the hash function column correspond to the number of hash table slots to which a certain number of records, in the first column in the same row, are hashed. As can be seen in Table2 , the Mid-square performed the worst among the hash functions; NH25 has a similar result to that of the Division; and NH50 performed the best: it has the least number of unassigned slots and most slots with only one hash value assigned. Another criterion for judging the performance of a hash function is degradation of the collision rate as the packing density increases.... ..."