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Ph.D. - geht es zur Homepage der Informatik des Fachbereiches 3 ...

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Chapter 7. openETCS Meta Model<br />

This mathematical model is quite similar to a Moore machine [58]. According to the openETCS<br />

meta model, the inputs are defined by Boolean data flows to guard objects (oModeGuard,<br />

oStateGuard, oApplicationLevelType). Thus, this input can be defined as<br />

Σ ≡ {i j ; j = 1, 2, 3, . . . , n i } ; i j ∈ {0; 1} (7.33)<br />

The transition function δ us<strong>es</strong> the state transition vector v(s), which defin<strong>es</strong> for each certain /<br />

active state s the possible transitions to all others depending on the current inputs:<br />

s ′ = δ(s) = δ ( v(s) T s ) (7.34)<br />

s ′ is the new active state and s the state vector with all available stat<strong>es</strong>:<br />

⎡ ⎤<br />

s 1<br />

s 2<br />

s = ⎢ ⎥<br />

⎣ . ⎦ ; ∀o : s o ∈ S (7.35)<br />

s ns<br />

The Sum of all available inputs multiplied by their numerical priority, which is in the meta<br />

model a property of the related Transition relationship, are the elements of the state transition<br />

vector v(s):<br />

v(s) =<br />

⎡<br />

⎢<br />

⎣<br />

c 1 (s)<br />

c 2 (s)<br />

. . .<br />

c ns (s)<br />

⎤<br />

⎥<br />

⎦ (7.36)<br />

If several transition to the same new state s ′ exist but un<strong>der</strong> different input conditions, the<br />

corr<strong>es</strong>ponding element c i of the state transition vector is the sum of the products of inputs and<br />

their priority. In general, this means for each element<br />

∑n i<br />

∀l : c l = (i j (p j + 1)) ; p j ∈ N ∪ {0} (7.37)<br />

j=0<br />

p j is the priority of the input i j . i j = 1 means that the input i j is a condition for the<br />

corr<strong>es</strong>ponding new state. Otherwise, i j = 0 is set. In the openETCS model, p j is taken from<br />

the Transition relationship. The r<strong>es</strong>ult of the v(s) T s operation is a sum of possible different<br />

stat<strong>es</strong> s j , which have a numerical factor each. The δ function selects from this sum the state s j<br />

with the high<strong>es</strong>t factor and returns it. Therefore, it is important, that the priority is different<br />

for all possible transitions from a certain state. Otherwise, two stat<strong>es</strong> with the same factor<br />

may occur and the r<strong>es</strong>ult of the δ function is undefined. Since not at every execution point<br />

an input for a transition to a new state is set, the element in transition vector v(s) for a self<br />

transition has always the value 1.<br />

s ′ = s = s j ⇒ c j<br />

!<br />

= 1 (7.38)<br />

Therefore, 1 is added to the priority p j in (7.36) in or<strong>der</strong> that transitions that are not a<br />

self transition are always preferred by the δ function. Although the state machin<strong>es</strong> in the<br />

116

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