What this is asking for is a steady state matrix.
A steady state matrix eventually will always take the same values regardless of the initial conditions, so the initial conditions do not even matter.
Your first error was including the initial conditions.
We shall assign X=0 for car and X=1 for Train.
Pr(X
n+1=1|X
n=0) =
0.75 a [[(Probability he catches the train today given he took the car yesterday) a.k.a Pr(Train
n+1|Car
n) ]]
Pr(X
n+1=0|X
n=0) =
0.25 1-a [[(Probability he takes the car today given he took the car yesterday) a.k.a Pr(Car
n+1|Car
n) ]]
Pr(X
n+1=0|X
n=1) =
0.35 b [[(Probability he takes the car today given he took the train yesterday) a.k.a Pr(Car
n+1|Train
n) ]]
Pr(X
n+1=1|X
n=1) =
0.65 1-b [[(Probability he catches the train today given he took the train yesterday) a.k.a Pr(Train
n+1|Train
n) ]]

fill it in

Steady State Formula:
Recall taking the train X=1
Steady State formula:
Pr(X
n=1) =


= 0.681818
Maybe they are wrong..