  In recent works, we have proposed a stochastic cellular automaton model of
traffic flow connecting two exactly solvable stochastic processes, i.e., the
Asymmetric Simple Exclusion Process and the Zero Range Process, with an
additional parameter. It is also regarded as an extended version of the Optimal
Velocity model, and moreover it shows particularly notable properties. In this
paper, we report that when taking Optimal Velocity function to be a step
function, all of the flux-density graph (i.e. the fundamental diagram) can be
estimated. We first find that the fundamental diagram consists of two line
segments resembling an {\it inversed-$\lambda$} form, and next identify their
end-points from a microscopic behaviour of vehicles. It is otable that by using
a microscopic parameter which indicates a driver's sensitivity to the traffic
situation, we give an explicit formula for the critical point at which a
traffic jam phase arises. We also compare these analytical results with those
of the Optimal Velocity model, and point out the crucial differences between
them.
