  We consider a problem of cooperative evasion between a single pursuer and
multiple evaders in which the evaders are constrained to move in the positive Y
direction. The evaders are slower than the vehicle and can choose their speeds
from a bounded interval. The pursuer aims to intercept all evaders in a given
sequence by executing a Manhattan pursuit strategy of moving parallel to the X
axis, followed by moving parallel to the Y axis. The aim of the evaders is to
cooperatively pick their individual speeds so that the total time to intercept
all evaders is maximized. We first obtain conditions under which evaders should
cooperate in order to maximize the total time to intercept as opposed to each
moving greedily to optimize its own intercept time. Then, we propose and
analyze an algorithm that assigns evasive strategies to the evaders in two
iterations as opposed to performing an exponential search over the choice of
evader speeds. We also characterize a fundamental limit on the total time taken
by the pursuer to capture all evaders when the number of evaders is large.
Finally, we provide numerical comparisons against random sampling heuristics.
