  This paper is concerned with the network-theoretic properties of so-called
$k$-nearest neighbor intelligent vehicular platoons, where each vehicle
communicates with $k$ vehicles, both in front and behind. The network-theoretic
properties analyzed in this paper play major roles in quantifying the
resilience and robustness of three generic distributed estimation and control
algorithms against communication failures and disturbances, namely resilient
distributed estimation, resilient distributed consensus, and robust network
formation. Based on the results for the connectivity measures of the
$k$-nearest neighbor platoon, we show that extending the traditional platooning
topologies (which were based on interacting with nearest neighbors) to
$k$-nearest neighbor platoons increases the resilience of distributed
estimation and control algorithms to both communication failures and
disturbances. Finally, we discuss how the performance of each algorithm scales
with the size of the vehicle platoon.
