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In this paper the Stochastic Inclusion Principle is applied to decentralized LQG suboptimal longitudinal control design of a platoon of automotive vehicles. Starting from a stochastic linearized platoon state model, input/state overlapping subsystems are defined and extracted after an adequate expansion. An algorithm for approximate LQG optimization of these subsystems is developed. Vehicle controllers obtained after contraction, provide high performance tracking and noise immunity.

In GPS, correlation function distortion of the received signal due to multipath propagation can gravely degrade the position estimation. The positioning accuracy is strongly affected by the quality of the signal propagation time estimations. This paper presents an approach to the Sequential Monte Carlo filtering for the time delay estimation of direct and multipath signals. Filtering is done approximating posterior density function for time delays. Through comparative analysis, using simulated GPS signal, advantages of this method are presented.