Moment-based Plant and String Stability Analysis of Connected Cruise Control with Stochastic Delays

Abstract-In this paper we investigate the concept of connected cruise control (CCC) where vehicles rely on ad-hoc wireless vehicle-to-vehicle (V2V) communication to control their longitudinal motion. While V2V communication potentially allows vehicles to build detailed knowledge about the traffic environment, intermittencies and packet drops introduce stochastic delays into the communication channels that make control very challenging. We derive the mean and covariance dynamics for the corresponding stochastic system and analyze the effects of stochastic delays on vehicular strings. We also provide conditions for plant and string stability using the mean and the covariance. Moreover, we demonstrate that how the stable regimes shrink when the sampling time or the packet drop ratio increases. Our results have important implications regarding safety and efficiency of connected vehicle systems

Representing Lanes as Arc-length-based Parametric Curves to Facilitate Estimation in Vehicle Control

This paper revisits the fundamental mathematics of Taylor series to approximate curves with function representation and arc-length-based parametric representation. Parametric representation is shown to preserve its form in coordinate transformation and parameter shifting. These preservations can significantly facilitate lane estimation in vehicle control since lanes perceived by cameras are typically represented in vehicle body-fixed frames which are translating and rotating. Then we derived the transformation from function representation to arc-length-based parametric representation and its inverse. We applied the transformation to lane estimation in vehicle control problem, and derived the evolution of coefficients for parametric representation that can be used for prediction. We come up with a procedure to simulate the whole process with perception, lane estimation and control for the path-following problem. Simulations are performed to demonstrate the efficacy of the proposed lane estimation algorithm using parametric representation. The results indicate that the proposed technique ensures that vehicle control can achieve reasonably good performance at very low perception updating rate.Comment: 14 pages, 8 figures, currently submitted and under revie

Nonholonomic dynamics and control of road vehicles: moving toward automation

Nonholonomic models of automobiles are developed by utilizing tools of analytical mechanics, in particular the Appellian approach that allows one to describe the vehicle dynamics with minimum number of time-dependent state variables. The models are categorized based on how they represent the wheel-ground contact, whether they incorporate the longitudinal dynamics, and whether they consider the steering dynamics. It is demonstrated that the developed models can be used to design low-complexity controllers that enable automated vehicles to execute a large variety of maneuvers with high precision

Exact Stability Analysis of Discrete-Time Linear Systems with Stochastic Delays

This paper provides analytical results regarding the stability of linear discrete-time systems with stochastic delays. Necessary and sufficient stability conditions are derived by using the second moment dynamics which can be used to draw stability charts. The results are applied to a simple connected vehicle system where the stability regions are compared to those given by the mean dynamics. Our results reveal some fundamental limitations of connected cruise control which becomes more significant as the packet drop ratio increases

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