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This paper describes a robust stop-and-go control strategy for vehicles. Since sensors used in a real automotive context are generally low cost, measurements are quite noisy. Furthermore, many vehicle/road interaction factors (road slope, rolling resistance, aerodynamic forces) are very poorly known. Hence, a robust strategy to noise and parameters is proposed within the same theoretical framework: algebraic non-linear estimation and control techniques. On the one hand, noisy signals will be processed to obtain accurate derivatives, and thereafter, variable estimates. On the other hand, a grey-box closed-loop control will be implemented to reject all kinds of disturbances caused by exogenous parameter uncertainties.