Model of Intelligent Vehicle Cruise and Hardware-in-the-loop Test

Neuro-fuzzy model of intelligent vehicle cruise is built in the way of soft computing. The model included two inputs and one output The inputs are relative velocity and relative distance between the lead car and the following car, the output is the journey of gas pedal or brake pedal. To acquire data of training and simulation, test of inter-vehicle following is carried out. Inter-vehicle distance and relative velocity are obtained by GPS and wireless Bluetooth. The ANFIS (adaptive neuro-fuzzy inference system) model is trained by experiment data and the vehicle-to-vehicle distance controller is designed. Finally the hardware-in-the-loop test is made to validate the model. It makes it clear that the built model is rationality between the simulation and test and utilizes nonlinear feature of vehicle.