A system for use in a vehicle for determining an indication of the type of terrain ahead of the vehicle, the system comprising: means configured to receive sensor output data from at least one sensor on the vehicle, the sensor output data including a reflected radar signal from the terrain ahead of the vehicle; means configured to determine a plurality of parameters in dependence on the sensor output data; a neural network algorithm configured to receive the plurality of parameters, the neural network algorithm comprising a plurality of nodes; means for storing a plurality of weighting factors, each one of the weighting factors associated with a corresponding node of the plurality of nodes and each weighting factor being applied to said corresponding node when the neural network algorithm is executed; means configured to execute the neural network algorithm to provide a plurality of outputs corresponding to a plurality of different terrain types, the neural network algorithm being further configured to associate the plurality of parameters with one of the plurality of outputs, so as to determine an indication of the terrain type; means configured to compare the terrain type determined by the neural network algorithm to a current terrain type for which the vehicle is currently set up to travel over; means configured to send a control signal to one or more vehicle systems or subsystems to automatically adjust a setup of at least one vehicle system or subsystem in dependence on the terrain type determined by the neural network algorithm being different to the current terrain type; means configured to compare the terrain type determined by the neural network algorithm with a terrain type determined by a driver of the vehicle, as part of a self-learning process, and cause the automatic adjustment of the setup of the at least one vehicle system or subsystem to be overridden by the terrain type determined by the driver, if the terrain type determined by the driver is different to the terrain type determined by the neural network algorithm; and means configured to, as part of the self-learning process and if the terrain type determined by the driver is different to the terrain type determined by the neural network algorithm, adjust one or more of the weighting factors applied to the corresponding nodes of the neural network algorithm in dependence on the plurality of parameters, and/or one or both of the terrain type determined by the neural network algorithm and the terrain type determined by the driver. means configured to receive sensor output data from at least one sensor on the vehicle, the sensor output data including a reflected radar signal from the terrain ahead of the vehicle; means configured to determine a plurality of parameters in dependence on the sensor output data; a neural network algorithm configured to receive the plurality of parameters, the neural network algorithm comprising a plurality of nodes; means for storing a plurality of weighting factors, each one of the weighting factors associated with a corresponding node of the plurality of nodes and each weighting factor being applied to said corresponding node when the neural network algorithm is executed; means configured to execute the neural network algorithm to provide a plurality of outputs corresponding to a plurality of different terrain types, the neural network algorithm being further configured to associate the plurality of parameters with one of the plurality of outputs, so as to determine an indication of the terrain type; means configured to compare the terrain type determined by the neural network algorithm to a current terrain type for which the vehicle is currently set up to travel over; means configured to send a control signal to one or more vehicle systems or subsystems to automatically adjust a setup of at least one vehicle system or subsystem in dependence on the terrain type determined by the neural network algorithm being different to the current terrain type; means configured to compare the terrain type determined by the neural network algorithm with a terrain type determined by a driver of the vehicle, as part of a self-learning process, and cause the automatic adjustment of the setup of the at least one vehicle system or subsystem to be overridden by the terrain type determined by the driver, if the terrain type determined by the driver is different to the terrain type determined by the neural network algorithm; and means configured to, as part of the self-learning process and if the terrain type determined by the driver is different to the terrain type determined by the neural network algorithm, adjust one or more of the weighting factors applied to the corresponding nodes of the neural network algorithm in dependence on the plurality of parameters, and/or one or both of the terrain type determined by the neural network algorithm and the terrain type determined by the driver.