1. A computer-implemented method for a driver assistance system for estimating properties of objects in a vehicle's environment represented in digital images received from sensors, the properties including at least one of object identity, object position, and object distance, comprising the steps of: in a neural map comprising neurons having numerical activation values, extracting data on object identity and data on one of the other properties of the object from the input data from the sensors, and assigning the data on the object identity to a first neural map and assigning the data on said one of the other properties to a second neural map; the data on the object identity being encoded in accordance with common data encoding scheme (CDES) wherein two-dimensional arrays of numbers are encoded into a set of two-dimensional arrays of floating point numbers; between the first and the second neural maps, performing an unsupervised learning for adapting weights that implement a unique connection between a source neuron and a destination neuron, and incrementally increasing the complexity of a learning task; transmitting data between the first and the second neural maps, based on the values of the weights; detecting correlations between the first and the second neural maps, and estimating object identity from the second neural map based on the correlations; and determining the object identity based on the first neural map and said estimation of the object identity.