Vision based road trackers are about to be integrated in current vehicles mainly for security purposes in response to sleepiness problems for example. Nevertheless, such systems must be acceptable for drivers and must have a good reliability both in terms of roadsides recognition and of vehicle location estimation. Such a system must therefore be able to run in spite of difficult situations (due to occlusions, traffic, bad weather conditions, etc). Furthermore, the accuracy of the 3D vehicle estimation must be sufficient in order to feed subsequent warning systems. The system we have designed is able to recognize with reliability the lane sides in the current image and uses a 3D/4D modelling which provides both a good recognition as well as a very accurate 3D parameters estimation (vehicle location, steer angle, road curvatures, etc). The paper focuses mainly on this 3D original estimation stage and presents our recent developments (distance between vehicle and each road side for lane tracking application, analysis distances increasing, vertical road curvature estimation). The algorithm behaviour is then presented in simulated and real situations as well in order to prove the reliability of the approach.