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Locating the surrounding vehicles is an important environment perception task for autonomous vehicles and advanced driver assistance systems. This task is usually explored based on the sensors’ pre-calibration (e.g. height or pitch angle), but can be challenging when the calibration fails (e.g. on the sloping and uneven roads). In this work, we propose a calibrated feature-point based (CFPB) method to estimate the car-following distance adaptive to rough roads, using a single camera. Instead of using the pre-calibrated parameters, CFPB method is based on the surrounding vehicles’ feature points. It benefits from the fixed coordinate relations among these points, which enables the algorithm to be adaptive to rough roads. These fixed coordinate relations can be calibrated during driving. Namely, after a few seconds of observation to a surrounding vehicle, the CFPB method can start working for more accurate …