The TME Motorway Dataset is composed of 28 clips for a total of approximately 27 minutes (30000+ frames) with vehicle annotation. Annotation was semi-automatically generated using laser-scanner data. Image sequences were selected from acquisition made in North Italian motorways in December 2011. This selection includes variable traffic situations, number of lanes, road curvature, and lighting, covering most of the conditions present in the complete acquisition.The dataset comprises:Image acquisition: stereo, 20 Hz frequency , 1024x768 grayscale losslessly compressed images, 32 horizontal field of view, bayer coded color information (in OpenCV use CV_BayerGB2GRAY and CV_BayerGB2BGR color conversion codes).Ego-motion estimate (confidential computing method).Laser-scanner generated vehicle annotation and classification (car/truck).A software evaluation toolkit (C++ source code).The data provided is timestamped and includes extrinsic calibration. The dataset has been divided into two sub-sets depending on lighting condition, named daylight (although with objects casting shadows on the road) and sunset (facing the sun or at dusk). For each clip, 5 seconds of preceding acquisition are provided, to allow the algorithm stabilizing before starting the actual performance measurement.