Overtaking behavior on oncoming separated rural roads with intermittent overtaking sections, so called 2+1 roads, is unique as there are predefined sections where overtaking can take place. There is a growing interest in questions related to the design of such roads, including the length and placement of overtaking lanes to improve both safety and traffic efficiency. This study applies a computer vision-based vehicle re-identification methodology to gather evidence about vehicle speeds and overtaking and merging behavior along a 2-lane segment of a 2 + 1 road on the E18 route north of Stockholm. The results show that the vehicle re-identification method performs satisfactorily with only a few missed or false detections and more than 85% of all vehicles were successfully re-identified at all the cameras. The missed detections were commonly due to the vehicle not being detected at the first sensor because of occlusion from other vehicles. The method enables new possibilities to study number of overtakings for different sub-segments, how many vehicles that a single vehicle overtake, speeds or overtaking and overtaken vehicles, space mean speed, etc. For example, a comparison of the segment speed over the entire two-lane stretch with cross-section speed measurements from the different measurement locations shows the possibility to identify the location where cross-section measurements on two-lane stretches should be placed in order to best estimate the speed on the entire two-lane stretch. The current study also provides insights into how high the speed of overtaking vehicles is and how it varies between vehicles and segments as well as how many overtakes are conducted on the merging segment. One important observation is that between 5 – 8% of the overtaking vehicles tend to try to maximize the number of overtakes on the two-lane stretch by increasing the speed up to 120–130 km/h and a direct relationship can be observed between the number of overtakings performed by a vehicle with the speed of the overtaking vehicle.