To investigate the impact of Autonomous Vehicles (AVs) on urban congestion, this study looks at their performance at road intersections. Some suggest that because of increased environmental awareness, sensing and communication, AVs have the potential to outperform their human counterparts [11]. Others suggest that AVs might behave in simplistic ways and, sticking rigidly to the rules, make congestion worse [5]. Intersection performance will be a key determining factor: although human-drivers are typically very good at making decisions [9], over one third of road accidents happen at the intersections [3]. Intersection performance has been studied across a range of traffic densities using a simple MATLAB simulation of two intersecting 1-D flows of homogeneous automated vehicles. This lacks the detail of more advanced simulations, such as those using VISSIM (Verkehr In Städten SIMulationsmodell) [1, 6] or SUMO (Simulation of Urban MObility) [4, 7], but it enables fast identification of fundamental behaviours. The results show that there are distinct crossing regimes at low, medium and high densities. Furthermore, the transitions between regimes can be predicted analytically and their performance related to the fundamental model of 1-D traffic flow. These findings have the potential to focus efforts on the development of improved decision-making rules for emerging AVs.