Each year, millions of motor vehicle traffic accidents all over the world cause a large number of fatalities, injuries, and significant material loss. Automated Driving (AD) has potential to drastically reduce such accidents. In this work, researchers focus on the technical challenges that arise from AD in urban environments. Researchers present the overall architecture of an AD system and describe in detail the perception and planning modules. The AD system, built on a modified Acura RLX, was demonstrated in a course in GoMentum Station in California. Researchers demonstrated autonomous handling of 4 scenarios: traffic lights, cross-traffic at intersections, construction zones and pedestrians. The AD vehicle displayed safe behavior and performed consistently in repeated demonstrations with slight variations in conditions. Overall, researchers completed 44 runs, encompassing 110 km of automated driving with only 3 cases where the driver intervened the control of the vehicle, mostly due to error in GPS positioning. The demonstration showed that robust and consistent behavior in urban scenarios is possible, yet more investigation is necessary for full scale roll-out on public roads.