This paper is motivated by the autonomous shuttle service that operates in the geo-fenced Linden Residential Area of Columbus, Ohio that links residents to the two nearby locations of opportunity of a community center and a transit hub. This paper focuses on path planning and path tracking of an autonomous shuttle which are its most fundamental autonomous driving functions. Path planning is based on improving efficiency of computation and smoothness of path. Velocity planning is based on obeying speed limits, limiting longitudinal acceleration along straight segments and lateral acceleration during curved segments for improved ride comfort of the passengers. Path tracking control focuses on robust implementation that keeps accuracy of path following in the presence of uncertainties and variations in speed. A realistic, 3D virtual simulation environment of the actual geo-fenced urban area used here is built for evaluating and developing the path planning and path tracking functions of this paper. The same environment can also be used for developing and evaluating other autonomous driving functions with the capability of generating complicated traffic scenarios. The path tacking control results are compared with those of the pure pursuit path tracking algorithm of the open source and publicly available Autoware autonomous driving interface for the Robot Operating System.