Intelligent vehicles require an efficient way to compute a feasible path that connects its current localization to a destination point. To achieve that, the knowledge about the road network, including its geometry, is important since connections between roads can be used in the path planning. This work consists on computing a feasible global path for autonomous vehicles with kinematic constraints. Piecewise linear continuous-curvature paths composed of clothoids, circular arcs, and straight lines are used for this purpose. Low curvature derivatives provide comfort to passengers. This approach provides a compact road network representation as only the parameters of the curves are stored. A real urban scenario with straight and curved roads, multiple lanes, intersections, and roundabouts is modeled and the proposed approach is validated. As a result of the proposed approaches, door-to-door global continuous-curvature paths are generated considering the shortest traveled distance.