To realize a new type of personal vehicle for elderly people while contributing to a low-carbon traffic society, we have been developing a robotic wheelchair with autonomous traveling and obstacle avoidance in an urban environment. In this paper, we primarily discuss two kinds of key technologies, long-distance autonomous travel in an outdoor environment and obstacle avoidance in a human-shared environment. For the localization and navigation methods, we propose sub-map dividing and realignment with FastSLAM, which enables generation of large-scale 3D voxel maps by the sampling based SLAM method. For the planning and obstacle avoidance methods, we propose motion control by a combination of the global/local A* algorithm and the dynamic window approach. To confirm the effectiveness of our proposed methods, the results of demonstration experiments using our robotic wheelchair 'Marcus' in the Tsukuba Robot Zone are also reported.