Multimodal and multiactivity travel planning is a practical but thorny problem in transportation research. This paper develops an improved supernetwork model to address this problem. The supernetwork is constructed mainly in three steps: a personalized network is first split into two types of networks with all links mode-specified; these are then assigned to all possible activity-vehicle states by means of state spreading from the beginning activity state. Finally, these discrete networks are connected into a supernetwork by state-labeled transition links. The proposed supernetwork is easier to construct than previous proposals and reduces the size needed to embody all combinations of choice facets explicitly. It can be proved for any activity program that any tour is a feasible solution in this representation. Consequently, every transport and transition link can be defined mode and activity-state dependent; thus standard shortest path algorithms can be used to find the most desirable tour. A case study is presented to show that the supernetwork model can be applied in a real-time manner for practical travel planning.