Group Trip Planning (GTP) queries are targeting at finding some same activity sites for a group of users (usually expressed as Point of Interests (PoI)), in ordor to minimize the total travel cost. Existing researches on GTP queries are limited in Euclidean space, however, real travel is restricted by road network. Motivated by this observation, two algorithms (NE-GTP and ER-GTP) were designed to solve the GTP queries. NE-GTP expanded the network around every user's location to iteratively find the PoI, while ER-GTP used R-tree index and Euclidean distance to quickly get the results. The experimental results show that ER-GTP always performs on average an order of magnitude processing time faster than NE-GTP. In addition, when the dataset becomes large, ER-GTP also has good scalability.