Nowadays, with the increasing popularity of mobile Web (e.g., mobile social network), geo-positioning technologies and smart devices, it enables users to generate large amounts of location information and corresponding descriptive activities. Location-based services (LBSs) have been widely studied and applied into many real applications. During LBSs selection, the users want to do multiple activities on the route, which has many demands (e.g., time, site, service, etc.). However, the existing approaches do not consider the ratings of activities in route planning. In this paper, we propose a novel route planning method, called Rating Aware Route Planning (RARP). Given a set points of interest (POIs) in road network, where each point belongs to a specific category (e.g., resturant, gas station, bank, etc.) with several properties (rating, geo-position, etc.), a starting point S and an ending point T, our route planning method retrieves the best route with the constraint of rating specified by users that starts at S, passes through at least one point from each of the category in order, and ends at T. In addition, we propose two algorithms for the problem and conduct the experiments on a synthetic dataset in a real road network. The experimental results demonstrate that our propose method can plan a route having the shortest distance and high ratings with good efficiency.