Since the problem of trajectory privacy violation and homogeneous semantic location attack of moving objects in road network environment is very serious, a Privacy-aware Trajectory Data Collection (PTDC) algorithm was proposed. Firstly, through visits' entropy of Points Of Interests (POI), the sensitivity of each POI was computed; secondly, based on the mixture distance of sensitivity and Euclidean distance, θ-weight was defined and a weighted model of vertices and edges in the network environment was established to reach a k-θ-D anonymity, which can resist the semantic location homogeneity attack; finally, based on the bread-first traversal algorithm of undirected graph, an anonymous algorithm was proposed to satisfy the semantic difference of POIs, so that user's sensitive sampling location was replaced by an anonymous region. Data utility caused by PTDC algorithm was theoretically evaluated. A set of experiments were implemented to test PTDC algorithm, and compare it with the privacy-preserving algorithm named YCWA (You Can Walk Alone) in free space. In theory, the privacy level of YCWA algorithm was lower than PTDC algorithm. The experimental results show that the PTDC algorithm has an average information loss of about 15%, and average range count query error rate of about 12%, which performs slightly worse than YCWA algorithm, while the running time of PTDC algorithm is less than 5 seconds, which is much better than YCWA algorithm. PTDC algorithm meets the needs of real-time online data collection.