A Green Self-Adaptive Approach for Online Map Matching

摘要: GPS trajectory data plays a critical role for the intelligent transportation. Due to many factors like measure error, sampling error and battery power-saving requirement, directly obtained trajectories will inaccurately align digital map. This requires an online map matching algorithm with high precision, low latency, energy consumption saving. However, existing approaches need make some trade off among these criterions. Hence, based on hidden Markov model, this paper proposes adaptive improve performances in perspectives at same time: 1) probabilistic method integrating geometric information topological is developed accuracy; 2) frequency proposed reduce consumption; 3) sliding window presented output delay. The experiments demonstrate that our can not only but also latency simultaneously.