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GPS轨迹中交通方式的模糊识别及算法实现
发表时间：2011-11-15 浏览量：2127 下载量：884
| 全部作者： | 徐超，季民河，陈雯 |
| 作者单位： | 华东师范大学地理信息科学教育部重点实验室 |
| 摘 要： | 基于模糊模式识别原理，探讨全球定位系统（global positioning system，GPS）技术跟踪数据中交通方式的软划分，提出一种基于模糊最大隶属度法则的算法。实证案例收集了上海地区32位居民142 d的日常出行GPS轨迹，建立起用以描述5种出行运动状态（即步行、自行车、公交、轨道交通、静止）的4个速度关联模糊变量及模糊隶属函数，通过数据清理、行程探测等步骤将整体轨迹划分成若干交通方式单一的行程段，并利用隶属函数计算行程段在各个模糊集中相对每种交通方式的隶属度，然后根据最大隶属度法则确定每段记录点的交通方式。实验得出的识别正确率为92�0%（Kappa=0�862），表明模糊识别算法有利于改善GPS数据中出行方式的提取精度。 |
| 关 键 词： | 地理学；模糊推理；全球定位系统轨迹；居民出行调查；交通方式 |
| Title： | Identifying travel mode from GPS trajectories through fuzzy pattern recognition |
| Author： | XU Chao, JI Minhe, CHEN Wen |
| Organization： | Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University |
| Abstract： | This paper proposed and tested a fuzzy approach to travel mode recognition from the global positioning system (GPS) travel data collected from 32 volunteers for 142 days in Shanghai. Four speed-related fuzzy variables were selected to characterize five movement patterns (walk, bike, bus, rail, and rest) in the urban daily traffic. Fuzzy sets and membership functions were constructed for the patterns using self-reported sample data. A procedure of data cleaning and trip segmentation was performed to divide GPS trajectories into mode stages. The final step involved determining the travel mode of each mode stage through a min-max fuzzy operation. Evaluation results indicated that the approach handled the data uncertainty and vagueness rather well. The got recognition accuracy is 92.0%（Kappa=0.862）. It properly incorporated partial information from the fuzzy variables into the mode recognition process for accuracy enhancement. |
| Key words： | geography; fuzzy reasoning; global positioning system trajectory; household travel survey; travel mode |
| 发表期数： | 2011年11月第21期 |
| 引用格式： | 徐超，季民河，陈雯. GPS轨迹中交通方式的模糊识别及算法实现[J]. 中国科技论文在线精品论文，2011，4（21）：1938-1945. |
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