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研究生:蔡博汶
研究生(外文):Po-Wen Tsai
論文名稱(外文):Quantitative Performance Evaluation of Trajectory Data Cleansing
指導教授:孫敏德
學位類別:碩士
校院名稱:國立中央大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:英文
論文頁數:53
中文關鍵詞:HMMtrajectory data cleansingHausdorff distanceFréchet distance
外文關鍵詞:HMMtrajectory data cleansingHausdorff distanceFréchet distance
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在許多關於車輛安全的應用中,都需要車輛的軌跡資料,例如左轉輔助及前方碰撞警告。可惜的是,透過全球定位系統 (GPS) 收集到的車輛軌跡資料,受到 GPS 的限制或較低的取樣率影響,常常不夠準確。因此,如何清理並校正收集到的軌跡資料是一個重要的問題。而相較於其他的軌跡清理的研究,基於 HMM 的軌跡清理方式似乎較有希望達到效果。在此研究中,我們提出了使用三種不同的量測值來評估基於 HMM 的軌跡清理效能,分別是:Hausdorff 距離,Fréchet 距離以及 Average Fréchet 距離。在我們的實驗中,使用基於 HMM 的軌跡清理,並利用前面提出的三個量測值來找出對於這個基於 HMM 的軌跡清理最好的參數設定。
The vehicle trajectories are required in many vehicle safety applications, such as Left Turn Assist (LTA) and Front Collision Warning (FCW). Unfortunately, the vehicle trajectories collected by Global Positioning System are often inaccurate due to the limitation of GPS or low sampling rate. How to cleanse and calibrate the collected trajectory is therefore an important issue. The HMM based trajectory data cleansing seems to be promising among different research works of trajectory cleansing, but it does not provide adquate quantitative analysis to evaluate its performance. In this research, we propose to use three different distance measurements: Hausdorff distance, Fréchet distance, and Average Fréchet distance, to evaluate the performance of HMM based trajectory cleansing. In our HMM-based trajectory cleansing experiments, the three propose measurements are used to identify the best parameter settings for the HMM-based trajectory cleansing.
1 Introduction 1
2 Related Work 4
2.1 The Ratio of Exactly Match . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 Similarities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
3 Preliminary 7
3.1 OpenStreetMap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
3.2 HMM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .7
3.3 HMM on Trajectory Data Cleansing . . . . . . . . . . . . . . . . . . . . . 9
3.4 Hausdorff Distance . . . . . . . . . . . . . . . . . . . . . . . . . . . . .10
3.5 Fréchet Distance . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12
3.6 Average Fréchet Distance . . . . . . . . . . . . . . . . . . . . . . . . .13
4 Design 14
4.1 Trajectory Data Cleansing . . . . . . . . . . . . . . . . . . . . . . . . 14
4.1.1 Noise Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15
4.1.2 HMM Map Matching . . . . . . . . . . . . . . . . . . . . . . . . . . . .17
4.1.3 A* Route Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
4.2 Measurement Implementation . . . . . . . . . . . . . . . . . . . . . . . .23
4.2.1 Hausdorff Distance Measuring . . . . . . . . . . . . . . . . . . . . . .25
4.2.2 Fréchet Distance Measuring . . . . . . . . . . . . . . . . . . . . . . .27
4.2.3 Average Fréchet Distance Measuring . . . . . . . . . . . . . . . . . . .29
5 Performance 30
5.1 Data Source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
5.2 Studied Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . .30
5.3 Cleansing Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
6 Conclusion 38
Reference 39
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