Journal of Geo-information Science >
An Extraction Algorithm of Track Features Based on Trend Set of Heading Angle Variable
Received date: 2015-03-16
Request revised date: 2015-04-30
Online published: 2015-10-10
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When the GPS or a network signal is disturbed or obscured, the precision and autonomy of navigation will be greatly reduced. The integrated navigation technology can compensate for this defect. In view of the application requirements of real-time, quickness and accuracy of trail data and road data during the integrated navigation process, this paper puts forward a real-time, high accuracy algorithm which is entitled as an extraction algorithm of track features based on trend set of heading angle variable. The algorithm picks up the calculation and analysis of heading angle in trail data points for navigation, assigns values to the confirmed trend set and the pending trend set innovatively, which effectively improve the real-time aspect and the accuracy of this algorithm in the navigation trajectory data extraction, ensuring the efficiency and precision of the integrated navigation. This algorithm also provides analysis and judgment on trend set status for the invalid features which is caused by external factors (e.g. the overtaking, the emergency avoidance and the drivers’ driving habits). The invalid features will be filtered and eliminated using the buffer of the pending trend set, ensuring the accuracy of the feature extraction. The vehicle trajectory data in Beijing is used for conducting experiments. The results show that the extraction algorithm of track features based on trend set of heading angle variable has obvious advantages in real-time application and extracting effect, and the buffer judging with the pending trend set is able to rule out some invalid features and interferences caused by external factors. The proposed algorithm is not only simple and feasible, but also has high efficiency and strong maneuverability.
Key words: integrated navigation; trend sets; set status; heading angle; extraction of features
LI Xiang , ZHANG Jiangshui , YANG Baixin , WANG Xi . An Extraction Algorithm of Track Features Based on Trend Set of Heading Angle Variable[J]. Journal of Geo-information Science, 2015 , 17(10) : 1172 -1178 . DOI: 10.3724/SP.J.1047.2015.01172
Tab. 1 An extraction algorithm of track features based on the trend set of heading angle variable表1 基于航向角变化的趋势集合轨迹特征划分算法 |
基于航向角变化的趋势集合轨迹特征划分算法 |
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输入: ←导航轨迹数据点 输出:轨迹特征点集合 BEGIN 1. while() 2. ; //初始化,将接收到导航轨迹数据的第一点存放入中 3. else 4. ,; //将接收到导航轨迹数据点存放入中 5. ,,; //计算该点的航向角变化,并给趋势状态赋值 6. while() 7. ,,,; //若趋势不明,则将和合并,用的趋势替换,并将清空 8. else 9. if() //若和趋势状态相同 10. ,,; //将和合并,并将清空 11. goto 14; //跳到步骤14,进行直线状态判断 12. else() //若和趋势状态不同 13. goto 14; 14. //计算航向角变化和,即该段时间内航向角的变化程度 15. if()//航向角变化大于给定直线状态阈值 16. goto 4; //返回步骤4,继续接收新的轨迹数据点进行判断 17. else 18. return ;//特征划分完毕,即为特征点集合 END |
Fig. 1 Overview of the proposed approach图1 技术路线框图 |
Fig. 2 The track feature图2 轨迹特征示意图 |
Fig. 3 Result of the extraction algorithm of track features based on trend set of heading angle variable图3 基于航向角变化的趋势集合轨迹特征划分算法示意图 |
Fig. 4 The invalid track feature图4 无效特征示意图 |
Fig. 5 The result of invalid track feature exaction图5 无效特征划分示意图 |
Fig. 6 The comparison of computation time between the proposed extraction algorithm and varisized curvature analysis in roads with different lengths图6 针对不同长度路线轨迹特征提取用时及与曲率分析算法的比较 |
Fig. 7 The comparison of the extraction point quantity for the same route图7 针对同一路线2种算法的特征提取点数量的比较 |
Fig. 8 The extraction algorithm of track features based on trend set of heading angle variable图8 基于航向角变化的趋势集合轨迹特征划分算法效果图 |
Tab. 2 Statistics of the test results for the extraction of track features based on the proposed algorithm表2 基于航向角变化的趋势集合轨迹特征划分实验统计表 |
路线 | 里程(km) | 总点数 | 特征总点数 | 有效特征点数 | 提取准确率(%) |
---|---|---|---|---|---|
1 | 3 | 812 | 137 | 125 | 91.0 |
2 | 4 | 1474 | 255 | 235 | 92.3 |
3 | 2 | 371 | 68 | 62 | 91.2 |
4 | 3 | 560 | 89 | 81 | 91.0 |
总计 | 12 | 3217 | 549 | 454 | 91.6 |
Fig. 9 Quality of the extraction of the interference features图9 无效特征划分效果图 |
Tab. 3 Statistics of the test results for the extraction of track features based on varisized curvature analysis表3 基于曲率分析特征划分实验统计表 |
路线 | 里程(km) | 总点数 | 特征总点数 | 有效特征点数 | 提取准确率(%) |
---|---|---|---|---|---|
1 | 3 | 812 | 137 | 112 | 81.8 |
2 | 4 | 1474 | 255 | 201 | 78.8 |
3 | 2 | 371 | 68 | 51 | 75.0 |
4 | 3 | 560 | 89 | 75 | 84.3 |
总计 | 12 | 3217 | 549 | 454 | 80.0 |
The authors have declared that no competing interests exist.
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