scholarly journals Effect Evaluation of Spatial Characteristics on Map Matching-Based Indoor Positioning

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6698
Author(s):  
Shuaiwei Luo ◽  
Fuqiang Gu ◽  
Fan Xu ◽  
Jianga Shang
Keyword(s):  
Particle Filtering ◽  
Spatial Information ◽  
Map Matching ◽  
Spatial Structures ◽  
Effect Evaluation ◽  
Matching Method ◽  
Open Spaces ◽  
Spatial Characteristics ◽  
Matching Methods ◽  
Proper Map

Map-matching is a popular method that uses spatial information to improve the accuracy of positioning methods. The performance of map matching methods is closely related to spatial characteristics. Although several studies have demonstrated that certain map matching algorithms are affected by some spatial structures (e.g., parallel paths), they focus on the analysis of single map matching method or few spatial structures. In this study, we explored how the most commonly-used four spatial characteristics (namely forks, open spaces, corners, and narrow corridors) affect three popular map matching methods, namely particle filtering (PF), hidden Markov model (HMM), and geometric methods. We first provide a theoretical analysis on how spatial characteristics affect the performance of map matching methods, and then evaluate these effects through experiments. We found that corners and narrow corridors are helpful in improving the positioning accuracy, while forks and open spaces often lead to a larger positioning error. We hope that our findings are helpful for future researchers in choosing proper map matching algorithms with considering the spatial characteristics.

scholarly journals Map Matching for Urban High-Sampling-Frequency GPS Trajectories

2020 ◽  
Vol 9 (1) ◽  
pp. 31
Author(s):  
Minshi Liu ◽  
Ling Zhang ◽  
Junlian Ge ◽  
Yi Long ◽  
Weitao Che
Keyword(s):  
Traffic Management ◽  
Route Planning ◽  
Sampling Frequency ◽  
Urban Traffic ◽  
Map Matching ◽  
Trajectory Data ◽  
Matching Method ◽  
Matching Methods ◽  
High Sampling ◽  
Matching Rules

As a fundamental component of trajectory processing and analysis, trajectory map-matching can be used for urban traffic management and tourism route planning, among other applications. While there are many trajectory map-matching methods, urban high-sampling-frequency GPS trajectory data still depend on simple geometric matching methods, which can lead to mismatches when there are multiple trajectory points near one intersection. Therefore, this study proposed a novel segmented trajectory matching method in which trajectory points were separated into intersection and non-intersection trajectory points. Matching rules and processing methods dedicated to intersection trajectory points were developed, while a classic “Look-Ahead” matching method was applied to non-intersection trajectory points, thereby implementing map matching of the whole trajectory. Then, a comparative analysis between the proposed method and two other new related methods was conducted on trajectories with multiple sampling frequencies. The results indicate that the proposed method is not only competent for intersection matching with high-frequency trajectory data but also superior to two other methods in both matching efficiency and accuracy.

scholarly journals Development of Multilayer-Based Map Matching to Enhance Performance in Large Truck Fleet Dispatching

2021 ◽  
Vol 10 (2) ◽  
pp. 79
Author(s):  
Ching-Yun Mu ◽  
Tien-Yin Chou ◽  
Thanh Van Hoang ◽  
Pin Kung ◽  
Yao-Min Fang ◽  
...  
Keyword(s):  
Data Structures ◽  
Spatial Data ◽  
Spatial Information ◽  
Data Retrieval ◽  
Spatial Data Mining ◽  
Map Matching ◽  
Matching Algorithm ◽  
Table Method ◽  
Look Up Table ◽  
The Look

Spatial information technology has been widely used for vehicles in general and for fleet management. Many studies have focused on improving vehicle positioning accuracy, although few studies have focused on efficiency improvements for managing large truck fleets in the context of the current complex network of roads. Therefore, this paper proposes a multilayer-based map matching algorithm with different spatial data structures to deal rapidly with large amounts of coordinate data. Using the dimension reduction technique, the geodesic coordinates can be transformed into plane coordinates. This study provides multiple layer grouping combinations to deal with complex road networks. We integrated these techniques and employed a puncture method to process the geometric computation with spatial data-mining approaches. We constructed a spatial division index and combined this with the puncture method, which improves the efficiency of the system and can enhance data retrieval efficiency for large truck fleet dispatching. This paper also used a multilayer-based map matching algorithm with raster data structures. Comparing the results revealed that the look-up table method offers the best outcome. The proposed multilayer-based map matching algorithm using the look-up table method is suited to obtaining competitive performance in identifying efficiency improvements for large truck fleet dispatching.

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