POMM: Precise Overpass Map-Matching Model and Algorithm

2012 ◽  
Vol 457-458 ◽  
pp. 1213-1218 ◽  
Author(s):  
Zhen Xing Zhu ◽  
Jian Ping Xing ◽  
De Qiang Wang
Keyword(s):  
Topological Structure ◽  
Road Networks ◽  
Gps Data ◽  
Map Matching ◽  
Matching Model ◽  
Matching Algorithm ◽  
Actual Position ◽  
The Common

Current map-matching algorithms consider more about the common plain road networks. The overpass always be ignored or treated as normal intersection without considering its complex topological structure. In order to fill this gap in map-matching area, the POMM (Precise Overpass Map-matching Model and Algorithm) is proposed in this paper. A novel overpass model is built for the overpasses map-matching algorithm. This model divided the overpass into straight roads and curve ones which consist of a set of directional points. According to the match degree for each straight road or directional point, the optimum road can be selectd from the candidate roads. Finally, the vehicle can be matched to the actual position on the optimum road. Experiment results of Jinan Bayi overpass using the actual GPS data shows that the algorithm has efficiency in accuracy (over 95%) and can precisely find the actual position of the vehicle in the overpass road, especially for the curve roads.

A turning point-based offline map matching algorithm for urban road networks

2021 ◽  
Vol 565 ◽  
pp. 32-45
Author(s):  
Dongqing Zhang ◽  
Yucheng Dong ◽  
Zhaoxia Guo
Keyword(s):  
Turning Point ◽  
Road Networks ◽  
Map Matching ◽  
Matching Algorithm ◽  
Urban Road

Research on parallelized real-time map matching algorithm for massive GPS data

2017 ◽  
Vol 20 (2) ◽  
pp. 1123-1134 ◽  
Author(s):  
Hongyu Wang ◽  
Jin Li ◽  
Zhenshan Hou ◽  
Ruochen Fang ◽  
Wenbo Mei ◽  
...  
Keyword(s):  
Real Time ◽  
Gps Data ◽  
Map Matching ◽  
Matching Algorithm ◽  
Time Map

Center in Navigation System Design and Implementation of the Map Matching Algorithm

2014 ◽  
Vol 556-562 ◽  
pp. 3227-3233
Author(s):  
Chao Zhang ◽  
Zhi Bin Ren ◽  
Hui Qi ◽  
Jun Hong Meng ◽  
Da Wei
Keyword(s):  
System Design ◽  
Navigation System ◽  
Network Data ◽  
Gps Data ◽  
Transport Protocol ◽  
Map Matching ◽  
Data Transport ◽  
Matching Algorithm ◽  
Design And Implementation ◽  
Grid Storage

With regard to the map matching algorithm based on central navigation, the network data are downloaded according to the GPS data in real time. For this reason a network data transport protocol based on grid storage is designed. The paper discusses map matching algorithm on two cases according to having matching point or not. At last, a running experiment for map matching algorithm is given.

scholarly journals Trajectory Segmentation Map-Matching Approach for Large-Scale, High-Resolution GPS Data

2017 ◽  
Vol 2645 (1) ◽  
pp. 67-75 ◽  
Author(s):  
Lei Zhu ◽  
Jacob R. Holden ◽  
Jeffrey D. Gonder
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Longest Common Subsequence ◽  
Gps Data ◽  
Map Matching ◽  
Trajectory Data ◽  
Data Set ◽  
Matching Algorithm ◽  
Gps Trajectory ◽  
Trajectory Segmentation

With the development of smartphones and portable GPS devices, large-scale, high-resolution GPS data can be collected. Map matching is a critical step in studying vehicle driving activity and recognizing network traffic conditions from the data. A new trajectory segmentation map-matching algorithm is proposed to deal accurately and efficiently with large-scale, high-resolution GPS trajectory data. The new algorithm separated the GPS trajectory into segments. It found the shortest path for each segment in a scientific manner and ultimately generated a best-matched path for the entire trajectory. The similarity of a trajectory segment and its matched path is described by a similarity score system based on the longest common subsequence. The numerical experiment indicated that the proposed map-matching algorithm was very promising in relation to accuracy and computational efficiency. Large-scale data set applications verified that the proposed method is robust and capable of dealing with real-world, large-scale GPS data in a computationally efficient and accurate manner.

scholarly journals An adaptive map-matching algorithm based on hierarchical fuzzy system from vehicular GPS data

PLoS ONE ◽  
2017 ◽  
Vol 12 (12) ◽  
pp. e0188796 ◽  
Author(s):  
Jinjun Tang ◽  
Shen Zhang ◽  
Yajie Zou ◽  
Fang Liu
Keyword(s):  
Fuzzy System ◽  
Gps Data ◽  
Map Matching ◽  
Matching Algorithm ◽  
Hierarchical Fuzzy System
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