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

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.

On-line map-matching framework for floating car data with low sampling rate in urban road networks

2013 ◽  
Vol 7 (4) ◽  
pp. 404-414 ◽  
Author(s):  
Zhao-cheng He ◽  
She Xi-wei ◽  
Pei-lin Nie ◽  
Li-jian Zhuang
Keyword(s):  
Sampling Rate ◽  
Road Networks ◽  
Map Matching ◽  
Urban Road ◽  
Floating Car Data ◽  
On Line

Exploring the Structural Fractality of Urban Road Networks by Different Representations

2021 ◽  
pp. 1-15
Author(s):  
Hong Zhang ◽  
Peichao Gao ◽  
Tian Lan ◽  
Chengliang Liu
Keyword(s):  
Road Networks ◽  
Urban Road

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.

scholarly journals To re-route, or not to re-route: Impact of real-time re-routing in urban road networks

2021 ◽  
pp. 1-15
Author(s):  
Amine M. Falek ◽  
Antoine Gallais ◽  
Cristel Pelsser ◽  
Sebastien Julien ◽  
Fabrice Theoleyre
Keyword(s):  
Real Time ◽  
Road Networks ◽  
Urban Road
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