NDLI: Deep learning enabled vehicle trajectory map-matching method with advanced spatial

Content Provider	IET Digital Library
Author	Liu, Zhijia Fang, Jie Tong, Yingfang Xu, Mengyun
Abstract	Global positioning system (GPS) trajectory map matching projects GPS coordinates to the road network. Most existing algorithms focus on the geometric and topological relationships of the road network, while did not make full use of the historical road network information and floating car data. In this study, the authors proposed a deep learning enabled vehicle trajectory map-matching method with advanced spatial–temporal analysis (DST-MM). The algorithm mainly focused on the following three aspects: (i) analyse the spatial relevancy from the prospective of geometric analysis, topology analysis and intersection analysis; (ii) to make full use of the historical and real-time data, a deep learning model was conducted to extract the road network and vehicle trajectory features and (iii) establish a speed prediction model and nest it in the temporal analysis structure. It narrows down the path search range through establishing the dynamic candidate graph. Experimental results show that the proposed DST-MM algorithm outperforms the existing algorithms in terms of matching accuracy for low-sampling frequencies GPS data, especially in the central urban area.
Starting Page	2052
Ending Page	2063
Page Count	12
ISSN	1751956X
Volume Number	14
e-ISSN	17519578
Issue Number	Issue 14, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/14/14
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2020.0486
Journal	IET Intelligent Transport Systems
Publisher Date	2021-01-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Advanced Spatial–temporal Analysis Combinatorial Mathematics Computer Vision And Image Processing Technique Deep Learning Model DST-MM Algorithm Floating Car Data Geometric Analysis Geometric Relationships Global Positioning System Global Positioning System Trajectory Map Matching Projects GPS Historical Road Network Information Historical Time Data Intersection Analysis Learning in AI Low-sampling Frequency GPS Data Matching Accuracy Optimisation Technique Real-time Data Road Traffic Spatial Relevancy Statistics Temporal Analysis Structure Topological Relationships Topology Analysis Traffic Engineering Computing Vehicle Trajectory Feature Vehicle Trajectory Map-matching Method
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

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