Special Topics in Intelligent Transportation
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 5
1338-1342

Massive GPS data real-time map matching algorithm based on Spark Streaming

Chen Yanyan
Li Siyang
Zhang Yunchao
Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
DOI: 10.19734/j.issn.1001-3695.2023.08.0424

Abstract

Floating car GPS data serves as the foundation for processing traffic information, with the rapid increase in the number of monitored vehicles, a massive amount of GPS data is generated, posing great challenges to map matching. To address the shortcomings of traditional matching methods in terms of matching efficiency and accuracy, this paper proposed a real time parallel map matching algorithm for massive GPS data that ensured both high matching accuracy and computational efficiency. This paper firstly reconstructed an efficient and accurate real-time map matching algorithm for streaming data by introducing a comprehensive weight factor that considered velocity and direction to enhance the offline map matching algorithm that relied on historical trajectories. Then, it introduced the Spark Streaming distributed computing framework to achieve real-time and parallel computation of the map matching algorithm, significantly improving the efficiency of real-time map matching. Experimental results demonstrate that the proposed algorithm achieves more than a 10% increase in matching accuracy compared to conventional topological matching algorithms on complex road sections, with an overall matching accuracy of over 95%. In terms of matching efficiency, it achieves approximately a fourfold improvement compared to an equivalent number of standalone servers. The experimental results show that the proposed algorithm achieves real-time map matching of 80 million GPS data points on a computing cluster composed of 11 machines, proving that the proposed algorithm can achieve real-time vehicle matching in urban areas.

Foundation Support

国家重点研发计划资助项目(2022YFB2602104)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.08.0424
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 5
Section: Special Topics in Intelligent Transportation
Pages: 1338-1342
Serial Number: 1001-3695(2024)05-008-1338-05

Publish History

[2023-12-05] Accepted Paper
[2024-05-05] Printed Article

Cite This Article

陈艳艳, 李四洋, 张云超. 基于Spark Streaming的海量GPS数据实时地图匹配算法 [J]. 计算机应用研究, 2024, 41 (5): 1338-1342. (Chen Yanyan, Li Siyang, Zhang Yunchao. Massive GPS data real-time map matching algorithm based on Spark Streaming [J]. Application Research of Computers, 2024, 41 (5): 1338-1342. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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