Title: Interactive map matching and its visualisation: techniques and system

Authors: Li Cai; Bingyu Zhu; Yifeng Luo; Shuigeng Zhou

Addresses: School of Computer Science, University of Fudan, No. 220 Han Dan Road, 200433 Shanghai, China; School of Software, University of Yunnan, No. 2 North Cui Hu Road, 650091 Kunming, China ' School of Law, Southwestern University of Finance and Economics, No. 555, Liutai Avenue, Wenjiang District, 611130 Chengdu, China ' Shanghai Key Lab of Intelligent Information Processing, School of Computer Science, University of Fudan, No. 220 Han Dan Road, 200433 Shanghai, China ' Shanghai Key Lab of Intelligent Information Processing, School of Computer Science, University of Fudan, No. 220 Han Dan Road, 200433 Shanghai, China

Abstract: The trajectory data of taxies is an important kind of traffic data. Many traffic applications need to perform processing and analysis on trajectory data. Visualising trajectory data of vehicles on road maps is an important measure of reflecting and demonstrating the trend of traffic variation, where map matching from trajectory data to road network plays the most crucial role in such a visualisation process. We design and implement a novel interactive visualised map matching system in this paper, namely MMatchingVis, which provides multiple front-end functions including road selection, data extraction, map matching algorithm selection and result display, based on web techniques and Baidu Map. MMatchingVis employs the JStorm platform for trajectory data processing. We evaluate MMatchingVis' map matching results with the trajectory dataset collected from 6,599 taxies in Kunming, and evaluation results show that MMatchingVis could efficiently process and analyse trajectory data, support multiple user interaction models, and provide fine-grained visualisation presentation.

Keywords: visualisation; map matching; GPS trajectories data; user interaction; cloud computing.

DOI: 10.1504/IJES.2019.099402

International Journal of Embedded Systems, 2019 Vol.11 No.3, pp.340 - 351

Received: 01 Aug 2016
Accepted: 09 Apr 2017
Published online: 02 May 2019 *

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