A real‐time traffic index model for expressways. (3rd February 2019)

• Record Type: Journal Article
• Authors: Xu, Fusheng; Huang, Zhongxiang; Dai, Hao; Zhu, Xueying; Wu, Hongwei; Zhang, Jun
• Other Names: Li Gang guestEditor.; Batten Lynn guestEditor.; Foschini Luca guestEditor.; Kim Hyunbum guestEditor.; Dong Fang guestEditor.; Wu Chenshu guestEditor.; Gao Shangce guestEditor.
• Is Part Of: Concurrency and computation. Volume 31:Number 24(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-02-03
• Subjects: ARIMA model -- floating cars data -- time‐series forecasting -- traffic performance index of expressways; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.5155
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: In this paper, a real‐time traffic index model of expressways is proposed by using a traffic index to evaluate the actual conditions of expressways. The model considers the actual situation of floating and nonfloating vehicles on expressways, in the context of massive floating car data. Included is the realization of the complete calculation model of real‐time traffic index estimation, including highway section division, spatial topology map matching, driving route calculation, and road congestion status judgment. For roads without floating car coverage, the weighted‐moving‐average time‐series prediction method is used to predict the traffic index, so that the running condition of all roads in the network can be analyzed completely. The simulation results show that the proposed highway traffic index can reflect not only the overall high‐speed operation but also real‐time congestion at specific high‐speed or specific highway intervals, providing an effective reference for travel.