Urban Trace Utilizing Mobile Sequence

• 作者: Bin Xu Qi Li Yukun Ma
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 社会科学
• 关键词: URBAN TRACE MOBILE SEQUENCE URBAN real ROADS MOBILE network LOGS
• 年，卷（期）: 2017,（2）
• 页码范围: 55-57
• 页数: 3页
• 分类号: C5

摘要

Urban trace mining and modeling of large scale active mobile phone holders is of great significance as it can effectively reduce traffic jam and hit-and-run incidents as well as other urban problems. Traditionally,people monitors traffic flows by GPS devices installed on buses or cars and traces hit-and-run incidents by road cameras, which turns out to be inefficient in that the data are sparse to represent a massive of people traces. In this paper, we propose a novel approach called mobile sequence to describe urban roads and moving object trajectories. Firstly,we use real urban roads information and base stations location information to generate urban roads mobile sequence. Then we extract people's mobile sequence from massive mobile network logs. Finally, we match roads' mobile sequence with people's mobile sequence to obtain human traces. As a validation, we use application installed on mobile phone to gather some real urban roads and base stations' information and then calculate their real mobile sequences to match the theoretical mobile sequences and gain 94.8% covering rate. Also, we use people's mobile sequences extracted from mobile network logs with theoretical mobile sequences and gain 90.6% matching accuracy