Analysis and Perception of Social Signals in Social Transportation
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摘要: 近年来, 智能便携设备和移动互联网的迅速发展促使网络空间中积累了海量的数据信息, 从而影响了众多领域的研究与发展. 本文针对在以社会信号为主的数据对交通领域的影响下产生的跨学科领域--社会交通, 从数据及相应技术方法和研究应用方面对物理和网络空间信息的感知、挖掘、分析与利用的研究成果进行综述, 并分析、总结与展望该领域的未来研究趋势.Abstract: In recent years, the rapid development of smart portable devices and mobile Internet has led to the accumulation of massive data information in cyberspace, and has affected research and development in many fields. This paper focuses on an emerging interdisciplinary research field named social transportation, which derived from transportation under the impact of data based mainly on social signals. The perception, mining, analysis and utilization upon information of physical and cyber space in related work are introduced according to data, corresponding technical methods, and research applications. The research trends of social transportation is also analyzed and summarized.
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图 1 常规数据研究流程及相应典型技术方法
Fig. 1 Routine data research process and corresponding typical technical methods
图 2 一种用于交通预测的GAN架构示例[111]
Fig. 2 An example framework of the conditional GAN for traffic prediction
图 5 社会交通研究与应用的发展趋势及分类
Fig. 5 The development trend and classification of social transportation research and application
图 6 基于社交媒体大数据的交通感知分析与可视化系统[75]
Fig. 6 A Traffic Sensing and Analyzing System Using Social Media Data
图 7 社会交通领域研究的基本要素
Fig. 7 Basic elements of research in the field of social transportation
表 1 影响城市交通状况变化的因素
Table 1 Factors affecting the change of urban traffic conditions
既定因素 非既定因素 天气 实时路况 节假日 交通舆情 体育赛事、文艺演出等大型集会活动 交通拥堵、事故等非既定交通事件 道路施工、管制等既定交通事件 其他突发特殊事件 交通方式及其运行安排 …… 环境、经济、土地、人口等相关信息 …… 
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表 2 可用真实数据的类别、来源、类型、信息及研究实例
Table 2 The categories, sources, data types, information and examples of available data
类别 来源 主要数据类型及信息 典型研究实例 物理空间 传感设备、浮动车和移动
通讯终端以及共享单车、
公交巴士和地铁等媒介(1)数值: 日期、时间、GPS定位、
速度、加速度等文献[8], [10-11], [13-14],
[17-19], [21], [23-35](2)文本: 方向、起点、终点、地址、
站点、车牌号码、基站编号等文献[17], [21-23], [25-27] (3)图像/视频/语音: 图像、视频等 文献[18] 网络空间 非社交类 在线地图服务提供商、
签到网站、政府部门和
公共场所或科研组织机构
等官方机构或组织的公开
信息发布网站(1)数值: 时间、气温、速度、
流量、GPS定位等文献[19], [21], [31], [33-43] (2)文本: 地址、站点、事件类型
及描述、天气情况等文献[19], [21-22], [28-30],
[32], [38-39], [41], [45-50](3)图像/视频/语音: 图像、视频等 文献[12], [27] 社交类 Twitter、微博、贴吧、
论坛和出行服务等媒介(1)数值: 时间、GPS定位、手机号码等 文献[12], [15], [18], [40], [51-61] (2)文本: 用户名称、出行方式、
地址、事件及描述、
评论、天气情况等文献[1], [4], [12], [24], [28], [31],
[36], [38-39], [41-43], [48-50],
[52-58], [60], [62-78](3)图像/视频/语音: 图像、视频等 文献[79]
下载: 导出CSV
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