基于社会媒体数据增强的交通态势感知研究及进展

doi:10.11959/j.issn.2096-6652.202220

智能科学与技术学报 ›› 2022, Vol. 4 ›› Issue (1): 1-13.doi: 10.11959/j.issn.2096-6652.202220

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基于社会媒体数据增强的交通态势感知研究及进展

陈苑文¹^,², 王晓²^,³, 李灵犀³^,⁴, 王飞跃²^,³

¹ 厦门大学航空航天学院自动化系，福建厦门 361100
² 中国科学院自动化研究所复杂系统管理与控制国家重点实验室，北京 100190
³ 青岛智能产业技术研究院平行智能创新中心，山东青岛 266114
⁴ 美国印第安纳大学-普渡大学印第安纳波利斯分校电子与计算机工程系，美国印第安纳州 IN 46204

修回日期:2022-03-01 出版日期:2022-03-15 发布日期:2022-03-01
作者简介:陈苑文（2000− ），女，厦门大学航空航天学院自动化系在读，主要研究方向为基于社会媒体数据增强的交通态势感知及状态推理
王晓（1988− ），女，博士，中国科学院自动化研究所复杂系统管理与控制国家重点实验室副研究员，青岛智能产业技术研究院院长。主要研究方向为平行智能、社会交通、动态网群组织行为和社交网络分析
李灵犀（1977− ），男，博士，美国印第安纳大学−普渡大学印第安纳波利斯分校电子与计算机工程系教授，主要研究方向为复杂系统的建模、分析、控制与优化，智能交通系统，智能网联汽车，驾驶辅助系统与人因学
王飞跃（1961− ），中国科学院自动化研究所研究员，复杂系统管理与控制国家重点实验室主任，中国科学院大学中国经济与社会安全研究中心主任。主要研究方向为平行系统的方法与应用、社会计算、平行智能以及知识自动化
基金资助:
国家自然科学基金资助项目(62173329)

Traffic situational awareness research and development enhanced by social media data: the state of the art and prospects

Yuanwen CHEN¹^,², Xiao WANG²^,³, Lingxi LI³^,⁴, Fei-Yue WANG²^,³

¹ Department of Automation, School of Aerospace Engineering, Xiamen University, Xiamen 361100, China
² The State Key Laboratory for Management and Control of Complex Systems, Chinese Academy of Sciences, Beijing 100190, China
³ Parallel Intelligence Innovation Center, Qingdao Academy of Intelligent Industries, Qingdao 266114, China
⁴ Department of Electrical and Computer Engineering, Indiana University-Purdue University, Indianapolis IN 46204, USA

Revised:2022-03-01 Online:2022-03-15 Published:2022-03-01
Supported by:
The National Natural Science Foundation of China(62173329)

摘要/Abstract

摘要：

交通态势感知是智能交通系统的重要研究方向。已有研究大多关注如何使用物理传感器感知当下交通态势并预测未来交通状况。然而，物理传感器性能易因天气影响、电磁干扰、能源限制等问题出现不稳定或失效情况，导致其采集的数据稀疏或缺失，使其对交通态势感知滞后且不准确。社会媒体数据为及时感知完善的交通态势信息提供了新的增强方式。面向当下异常交通情况频发的城市交通管控现状，社会传感与物理传感数据互为补充，可进一步满足城市交通高效管理需求。基于此，对基于社会媒体数据的交通事件检测和交通状况预测工作展开分析研究，探讨社会媒体数据增强的交通态势感知研究工作如何为交通管理部门提供决策支持，以合理规划、引导交通，缓解交通拥堵，最后提出社会媒体数据增强的交通态势感知还需进一步探索的方向。

关键词: 交通态势感知, 智能交通系统, 社会感知, 交通事件检测, 交通状况预测

Abstract:

Traffic situational awareness is an important research direction of intelligent transportation systems.Most of the existing research focused on how to use physical sensors to perceive the current traffic situation and predict the future traffic state.However, the performance of physical sensors is prone to instability or failure due to adverse weather, electromagnetic interference, energy limitation and other problems, resulting in sparse or missing collected data, which makes the perception of traffic situation lagging and inaccurate.Social media data provides a new and enhanced way of perceiving comprehensive traffic situation information in a timely manner.Facing with the current traffic situation where sudden abnormal traffic events occur frequently, social sensing and physical sensing data can complement with each other to further improve the efficiency of urban traffic management.The related work of traffic event detection and traffic state prediction enhancing based on social media data were analyzed, and how those research works provide decision support for the traffic management departments to plan and guide traffic reasonably and alleviate traffic congestion were explored.Finally, some future research directions of traffic situational awareness enhanced by social media data were proposed.

Key words: traffic situational awareness, intelligent transportation system, social perception, traffic event detection, traffic state prediction

中图分类号:

TP399

陈苑文, 王晓, 李灵犀, 等. 基于社会媒体数据增强的交通态势感知研究及进展[J]. 智能科学与技术学报, 2022, 4(1): 1-13.

Yuanwen CHEN, Xiao WANG, Lingxi LI, et al. Traffic situational awareness research and development enhanced by social media data: the state of the art and prospects[J]. Chinese Journal of Intelligent Science and Technology, 2022, 4(1): 1-13.

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基于社会媒体数据增强的交通态势感知研究及进展

Traffic situational awareness research and development enhanced by social media data: the state of the art and prospects

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