Extracting Traffic Events and Human Mobility Patterns in Geosocial Media Data for Assessing Real-time Road Traffic

在地理社交媒体数据中提取交通事件和人员流动模式以评估实时道路交通

• 批准号: RGPIN-2017-05950
• 负责人: Li, Songnian
• 金额: $ 2.99万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=749379
• 关键词: Extracting; Traffic; Events; Human; Mobility

Large urban centers and emerging city regions, as well as others in the world, face a series of complex challenges such as traffic congestion as they continue to grow at a rapid pace. Many largest cities around the world, including Canadian cities such as Vancouver and Toronto, are known among top worst for traffic congestion. With increasing traffic congestion causing delays and health problems for motorists and producing extra air pollution, reliable traffic information is key for travelers all over the world. This proposed research will develop new traffic event detection methods for providing such real-time information using massive social media data, and also will build extra tools for integrating human mobility patterns into short-term traffic congestion prediction that will help predict traveler's road traffic conditions in next 15-60 minutes ahead. The results (models, methods and tools) of this research can be of great use by a new generation of urban planners, city traffic managers and researchers. The short-term objectives of the proposed research will focus on three key research components that will: 1) model human activity patterns at various spatial and temporal scales to study their interactions with recurrent and non-recurrent traffic situations; 2) examine and evaluate different traffic and traffic-related event detection methods to develop a space-time-semantics based detection approach; and 3) assess and explore how social media data together with related models, tools and workflows can support the provision of real-time road traffic information by developing an collaborative service-oriented open platform. The platform will give researchers, traffic managers and decision makers direct and timely access to real-time traffic data, primarily extracted from various social networks, traffic information services, and suitable computational and analytical models and tools for traffic-related studies.The long-term goal of my Research Program is to develop a real-time road information infrastructure that visualize, publish and push near real time traffic information to target users and provide optimal routing services, but also capable of predicting real-time traffic congestion taking into non-recurrent traffic situations and long-term traffic considering recurrent patterns. Such an infrastructure can be implemented as a web-based system that integrates cloud computing, web services and GIS for traffic management decision making and transportation planning. The proposed experimental open platform, with implementation of the models, methods and tools as services, will build strong capacity for sharing road traffic information and services and will open up new opportunities for research sharing, HQP training and collaborations with Canadian government agencies and industry.

大型城市中心和新兴的城市地区以及世界其他地区都面临着一系列复杂的挑战，例如交通拥堵，因为它们继续迅速增长。全球许多最大的城市，包括加拿大城市，例如温哥华和多伦多，在交通拥堵中最糟糕。随着交通拥堵的增加导致驾驶者的延误和健康问题并产生额外的空气污染，可靠的交通信息对于世界各地的旅行者来说都是关键。这项拟议的研究将开发新的交通事件检测方法，以使用大量的社交媒体数据提供此类实时信息，并且还将建立额外的工具，以将人类流动性模式集成到短期交通拥堵预测中，以帮助预测旅行者的道路交通状况接下来的15-60分钟。这项研究的结果（模型，方法和工具）可以极大地利用新一代城市规划师，城市交通经理和研究人员。 拟议的研究的短期目标将重点放在三个关键的研究组成部分上：1）在各种空间和时间尺度上对人类活动模式进行建模，以研究其与经常性和非交通状况的相互作用； 2）检查和评估不同的流量和交通相关事件检测方法，以开发基于时空的检测方法； 3）评估和探讨如何通过开发面向协作服务的开放平台来支持提供实时道路交通信息的相关模型，工具和工作流程。该平台将为研究人员，交通经理和决策者直接及时访问实时交通数据，主要从各种社交网络，交通信息服务以及适当的计算和分析模型以及与交通相关研究的工具中提取。我的研究计划的任期目标是开发一个实时道路信息基础架构，该基础架构可视化，发布和推动接近实时流量信息到目标用户并提供最佳路由服务，但也能够预测实时的交通拥堵考虑复发模式的经常流量情况和长期流量。这样的基础架构可以作为基于Web的系统实现，该系统集成了云计算，Web服务和GIS，以进行交通管理决策和运输计划。拟议的实验开放平台通过实施模型，方法和工具作为服务，将建立强大的共享道路交通信息和服务的能力，并将为研究共享，HQP培训以及与加拿大政府机构和行业的合作提供新的机会。