基于大数据的面向过程的交通管理决策支持系统
A Big-Data based and process-oriented decision support system for traffic management
摘要：
从可靠性和性能方面对公路网进行数据分析和监测是有价值的，但很难实现，特别是在必须及时向决策者提供分析信息的情况下。可观察事实的收集和分析可用于推断关于交通拥堵随时间推移的知识，并获得对道路安全的见解。然而，实时交通信息的持续监控会产生大量数据，这使得商业智能（BI）工具难以几乎实时地生成指标和关键绩效指标（KPI）。为了克服这些局限性，我们提出了一种基于大数据和以流程为中心的方法，该方法与运营交通信息系统集成，以深入了解道路网络的效率。本文演示了如何采用现有的面向过程的DSS解决方案与大数据的支持，可以利用可接受的响应时间的基础上监测和分析实时交通数据。
英文摘要：
Data analysis and monitoring of road networks in terms of reliability and performance are valuable but hard to achieve, especially when the analytical information has to be available to decision makers on time. The gathering and analysis of the observable facts can be used to infer knowledge about traffic congestion over time and gain insights into the roads safety. However, the continuous monitoring of live traffic information produces a vast amount of data that makes it difficult for business intelligence (BI) tools to generate metrics and key performance indicators (KPI) in nearly real-time. In order to overcome these limitations, we propose the application of a big-data based and process-centric approach that integrates with operational traffic information systems to give insights into the road network's efficiency. This paper demonstrates how the adoption of an existent process-oriented DSS solution with big-data support can be leveraged to monitor and analyse live traffic data on an acceptable response time basis.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
