I-Corps: Traffic Analyzer for Visualization and Simulation

I-Corps：用于可视化和模拟的流量分析器

• 批准号: 2324972
• 负责人: Tam Nguyen
• 金额: $ 5万
• 依托单位: University of Dayton
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2324972&HistoricalAwards=false
• 关键词: Corps; Traffic; Analyzer; Visualization; Simulation

The broader impact/commercial potential of this I-Corps project focuses on assessing state-of-the-art technologies in artificial intelligence and computer vision for traffic visualization and simulation. This is important since the construction demands keep increasing in the post-pandemic era. At the moment, many simulators used the mock-up data or random data. Meanwhile, consulting firms still deploy humans using manual clickers to count vehicles in a period of several days or weeks. This process is time and labor consuming. This project will explore implementation and commercialization opportunities with a traffic analysis tool to visualize and simulate the traffic from the analyzed data. This I-Corps project develops a system to analyze the traffic cameras. It applies state-of-the-art computer vision algorithms from object detection to trajectory-based tracking in order to improve the performance of traffic flow estimation. The technology analyzes the camera data in the context of a graph; the traffic of one node can affect another node in the traffic graph. Significantly, the visual data taken from one city camera grid can be used for other cities where the traffic situation remains the same. The technology also includes a city traffic planning simulator using the analyzed traffic data. The simulator is used to support metropolitan transportation planning. The addition or removal of any traffic infrastructure can be observed from the simulator. Therefore, the simulator results can guide engineers and city authorities in urban development planning.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个I-Corps项目的更广泛的影响/商业潜力侧重于评估用于交通可视化和模拟的人工智能和计算机视觉方面的最先进技术。这一点非常重要，因为在后疫情时代，建筑需求不断增加。目前，许多模拟器使用模拟数据或随机数据。与此同时，咨询公司仍然部署人工使用手动点击器在几天或几周内清点车辆。这个过程是耗时耗力的。该项目将利用流量分析工具探索实施和商业化机会，以可视化和模拟分析数据的流量。这个I-Corps项目开发了一个分析交通摄像头的系统。它应用了最先进的计算机视觉算法，从目标检测到基于概率的跟踪，以提高交通流量估计的性能。该技术在图的上下文中分析摄像机数据;一个节点的流量可以影响流量图中的另一个节点。值得注意的是，从一个城市摄像机网格获取的视觉数据可以用于交通状况保持不变的其他城市。该技术还包括使用分析的交通数据的城市交通规划模拟器。该模拟器用于支持大都市交通规划。任何交通基础设施的添加或删除都可以从模拟器中观察到。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。