I-Corps: Smart Street Parking Assistant

I-Corps：智能街道停车助理

• 批准号: 2024103
• 负责人: Wei Cheng
• 金额: $ 5万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2024103&HistoricalAwards=false
• 关键词: Corps; Smart; Street; Parking; Assistant

The broader impact/commercial potential of this I-Corps project is the development of technology for smart street parking. An estimated thirty percent of all traffic in the average U.S. city consists of vehicles searching for parking spots. Finding street parking in big cities can be challenging; the time spent searching is long, signage may be confusing or misinterpreted, and errors can be expensive (ticketed or towed). This could be mitigated with: (i) Street parking planning identifying suitable parking areas in advance of a trip, and (ii) curb-surfing verify the parking rules. The estimated market size for smart parking is $3.8 B. The proposed technology offers these two essential street parking services to drivers, delivery providers, and smart vehicle/smart city infrastructure through apps and APIs.This I-Corps project is based on the development of a series of machine learning algorithms and IoT technologies. Specifically, the novel techniques are developed and used in the following steps: (i) Street parking sign detection from pictures/videos taken by cameras on smartphones/vehicles; (ii) text recognition from the detected street parking signs; (iii) Natural language processing (NLP) used to generate parking rules; (iv) allowed parking time calculation; and (v) trust evaluation in crowdsourcing. This technology focuses on street parking sign recognition and interpretation. Although there are many AI-based object detection and text recognition techniques, typically they do not work well in these applications as the text on street parking signs is different and signs vary among cities. In addition, the technology addresses the challenge of distinguishing parking signs from other co-located signs.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/商业潜力是开发智能路边停车的技术。估计美国平均城市中所有交通的30％由寻找停车位的车辆组成。在大城市找到街道停车可能是具有挑战性的。搜索花费的时间很长，标牌可能会造成混淆或误解，并且错误可能很昂贵（票或拖曳）。可以通过以下方式进行缓解：（i）街道停车计划在旅行前确定合适的停车区，（ii）遏制冲浪验证停车规则。智能停车的估计市场规模为$ 3.8B。拟议的技术通过应用程序和APIS为驾驶员，送货提供商以及智能车辆/智能城市基础设施提供了这两种基本的街道停车服务。该I-Corps项目基于开发一系列机器学习算法和IoT技术。具体而言，新颖的技术是在以下步骤中开发和使用的：（i）摄像头在智能手机/车辆上拍摄的图片/视频中检测到路口停车标志； （ii）从检测到的路口识别的文本识别； （iii）用于制定停车规则的自然语言处理（NLP）； （iv）允许停车时间计算； （v）众包中的信任评估。这项技术着重于路边停车标志的识别和解释。尽管有许多基于AI的对象检测和文本识别技术，但通常它们在这些应用中效果不佳，因为路边停车标志上的文字不同，并且在城市之间的标志有所不同。此外，该技术解决了将停车标志与其他共同确定标志区分开的挑战。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。