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/商业潜力是智能街道停车技术的发展。据估计，美国平均城市30%的交通是由寻找停车位的车辆组成的。在大城市寻找街道停车位可能是一项挑战；搜索花费的时间很长，指示牌可能令人困惑或误解，错误可能代价高昂(罚单或拖车)。可以通过：(I)街道停车规划，在出行前确定合适的停车区域，以及(Ii)路边冲浪检查停车规则来缓解这一问题。智能停车的市场规模估计为380亿美元。拟议的技术通过APP和API向司机、送货提供商和智能车辆/智能城市基础设施提供这两项基本的街道停车服务。这个i-Corps项目基于一系列机器学习算法和物联网技术的开发。具体地说，在以下步骤中开发和使用了新技术：(I)从智能手机/车辆上的摄像头拍摄的照片/视频检测街道停车标志；(Ii)从检测到的街道停车标志进行文本识别；(Iii)用于生成停车规则的自然语言处理(NLP)；(Iv)允许停车时间计算；以及(V)众包中的可信度评估。这项技术的重点是街道停车标志的识别和解释。尽管有许多基于人工智能的对象检测和文本识别技术，但通常它们在这些应用程序中不能很好地工作，因为街道停车标志上的文本不同，不同城市的标志也不同。此外，这项技术解决了将停车标志与其他共存标志区分开来的挑战。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。