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通勤助推器:一款为视障人士提供第一/最后一英里和中途导航支持的移动应用程序。

Commute Booster: A Mobile Application for First/Last Mile and Middle Mile Navigation Support for People With Blindness and Low Vision.

机构信息

Department of Biomedical EngineeringTandon School of EngineeringNew York University Brooklyn NY 11201 USA.

Center for Urban Science and Progress, Tandon School of EngineeringNew York University Brooklyn NY 11201 USA.

出版信息

IEEE J Transl Eng Health Med. 2023 Jul 7;11:523-535. doi: 10.1109/JTEHM.2023.3293450. eCollection 2023.

Abstract

OBJECTIVE

People with blindness and low vision face substantial challenges when navigating both indoor and outdoor environments. While various solutions are available to facilitate travel to and from public transit hubs, there is a notable absence of solutions for navigating within transit hubs, often referred to as the "middle mile". Although research pilots have explored the middle mile journey, no solutions exist at scale, leaving a critical gap for commuters with disabilities. In this paper, we proposed a novel mobile application, Commute Booster, that offers full trip planning and real-time guidance inside the station.

METHODS AND PROCEDURES

Our system consists of two key components: the general transit feed specification (GTFS) and optical character recognition (OCR). The GTFS dataset generates a comprehensive list of wayfinding signage within subway stations that users will encounter during their intended journey. The OCR functionality enables users to identify relevant navigation signs in their immediate surroundings. By seamlessly integrating these two components, Commute Booster provides real-time feedback to users regarding the presence or absence of relevant navigation signs within the field of view of their phone camera during their journey.

RESULTS

As part of our technical validation process, we conducted tests at three subway stations in New York City. The sign detection achieved an impressive overall accuracy rate of 0.97. Additionally, the system exhibited a maximum detection range of 11 meters and supported an oblique angle of approximately 110 degrees for field of view detection.

CONCLUSION

The Commute Booster mobile application relies on computer vision technology and does not require additional sensors or infrastructure. It holds tremendous promise in assisting individuals with blindness and low vision during their daily commutes. Clinical and Translational Impact Statement: Commute Booster translates the combination of OCR and GTFS into an assistive tool, which holds great promise for assisting people with blindness and low vision in their daily commute.

摘要

目的

视障人士在室内和室外环境中导航时会面临巨大挑战。虽然有各种解决方案可以帮助他们前往和离开公共交通枢纽,但在交通枢纽内导航的解决方案却明显缺失,通常被称为“中间英里”。虽然研究试点已经探索了“中间英里”的旅程,但没有规模化的解决方案,这使得残疾通勤者留下了一个关键的空白。在本文中,我们提出了一个名为 Commute Booster 的新型移动应用程序,它提供了站内全程规划和实时引导。

方法和程序

我们的系统由两个关键组件组成:通用公共交通馈送规范 (GTFS) 和光学字符识别 (OCR)。GTFS 数据集生成了地铁站内用户在预期行程中会遇到的全面的寻路标志列表。OCR 功能使用户能够识别其手机摄像头视野内周围环境中的相关导航标志。通过无缝集成这两个组件,Commute Booster 可以在用户的行程中,实时向用户反馈其手机摄像头视野内是否存在相关导航标志。

结果

作为我们技术验证过程的一部分,我们在纽约市的三个地铁站进行了测试。标志检测的整体准确率达到了令人印象深刻的 0.97。此外,该系统的最大检测范围为 11 米,并支持大约 110 度的倾斜角度进行视野检测。

结论

Commute Booster 移动应用程序依赖于计算机视觉技术,不需要额外的传感器或基础设施。它在帮助视障人士日常通勤方面具有巨大的潜力。

临床和转化影响声明

Commute Booster 将 OCR 和 GTFS 的组合转化为辅助工具,对视障人士的日常通勤具有巨大的帮助。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2296/10697290/1e71cc973faf/rizzo1abc-3293450.jpg

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