导航中任意因子与距离的积分:安全快速行走

Yizhou Zhao, Yuetian Xie, S. Ahvar
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引用次数: 1

摘要

随着个人导航系统和移动设备的普及,各种基于位置的服务和数据集不断涌现。在本文中,我们提出了一种基于任何因素(如安全、享受、空气质量等)与距离相结合的新导航方法。介绍了一种基于因子强度的数据结构。这种数据结构可以很容易地扩展,以涵盖不同来源的数据(例如政府公开数据、用户反馈)。所提出的方法可以使用任何一种最短路径算法。我们将这种方法应用于旅行者寻求更安全路线的情况。利用2017年来自巴黎的每个站点的传入交通数据来建模基于位置的城市安全状态。然后将最短的路线调整为更安全的路线,以帮助行人绕过城市中的不安全区域,从而降低遇到事故的风险。作为概念验证,我们生成了一个基于谷歌Maps API的web应用程序,它说明了我们的方法和应用程序的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On Integration of Any Factor with Distance for Navigation : Walk Safely and Fast Enough
With the popularization of personal navigation systems and mobile devices, multifarious location-based services and datasets are being advanced. In this paper, we propose a new method for navigating based on combination of any factor (e.g. safety, enjoyment, air quality, etc.) with distance. A data structure based on intensity of the factor is introduced. This data structure can be extended easily to cover different sources of data (e.g. government open data, users' feedback). Any kind of shortest path algorithm can be used in proposed method. We apply this method to a situation where travelers are seeking safer routes. The incoming traffic data of each station from Paris in 2017 is utilized to model a location-based safety status of the city. The shortest route is then modulated to a safer route to help pedestrians bypass unsafe zones in the city, thereby reducing the risk of encountering incidents. As a proof-of-concept, we produce a web application based on Google Maps API, which illustrates the performance of our method and application.
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