On Integration of Any Factor with Distance for Navigation : Walk Safely and Fast Enough

Yizhou Zhao, Yuetian Xie, Shohreh Ahvar

Abstract: 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.