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Accurate Self-Localization in Transit Stations: A Case Study

  • Author(s): Mirzaei, Fatemeh
  • Lam, Jonathan
  • Manduchi, Roberto
  • et al.
Abstract

Public transit stations and hubs can be diffi- cult to navigate by people who are blind or have low vision, and by people with cognitive impairment. We are building a system, named RouteMe2, that provides microrouting and guidance in these environments. A critical component of this system is self-localization. In this paper, we present a system for self-localization in outdoor places (such as a train station), in which GPS signal is available but, due to shading from nearby buildings, often unreliable. We propose a new approach that uses a small number of Blue- tooth low energy (BLE) beacons to increase self-localization accuracy by means of statistical fusion with data from GPS, paired with a Bayes discrete filter tracker. A number of experiments were conducted at San Jose Diridon light rail station to quantitatively assess the performance of the proposed system.

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