STREETALK: A NAVIGATION SYSTEM FOR PEDESTRIANS AND CYCLISTS

Liu LIU; Fan ZHANG; Bolei ZHOU; Zhoutong WANG; Yingxin LI

doi:10.15302/J-LAF-20180210

PDF(11520 KB)

Landsc. Archit. Front. ›› 2018, Vol. 6 ›› Issue (2) : 94-101. DOI: 10.15302/J-LAF-20180210

THEMATIC PRACTICES

STREETALK: A NAVIGATION SYSTEM FOR PEDESTRIANS AND CYCLISTS

Author information +

History +

Abstract

Different from the conventional efficiency-driven navigation systems, StreeTalk navigation system is developed for pedestrians and cyclists to optimize their travelling safety and comfort. Through the application of technologies including object detection and scene parsing, the characteristics of urban streetscapes can be extracted. By combining deep learning models, machines can imitate human’s perception and evaluate streetscapes automatically, and intuitively show users the street safety and comfort level of different commuting options. Relevant technologies can not only be applied in offering panorama navigation services for pedestrians and cyclists, but also better support urban research, inform decision-making and urban landscape design, and explore more possibilities for future urban life.

Keywords

Urban Street / Safety and Comfort / Navigation System for Pedestrians and Cyclists / Deep Learning / Object Detection / Scene Parsing

Cite this article

EndNote

Ris (Procite)

Bibtex

Download citation ▾

Liu LIU, Fan ZHANG, Bolei ZHOU, Zhoutong WANG, Yingxin LI. STREETALK: A NAVIGATION SYSTEM FOR PEDESTRIANS AND CYCLISTS. Landsc. Archit. Front., 2018, 6(2): 94‒101 https://doi.org/10.15302/J-LAF-20180210