MyWay: A contextual way-finding

Walking is perhaps the best way to experience a city. Walking along the streetlight at night, walking underneath the arcade in the rain, or jogging along the shading of sidewalk trees. As usual as they may seem, at the time where we are given so many fancy maps and navigation tools, we paid too little attention to, or imagined too little about walking.

Almost all of our navigation apps were designed for better efficiency, rather than better experience.

However, thanks to the growing urban data we have today, we could now have more thorough information of our walkable environment and propose new way-finding/ suggesting application that celebrates street lifestyle based on individual preference and realtime urban context.

Rainy Day Map

You must have experienced running in the rain and seeking desperately for a shelter. Imagine yourself walking on the street, suddenly a pouring rain occurred and you are stuck at some street corner, the arcade space, a common cityscape in Taiwan, would suddenly become your best choice to walk under. So, where are those rain-free public corridors in downtown Taipei?

Since there is no direct geolocation data for arcade space, we estimated them based on its typical condition: consistent setback from main streets, concept shown as below.

Besides the arcade, one could also avoid getting wet by walking through some public passage in the malls, or hiding in some underpass or subway streets. Together with arcade space, the below is the map that tells you where you could walk in rainy days, without carrying an umbrella.

Sunny Day Greeenscape Map

In sunny days, you might want to jog along the trees and stay closer to the greenery. Based on street tree location data, we could easily identify the green corridors that the city is providing. Combined with park areas, the green network is shown and composes the city’s sunny day map.

Nighttime Lightscape Map

At nighttime, people tend to follow the streetlights or stay closer to brighter area for better safety. By using the streetlight location data, we could tell the general brightness of streets during nighttime. Although the streetlight data illustrate the some degree of light source intensity, other light source such as building illuminations, privately installed lights, billboards, etc., were not included in the map, which could be improved if given more information.

Imagine a Contextual Way-finding System

Walking from one point to another, what more suggestion could be provided besides the shortest distance or the fastest? In this project, we tend to provoke new imagination of way-finding tool. With more kinds of data within our reach, maybe we could come up with more creative and useful use case scenario that help people better walk around in the city.

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