Thesis & Design Research

Between Destinations

Project Details

Programme
Urban Design MArch
Cluster
RC15
Students
Bor-En Huang, Qianqian Wang, Shanshan Gao

Project Overview

The project investigates the hidden emotional costs embedded in London's public transport system. While efficient on the surface, the network imposes overlooked burdens on its most dependent users, such as long commutes, cognitive fatigue, and emotional strain. These impacts are rarely addressed in transport planning, yet they deepen urban inequality.

Using geospatial analysis, public transport accessibility level (PTAL) mapping, and wearable GSR sensors, the group mapped emotional stress across transit journeys in Stratford (East London), revealing unequal experiential geographies, and how, for many, public transport is not a path to opportunity but a mechanism of urban injustice.

In response, the project proposes a dual intervention: a mobile app that tracks users' emotional states in transit, offering a live affective overview of the network and suggesting neurodiverse routes; and a parasitic architectural system embedded in multimodal hubs, offering spaces from quiet rest to collective events, in a process that transforms commuting into civic time and reimagines mobility as a shared spatial practice of care.

Project Introduction

Project Gallery

01

Transport Gaps

This analysis examines transport infrastructure to uncover regional disparities and shifts over time. By identifying gaps in urban functionality, it highlights where services fall short and where interventions are most needed.

02

Facility Services Analysis

The study examines transportation infrastructure to reveal regional disparities and shifts over time. By highlighting gaps in urban functionality, it provides insight into where improvements are needed for more balanced city access.

03

Sensing Transport

Using the four most common routes in the monitored community, this analysis captures and compares travel experiences across different transport modes, revealing how mobility shapes daily routines and perceptions of the city.

04

t-SNE Spatial Clusters

By compressing multi-vector data into 3D space with t-distributed Stochastic Neighbor Embedding (t-SNE), zones of similar negative experiences cluster together. These patterns form the basis for spatial growth.

05

Principles of Data Collection

Wearable devices capture shifts in physiological activity as people move through the city. By measuring skin potential changes triggered by perception, they reveal how urban environments affect the body and shape lived experience.

06

Data Translation and Skeleton Generation

Growth locations and skeletal structures are translated from two-dimensional data via the wool algorithm, then combined with site characteristics and visible construction zones to generate the parasitic structures.

07

Strategic Overview

This project uses sensors to explore hidden issues of urban mobility. Through data analysis and spatial translation, it creates parasitic spaces that amplify human perception and reconnect people with the city in a dynamic, symbiotic way.

08

Rendering and Possibility

Human perception resonates with the urban fabric, blurring the line between observer and environment. Through sensory exchange, people and cities co-transform, creating a feedback loop where space is continually redefined.

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