14 MAY 2026 (WED) 15:05 - 15:35

Spatial Mobility for Sustainable Transport

Mr HUANG Zhucheng    

( Supervisor: Prof Becky P.Y. Loo )

Abstract:

Constructing sustainable, inclusive, and resilient transport systems has become a key objective worldwide. However, current practices of sustainable transport face multiple challenges: A unified framework for assessing and monitoring its potential has yet to be established. Furthermore, constrained by privacy issues and data resolution, detailed and dynamic evaluations are difficult to conduct. Additionally, existing measurements mainly focus on service levels or the environment, failing to measure the contribution of sustainable transport in reducing social segregation and promoting social inclusion. Spatial mobility serves as a bridge connecting physical space and social life. It not only reflects the activity potential of people enabled by the transport system, but also captures chosen travel paths and their social effects. In light of this, this research introduces a spatial mobility perspective to assess sustainable transport, establishing a comprehensive quantitative framework through the logic of potential-actuality-outcome at the city scale.

Focusing on potential mobility, this research systematically reviews the United Nations Sustainable Development Goals (SDGs) to construct a comprehensive assessment framework with a dual national-city dimension. Based on OpenStreetMap (OSM) data, local statistics and WorldPop data, the sustainability performance and the potential transport supply are evaluated through normalisation, weighting, and aggregation. Focusing on empirical mobility, the focus shifts to micro-level behavioural dynamics at the city level. Relying on multi-source data including Travel Characteristic Survey (TCS) and population censuses, an efficient deep generative model (DGM) is incorporated to generate a diverse and feasible synthetic population based on empirical validation. This method enables the effective simulation of complex, real-world travel choices and flows, providing a micro-level data engine for the detailed evaluation of sustainable transport systems. Focusing on mobility outcomes, this research extends its perspective to the social impacts caused by spatial mobility. Using datasets such as Replica and Dewey, social segregation is investigated across place, individual, and activity levels. By calculating relevant social mixing indices, the degree of spatial interaction among different income groups during day time is quantified, thereby uncovering the role of public and active transport in reducing social segregation.

Taking spatial mobility as a starting point, this research constructs a potential mobility-actual mobility-mobility outcome framework, providing a new evaluation pathway for sustainable transport. This research bridges the gap caused by the lack of an assessment framework for sustainable transport potential, and provides both conceptual and practical support for its detailed and dynamic evaluation. Simultaneously, through the analysis of social mixing, it establishes spatial social interaction as a benchmark for testing the sustainable performance of transport systems, revealing the actual social impact of transport systems.