Yikang Wang

Image: ULEZ

Research

Subject

Exploring the Impacts of Charging Zones on Human Mobility Using Mobile Phone Location Data and a Causal Inference Approach

First and second supervisors 

Abstract

Charging zone policies aim to reduce the number of polluting vehicles in high-traffic areas by charging fees based on vehicle emissions and have been, or are planned to be, implemented in various cities across the world, including 14 cities in the UK. This research is dedicated to investigating the effects of such charging zone policies on human mobility. The research conducted is particularly focused on the London Ultra Low Emission Zone (ULEZ) and its expansions. 

The study employs mobile phone location data to quantify human mobility. After detecting users’ stays, frequent visit locations, and travel modes, this research utilises a set of mobility indices, including the number of activities, activity locations, travel distance, and travel mode choice. These indices offer a fine-granularity perspective on how individual travel behaviour shifts in response to charging zones. 

To further understand the cause-effect relationship, we employ causal inference methods. Through utilising the Difference-in-Difference (DiD) model, the Interrupted Time Series (ITS) model, and improving these models for spatial causal inference. We further utilize the spatiotemporal transferability of causal relationships to conduct spatiotemporal causal predictions. This approach provides a nuanced understanding of how the impacts of these policies evolve over space and time, and across different population groups. 

This thesis provides a robust analytical framework for exploring the consequences of charging zone policies on human mobility, leveraging big data and causal inference approaches. The insights from this research hold significant implications for the design and implementation of future urban mobility and sustainable transport policies, underscoring the value of a data-driven, human-centred approach to achieving environmental sustainability in our cities. 

Biography

Yikang Wang is a PhD student at CASA UCL. He holds a bachelor’s degree with honours in Geographic Information Science (GIS) from Wuhan University and a Master’s in Computational Science from Imperial College London. His research focuses on exploring the impacts of transport policies, such as the Ultra Low Emission Zone (ULEZ), on human mobility. Utilising mobile phone location data and spatial causal inference approaches, his work provides key insights into travel behaviour, policy evaluation, and sustainable urban transport strategies.  

In addition to his research, Yikang serves as the co-chair of the non-profit organisation GISphere Corporation, and is a student board member of CPGIS (The International Association of Chinese Professionals in Geographic Information Sciences).

Publications

  • Gao, Q.L., Zhong, C. and Wang, Y. (2024). ‘Unpacking urban scaling and socio-spatial inequalities in mobility: Evidence from England’, Environment and Planning B: Urban Analytics and City Science. Available at: https://doi.org/10.1177/23998083241234137 
  • Wang, Y., Kang, Y., Liu, H., Hou, C., Zhou, B., Ye, S., Liu, Y., Rao, J., Pei, Z., Ye, X. and Gao, S. (2023). ‘Choosing GIS graduate programs from afar: Chinese students' perspectives’, Transactions in GIS, 27(2), pp.450-475. Available at: https://doi.org/10.1111/tgis.13037 
  • Wang, Y., Zhong, C., Gao, Q. and Cabrera-Arnau, C. (2022). ‘Understanding internal migration in the UK before and during the COVID-19 pandemic using twitter data’, Urban informatics, 1(1), p.15. Available at: https://doi.org/10.1007/s44212-022-00018-w 

Please see the full list of publications on Google Scholar. 

Funding

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