How can cities plan better when travel data is limited?
Published on the 21 July 2026
Photo above L-R: Kartikeya Gaur, Meead Saberi, Taha Hossein Rashidi, Dr Prateek Bansal, Donghyun Kwon.
Dr Prateek Bansal Presidential Young (Assistant) Professor at the National University of Singapore (NUS), made a presentation to the Research Centre for Integrated Transport Innovation (rCITI), the seminar explored how artificial intelligence, open data, and advanced data fusion techniques are helping overcome one of transport planning's biggest challenges鈥攍imited mobility data.聽
Origin-destination (OD) data is fundamental for understanding how people move through cities, yet many cities lack comprehensive travel datasets. Dr Bansal demonstrated how combining household travel surveys with passively collected mobility data鈥攕uch as smart card records, cellular data, and time-dependent origin-destination (TD-OD) matrices鈥攃an create a far richer understanding of travel behaviour than either data source alone. This approach enhances the diversity and accuracy of synthetic travel data while preserving privacy, enabling more realistic activity-based transport models for planning and policy development.聽
A key focus of the seminar was cross-city learning, an emerging approach that transfers knowledge from data-rich cities to those with cities that have limited transport information. Rather than relying solely on city-wide similarities, Dr Bansal's research identifies the most appropriate source regions within other cities to predict travel demand more accurately. Validated using real-world data from 50 cities across the United States, the research demonstrates how open data and machine learning can support evidence-based transport planning, even where detailed local data are unavailable.
The seminar highlighted the growing potential of data fusion and cross-city learning to support smarter mobility decisions and better outcomes for communities. By integrating travel surveys, smart card records, and large-scale mobility datasets, researchers can generate richer insights into how people travel, improve transport models, and provide planners with stronger evidence to guide future investment and policy. These innovations represent an important step towards more sustainable, efficient, and equitable transport systems.
Taha Hossein Rashidi and Dr Prateek Bansal
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