New micro-location data analytics for improved cross-sectoral policies mitigating transport, environmental and inactivity related societal burdens (KARMA)

People need mobility for access to work, social activities and many services, but the transport sector is one of the main sources of harmful emissions in the UK and how people choose to travel has wide ranging impacts on health, pollution, safety and energy demand.

This research will analyse novel types of high-resolution digital mobility data and other data arising from new technologies, including smartphone and smart city sensors. This will produce a new understanding of individuals’ travel choices, enhanced models covering transport, energy, health, security and safety impacts, and ultimately improved policies for the benefit of individuals, communities and the environment.

This research uses a ‘micro-life’ approach, whereby small changes in levels of physical activity feed through to small but important changes in health (and other) impacts over a period of time. A ‘systems dynamics’ modelling approach is used to capture the interrelations between transport and other sectors, i.e. mathematical equations that reflect how changes in one sector can have impacts on another sector. Previously this type of modelling has been based on aggregate (e.g. city or regional) level data. The research in this project will interface micro-level data into a systems dynamics model.

Impact

The project goals are to create a step change in understanding the cross-sectoral impacts of transport schemes by advanced analytics of next generation transport and other urban data (e.g. phone location signals, sensor data etc). The project aims to:

• Create new databases and model interfaces, with interoperability between ‘next-generation’ data, traditional data and mathematical models
• Enhance existing mathematical models of transport-energy, transport-health, transport-security and transport-safety impacts, building new models to fill research gaps
• Explore the cross-sectoral implications of existing and new initiatives (such as the use of positive incentives, rewards and gamification) in travel choice
• Improve the asset base (ecosystems and platforms) that support increased analysis and use of new digital mobility data, so that improved policies and initiatives can be developed and implemented (e.g ethical frameworks, digital innovation, impact visualisation, business models).

The main area of application is in the development of transport policy by those working in the transport sector at local, regional or national level. Policies that relate to the health sector, particularly those that encourage more active travel choices will also be better supported. Other sectors that relate to transport will benefit, including the local environment (through air quality), safety, security and energy.

Finally, the project will contribute to the development of national data infrastructure by the demonstration of the qualities, characteristics and usability of new location based digital data.

Publications and outputs

Grant-Muller, S.M., Harrison, G., and Hodgson, F. 2020. Sustainable Urban Mobility: How to get people out of their cars.

EC Committee of The Regions/UITP, Brussels Harrison, G., Grant-Muller S. M. Hodgson F. C. 2020. New and emerging data forms in transportation planning and policy: Opportunities and challenges for “Track and Trace” data. Transportation Research Part C: Emerging Technologies, 117, p102672. https://doi.org/10.1016/j.trc.2020.102672

Harrison, G., Grant-Muller S. M. Hodgson F. C. 2021. The Role of New Data & Technologies in Transport-Related Health: An online Delphi Approach to Model Building. System Dynamics Society Special Interest Group in Transportation Annual Workshop.

Harrison, G., Grant-Muller S. M. and Hodgson F. C.. In Proof. A Review of Transport-Health System Dynamics Models. Journal of Transport & Health.

Project website

https://www.turing.ac.uk/research/research-projects/new-data-forms-transport-policies

Grant

R-LEE-006