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Reference Number ES/X000648/1
Title CARS : Connecting Administrative vehicle data for Research on Sustainable transport
Status Started
Energy Categories ENERGY EFFICIENCY (Transport) 20%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields ENVIRONMENTAL SCIENCES (Geography and Environmental Studies) 50%;
SOCIAL SCIENCES (Town and Country Planning) 30%;
SOCIAL SCIENCES (Sociology) 10%;
PHYSICAL SCIENCES AND MATHEMATICS (Statistics and Operational Research) 10%;
UKERC Cross Cutting Characterisation Sociological economical and environmental impact of energy (Environmental dimensions) 20%;
Sociological economical and environmental impact of energy (Consumer attitudes and behaviour) 40%;
Other 40%;
Principal Investigator Prof JL (Jillian ) Anable
No email address given
Institute for Transport Studies
University of Leeds
Award Type Standard
Funding Source ESRC
Start Date 01 July 2022
End Date 31 March 2026
Duration 45 months
Total Grant Value £845,037
Industrial Sectors
Region Yorkshire & Humberside
Programme ADRP
Investigators Principal Investigator Prof JL (Jillian ) Anable , Institute for Transport Studies, University of Leeds (99.999%)
  Other Investigator Dr RE Wilson , Faculty of Engineering and the Environment, University of Southampton (0.001%)
Web Site
Objectives We aim to provide an annually updatable longitudinal dataset (dating back to ~2006/7) of the characteristics, location, annual mileage and associated emissions of every light-duty vehicle (cars and vans < 3.5 tonnes) in GB, which can be used at national and local levels to support sustainable transport policy design and implementation.We will do this by:1. Developing, in partnership with the DVLA, DVSA and DfT, the methodological and practical specifications for automated annual generation of combined registration and MOT vehicle-level data to be made available via a Trusted Research Environment;2. Developing the processes for a series of aggregated and summarised datasets of vehicle characteristics at an appropriate geographical scale that would be published as either safeguarded or open data as appropriate;3. Solving the practical (e.g. computational), organisational (e.g. data management, storage), ethical (e.g. anonymity) and applied (e.g. training, new policy insight) issues involved in combining these datasets;4. Building longevity and capacity through high-quality documentation and postgraduate and professional training (through secondments) with this data;5. Exploring ways in which this dataset could be enhanced and its utilisation maximised in the future by linking it to, for example, area-based statistics (including Census '21 as they become available), accident statistics, plus other vehicle-level data such as ANPR (automatic number plate recognition) data and telematics.6. Demonstrating the applicability for local transport policy design and evaluation through early pathfinder research project in partnership with two large case study local authority areas. We will evaluate the progress and distributional impacts of local policies to tackle air pollution from passenger cars and the investment of electric vehicle charging infrastructure.
Abstract Our proposal builds on a previous UKRI funded project (referred to as the 'EPSRC MOT Project') and is a timely and exciting opportunity to link and open up two data-sets related to the registration and usage patterns of all vehicles less than 3.5 tonnes ('Light Duty Vehicles') in Great Britain (GB):1. "Registration data": the DVLA's vehicle licensing procedures generate vehicle stock tables, compiled for about 40 million vehicles each quarter, which record the location of the registered keeper through the vehicle's lifetime as well as numerous vehicle attributes. The Department for Transport (DfT) receives this data quarterly and publishes aggregated vehicle licencing statistics with a very limited number of vehicle characteristics. A Vehicle Enquiry Service API can be accessed via special permission but the available fields are limited.2. "MOT data": since 2006, the DVSA has digitally recorded the make, model, age, engine type and odometer reading of every vehicle taking an annual road worthiness ('MOT') test in GB. Approximately 30 million tests and 50 million associated items are added each year. This data has been on public release since late 2010 but the database only includes a vehicle once it has its first test (usually after three years) and so it is only a partial record of all vehicles. The data on public release also does not include the location of the registered keeper. The creation of annual mileages for each vehicle from the odometer reading supplied in the MOT data is computationally complex and formed a core part of the work undertaken in our previous study (see details of our initial study on which we would base the methodology).It is currently impossible for anyone other than the data owners to link these data sources to create a complete database of all vehicles and odometer readings and link these to where they are located in the country. This is because only aggregated or partial data from these two sources is currently on public release. In addition, even where the odometer readings are supplied in the MOT data, the creation of annual vehicle mileages is computationally complex and requires a significant amount of effort and resource to produce robust data. These computations formed a core part of the work undertaken in our previous study and we would base the methodology in this project on those innovations.The goal is that these two sets of data generated by the motoring public are routinely combined, mileage calculations are standardised and automated and an anonymised single set of data is made available. We expect to produce multiple research-ready datasets from this project. Our core 'minimum viable product' (MVP) will consist of:1. 'Vehicle-level Data' which is the most disclosive and stored inside a Trusted Research Environment (TRE) (and from which other product datasets are derived).2. 'Aggregated Vehicle Data' which is aggregated to an appropriate geography, such as LSOA and also stored within a TRE. We will work with the data owners to streamline the way in which these two sets of data generated by the motoring public can be routinely brought together and anonymised so that individual vehicles cannot be identified. We will develop ways of robustly adding mileages and emissions of each vehicle and carry out some exploratory data to show how this data can be used to investigate a whole series of societal objectives related to environmental impacts, road safety, accessibility and efficient and fair investment in transport and energy infrastructure
Publications (none)
Final Report (none)
Added to Database 10/08/22