Using Motor Vehicle Testing Data to Investigate Patterns of Vehicles and Energy Use.
Paul Emmerson, Transport Research Laboratory, Sally Cairns, Transport Research Laboratory, Professor Jillian Anable, University of Leeds
The paper presents results of the analysis of car ownership, use and energy consumption and their relationships to transport models that have been made possible by linking motor vehicle testing data with licensing and locational data in the UK.
Using motor vehicle testing data to investigate patterns of vehicles and energy use.
Paul Emmerson, Transport Research Laboratory, Dr. Sally Cairns, Transport Research Laboratory, Professor Jillian Anable, University of Leeds, Simon Ball, Transport Research Laboratory, Dr. Tim Chatterton, University of the West of England, Professor Eddie Wilson, University of Bristol.
The 'MOT' vehicle inspection test record dataset recently released by the UK Department for Transport (DfT) provides the ability to estimate annual mileage figures for every individual light-duty vehicle greater than 3 years old within Great Britain. Vehicle age, engine size and fuel type are also provided in the dataset and these allow further estimates to be made of fuel consumption, energy use, and per vehicle emissions of both air pollutants and greenhouse gases. The use of this data permits the adoption of a new vehicle-centred approach to assessing emissions and energy use in comparison to previous road-flow and national fuel usage based approaches. The dataset also allows a spatial attribution of each vehicle to the postcode of the registered keeper, through a linkage to the vehicle licensing data. Consequently, this new vehicle data can be linked with socio-demographic data, such as the 2011 census data at LSOA-level, in order to investigate spatial patterns of vehicle use and emissions and the relationship with socio-demographic characteristics at a variety of spatial scales.
The first part of the paper describes the process of linking the ‘MOT’ testing data and the licensing data to a vehicle data base of over 50 million vehicles tested between 2006 and 2014. The second part of the paper will describe some of the areas of investigation that the multi-disciplinary study team have explored using this data-set including studies of the spatial variations in vehicle use and the implications for vehicle energy use by where the vehicle is registered, the impact of the distributions of vehicle characteristics within the census areas, and the relationship of such patterns to vehicle use patterns from traditional transport models. Finally the paper will look forward to the potential uses of such as data-set from a time-series, and a policy assessment perspective.
Association for European Transport