We utilise DVLA data and statistics to track the number of vehicles still registered, taxed, and declared SORN (Statutory Off Road Notification) in the UK. It provides a detailed snapshot of vehicle survival rates, offering enthusiasts and analysts insight into the trends and longevity of various makes and models over time.
The majority of variables reported are recorded by DVLA for administrative purposes only and any errors can take time to be resolved, especially if they do not impact the taxation or keepership of the vehicle. Common inconsistencies include:
Due to the encoding system used for makes and models, data can be missing for a variety of reasons. These include:
All information on this site originates from vehicle licensing statistics released by the Department for Transport and the Driver and Vehicle Licensing Agency (DVLA) in the UK.
Contains public sector information licensed under the Open Government Licence v3.0.
Generic model is a grouping of models to help compare models on the road. Manufacturers vary in their approach on how many model versions they give a particular range of vehicles. For example, there are currently 3 model versions for Tesla Model 3, but there are over 800 model versions for Ford Fiesta.
The limitations of these make and model statistics are not errors in the DVLA database, but issues with the statistical process used.
If a vehicle keeper believes that there is a specific error on the V5 document for their own vehicle, they should contact the DVLA directly to have this corrected.
Vehicle manufacturers submit vehicle information at point of first registration and DVLA do not change it unless prompted. This means that most mistakes in the final data are usually because of administrative errors made by the manufacturer. Other mistakes can occur when vehicles are registered manually using a paper form as there is opportunity for typographic errors.
Other issues include
Any vehicle of a given model name which cannot be found in the data will most likely be included in the missing categories.