Accident, Vehicles and casualty data

The data used was taken from the Department for Transport and can be accessed through the buttons below.

The file is called AADF Data - major and minor roads, which contains the CSV files that were imported into Tableau. All road traffic data was from 2018 and published in 2019.

Tableau was utilised for the data visualisation since it was a free tool, as well as being able to do what this project required from us. The charts displayed within this site are linked to Tableau, where one can read the graphs in more detail if they wish to do so.

The data was a large set that was a combination of qualitative and quantitative data. There was also a large proportion which was nominal data.

The data was re-purposed, as it was not originally collected for the purpose of this report. The result of this is that there could not be any selection-bias and therefor is more natural. Although there are still biases, they are minimised since the data has been collected organically.

The data used constitutes as big data and having to identify trends and patterns without the use of technology would be very time consuming and tedious, opening it up to human error.

The data was analysed for insights, to be able to direct policy makers in how to make better informed decisions and map their organisations strategies.

This reports approach to the data begins by looking at the general trends noticed broadly across the whole data set and then identifies some areas where risks to vehicle occupants/passengers/road users is significantly raised.

Due to the breadth of the data set, to create an accurate projection of what the narrative of this data is would require a multidisciplinary team of individuals working collaboratively to really take the data apart and extract the vital parts of information, such as 'why do accidents occur at peak times?' 'Are there conditions with increase the risk of accidents?'

This report is an attempt to decode the data set.