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Work in Repl.it

Group 1007 - UK traffic accidents

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Milestones

Details for Milestone are available on Canvas (left sidebar, Course Project) or here.

Describe your dataset in about 150-200 words

The dataset that our group has chosen for our project was provided by the UK Department of Transport, and displays car accidents throughout multiple areas of the United Kingdom. The dataset shares information on car accidents from 2005-2014 (however 2008 data is missing) in the UK. Many characteristics are identified per accident in the dataset such as the location, date, severity, number of vehicles, light and weather conditions ect. The purpose of this dataset is to observe regions, road types, times of year and other road elements that cause car accidents and use the data to potentially predict accident rates and help improve them over time. With this data one can observe what characteristics of the road can cause vehicular accidents and perhaps use this knowledge to produce ways of mitigating accident risk. The accident data was collected by digitized records of the accident's characteristics/location as stated by police and insurance companies.

Describe your topic/interest in about 150-200 words

Using this data, we can examine differences in traffic accident rates among a variety of different conditions both environmental and artificial. For example, are accidents more commonplace during periods of high wind or wet road conditions? Does the time-of-day effect play a role in accident prevalence or severity and is this effected more by light conditions (i.e. daylight vs streetlight vs no light) or alertness of the driver, owing to the time of day? We can also examine things like speed limits or the type of road in assessing driver risk. It may be that higher speed leads to more severe accidents but fewer total accidents as they occur on straighter sections of road (or not!). Overall, the data seems well suited to the creation of visualizations and open to analyzation. By the end of the project, it may be possible for someone to filter the data by number of casualties by highway designation to deduce “The Most Dangerous Road in the UK” or any number of other interesting statistics or anomalies that present themselves.

Team Members

  • Conner Gauthier: I enjoying skiing!
  • Turner Woodroff: I'm a big fan of basketball.
  • Dima: A second year CS student who knows cool stuff <3

Group Presentation

https://youtu.be/CUwCwnI6a6k

References

Data used for analysis - Link to data