Factors in crash outcome - Advanced options
Explore how certain variable effect the outcome of a car crash!
The probabilities are based on data from the Queenland Government containing information about demographic, vechicle types, crash types, the condition of the driver ect. Using the Naive Bayes classifier, we calculate the posteriori probability which is based on the likelihood and the prior probability. However, all the attributes are assumed to be independent of each other. The order of the attributes reflects their contribution to the classifiers total F-measure. So filling out the attributes from top to bottom provides the most accurate results, you are however, free to fill in whatever attributes you wish!
For the simplified version:
Simple options
Type of crash:
Hit pedestrian
Single Vehicle
Multi Vehicle
Other
Unknown
Crash involving motorcycle:
Yes
No
Unknown
Speed limit of the road:
0 - 50 km/h
60 km/h
70 km/h
80 - 90 km/h
100 - 110 km/h
Unknown
Driver is driving while intoxicated:
Yes
No
Unknown
Driver is speeding:
Yes
No
Unknown
Crash involving truck:
Yes
No
Unknown
Unlicensed driver:
Yes
No
Unknown
Female driver:
Yes
No
Unknown
Crash nature:
Angle
Collision - miscellaneous
Fall from vehicle
Head-on
Hit animal
Hit object
Hit parked vehicle
Hit pedestrian
Non-collision - miscellaneous
Other
Overturned
Rear-end
Sideswipe
Struck by external load
Struck by internal load
Unknown
Federal electorate:
Blair
Bonner
Bowman
Brisbane
Capricornia
Dawson
Dickson
Fadden
Fairfax
Fisher
Flynn
Forde
Griffith
Groom
Herbert
Hinkler
Kennedy
Leichhardt
Lilley
Longman
Maranoa
Mcpherson
Moncrieff
Moreton
Oxley
Petrie
Rankin
Ryan
Wide Bay
Unknown
Male driver:
Yes
No
Unknown
Fatigued driver:
Yes
No
Unknown
Atmospheric condition:
Clear
Fog
Raining
Smoke/Dust
Unknown
Lighting condition:
Darkness - Lighted
Darkness - Not lighted
Dawn/Dusk
Daylight
Unknown
Crash involving bus:
Yes
No
Unknown
Fatality
2%
Hospitalised
37%
Medical treatment
41%
Minor injury
18%