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ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

ROAD FATALITIES IN THE US

Marion Farat/Ahmed Gaber/Kalyana Gugan

ENAC

January 16, 2013

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

SUMMARY

1) Study Definition

2) Scatter Plots

3) Regression Model

4) Conclusion

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

Study DefinitionThe purpose of our study is to analyse the factors thatinfluenced the fatalities in 2009 in the United States.

Explanatory Variables:

• Drivers under the influence of alcohol

• Gross state product

• Number of law enforcement employees (per 1,000 people)

• Percentage of urbanized area

• Population density

• Precipitation (mm)

• Speed limit (Mph)

• Sex ratio

• Average temperature

• Unemployment rate (per 1,000 people)

• Number of vehicles (per 1,000 people)

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

Study DefinitionInterest of study - Number of fatalities per 1,000 people

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

Scatter Plots

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

Scatter Plots

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

Scatter Plots

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

Scatter Plots

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

Scatter Plots

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

Regression Model

FP1 = β1.AI + β2LEEP + β3.PUR + β4.SL + β5.SR + β6.T +β7.GSP + β8.RN + β9.UR + β10.VRP + β11PD + β12

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

Regression Model

FP1 = 0.555.AI + 1.607.LEEP − 0.114 ∗ PUR + 0.137 ∗ SL−0.361 ∗ SR + 0.314 ∗ T − 0.0057 ∗ GSP + 0.00094 ∗ RN −0.00064 ∗ UR + 0.0084 ∗ VRP − 0.0035 ∗ PD + 23.59

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

Regression Model

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

Regression Model

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

ConclusionOf our model data

Road Fatalities increases with increase in the following

• the speed limit

• the number of vehicles

• the number of drivers under alcohol influence

Urbanization has an impact on Road Traffic fatalities onlywhen the value is high.

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

ConclusionOther explanatory variables

• Daylight

• Road infrastructure

• Emergency efficiency

• Snow and icing condition

• Terrain

ROADFATALITIESIN THE US

MarionFarat/AhmedGaber/Kalyana

Gugan

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