analysis of accidents at curves

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XQ541

Writing

Description

The purpose of the project is to identify spatial trends and patterns of traffic fatality accidents at curves in the state using Geographic Information Systems (GIS). The study will identify the counties with the highest rate of automobile fatalities based on curves and will also examine whether any urban/rural patterns exist in the frequency of fatal traffic accidents. The study will also examine driver factors, roadway conditions, and types of roads involved in the fatal accidents. Maps showing all the above factors and criteria will be produced to provide a visual representation of the FARS data that would make evident the factors involved in accidents and identify the most deadly roadways in Texas.

chapter 1

1.1 characteristic of accidents

1.2 accident type

1.3 accident severity

1.4 surface conditions

1.5 analysis of accidents

1.6 factors that influence accidents at curves

1.7 basic parameters of curve geometry

Chapter-2: Literature Review 10

2.1 Accident Causative Factors

2.2 Accident Prediction Model

2.3 Accident Optimisation Model

Chapter-3: Empirical Data Collection and Extraction 15

3.1 Data Collection( data should be collected from txdot from 2014-15)

3.1.1 Topographic Survey

3.1.2 Topographic Survey Methodology

3.2 Accident Record

3.2.1 Traffic Volume

3.2.2 Traffic Survey Methodology

3.3 Data Extraction

3.3.1 Data Extraction Methodology

3.3.2 Horizontal Radius

3.3.3 Deflection Angle

3.3.1.3 Horizontal Arc Length

3.3.1.4 Superelevation / Cross Fall

3.3.1.5 Rate of change of Superelevation

3.3.1.6 Vertical Gradient

3.3.1.7 Vertical Curve Length

3.3.1.8 K-value of Vertical Curve (K)

3.3.1.9 Visibility /Sight Distance

chapter 4

4.1)design safety features for curves to prevent the accident rate.

4.2)counter measures

chapter 5

5.1)gis mapping(atleast 30 dangerous curves should e identified in gis)

chapter 6

results

chapter 7

discussion

Model Development, results, and Discussions

Development of crash Prediction Models with geometric Data

Development of crash Prediction Models with sign Data

brief analysis of results

chapter 8

conclusion

chapter 9

references (at least 15)

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