This document summarizes a research project that examines the connection between driver risk perception and traffic accident involvement. The project was conducted in Kottayam district, India through a questionnaire given to licensed drivers aged 18-68. The objectives were to determine if driver perception influences accidents and suggest solutions to minimize accidents. Reliability analysis and descriptive statistics were performed on the data. Multiple regression analysis found that speeding, short headways, and anger were significant predictors of higher risk perception. Recommendations included promoting safety awareness, installing vehicle safety technologies, and enforcing traffic laws.

1. CAR DRIVER’S
RISK PERCEPTION

2. ABOUT
• Project focuses on the connection between risk perception and involvement in
accidents.
• Understanding the factors related to the driver risk assessment, the ability to
define adequate measures increases which should reduce the negative
consequences of inappropriate behavior.
• Kottayam district is selected as the domain for conducting the project.
• The project progresses by conducting a questionnaire survey for licensed
drivers aged between 18-68.

3. OBJECTIVE
The project aims to analyse if the between driver behaviour and their
commitment in traffic accidents.
The main objectives of this project are;
1. To know whether drivers perception has any significant role in accident
causation.
2. To suggest solutions to minimize accidents.

4. METHODOLOGY
Identification
of problem
Literature
Review
Questionnaire
preparation
Data
Collection
Analysis of
data
Interpretation
of results
Identification of problem
Literature Review
Questionnaire preparation
Data Collection
Analysis of data
Interpretation of results
Recommendations

5. ANALYSIS
Reliability Statistics
Cronbach's Alpha Cronbach’s-Alpha
based-on
Standardized Items
No of Items
.829 .826 14
Reliability coefficient (Cronbach’s Alpha)
Table1:Reliability Analysis of Variables

6. Descriptive statistics
Variables Mean Std. Deviation
Age 31.30 12.907
Driving-experience 8.52 8.217
Driving speed 3.07 .821
Driving ability 3.88 .756
Drive frequency 4.51 2.141
Table 2: Mean and Standard deviation of age, driving
experience, driving frequency, Driving speed, Driving ability

7. Table 3: Distribution of gender, qualification
Sex % Qualification %
Male 67.
5
School 10.6
Female 32.
5
UG 42.3
PG 30.9
Others 14.6

8. Independent variables:
 Years of driving:
 Anger behaviour
 Driving Ability
 Speedy driving
 Headways
Dependent variable:
 Driver’s risk perception
Multiple regression analysis

9. R .8656
R 2 .799
Adjusted R 2 .782
Std. Error of the Estimate 5.69
From the table above 79.9% of variations of accident risk perception is explained
by the independent variables
Table 4:model summary

10. Model
Unstandardized
Coefficients
Standardized
coefficients
t Sig.B Std.Error Beta
(Constant) .449 .56 8.067 .000
Speedy driving .010 .033 .569 3.250 .014
Anger Behaviour .142 .049 .555 3.198 .032
Driving Ability -.141 .044 .554 2.857 .864
Headways .108 .053 .429 2.444 .046
Driving Experience .101 .044 .256 1.660 .086
Table 6: Parameter estimates and fit of the linear

11. CONCLUSIONS
• Multiple regression analysis is applied to identify the characteristics of drivers
that contribute to a more risky driving behaviour
• From the analysis part it has been clear that factors such as speedy driving,
headways, anger behaviour are significant predictors of accident risk perception.
• The standardized beta value for speedy driving and anger behaviour are the
highest which means that these factors have slightly more impact on this model.
• The conclusions of the present study could contribute towards the improvement
of driving behaviour and road safety level if appropriate measures are taken.
• So recommendations are needed to avoid these behaviours on roads.

12. RECCOMENDATIONS
1. Road users
• Do not exceed the speed limits
• Know about the signs at different area
• Do not follow too closely
• Respect the right of way of everyone
• Manage your stress.

13. 2.Vechicle manufactures
• Modifications should be made to ensure better safety in vechicles.
• Speed Monitoring on Graph
• SMS and Email Alerts received from the GPS Trackers
• Intelligent speed adaptation
• Electronic Data recorders

14. 3.Government
• Raise safety education and awareness programs.
• Covert or overt use of cameras
• Penalities-fines, licence suspension
• Speed compliance incentives
• Community based programmes