A Case Study on Traffic Violations in

the City of Colombo

Udara Perera

Sandun Silva

Oshada Senaweera

Yogeswaran Akhilan

Amani Subawickrama

Introduction

Driving is very important for working, social life, entertainment, economic, recreational and other reasons

Number of registered vehicles in Sri Lanka have risen from 3.1 million in 2007 to 5.6 million in 2014

During last two decade approximately 25,000 km road were added to the national grid.

Violation in traffic laws are very common in Sri Lanka

Traffic law violations are a contributing factor to the majority of road accidents that occur in Sri Lanka

Objectives of the study

Identify the most frequent traffic law violations in Colombo

Examining the factors that influence traffic law violations

Identify the relationship between traffic law violations and other factors

Build a suitable model to predict the probability of doing a traffic law violation

Data Collection

Response variable

Violation type

Predictor variables

Location, vehicle type, gender of the driver, age of the vehicle, time, number of passengers

Target population

Motor vehicles using the roads in Colombo area

Sampling technique

Stratified sampling based on the type of location

Data Collection (ctd)

Data Collection (ctd)

Data collection method

Observational study

Analysis and Interpretation Univariate Analysis

Not d

rivin

g in

pro

per l

ine

Soun

ds a

nd ligh

t war

ning

s

Not w

earin

g se

at b

elts

Cuttin

g th

e lin

es

Wro

ng o

vertak

ing

Wro

ng p

arking

Posit

ion

of th

e dr

iver

Righ

t rul

e in

roun

dabo

uts

0

5

10

15

20

25

30

35

Frequency of violation types

Violation type

Frequency

Analysis and Interpretation (ctd)

New Moderate Old0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

14.4%

71.3%

14.4%

Percentage of vehicles by age

Age of the vehicle

Perc

enta

ge

Car

Thre

e-whe

eler

SUV

Mot

or B

ike

Van

Bus

Heavy

veh

icle

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

26.4%25.7%

14.2%12.8%

8.9% 8.9%

3.1%

Percentage of vehicle types

Vehicle type

Perc

enta

ge

Analysis and Interpretation (ctd)

4.7%

95.3%

Percentage of the gender of driver

Female

Male

One p

asse

nger

Two

pass

enge

rs

Thre

e pa

ssen

gers

Four

pas

seng

ers

Five

pas

seng

ers

Mor

e th

an fi

ve p

asse

nger

s0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

40.0%

45.0%

40.7%

33.4%

11.7%1.9% 1.1%

11.2%

Percentage of number of pas-sengers

Number of passengers

Perc

enta

ge

Analysis and Interpretation (ctd)

Relationship Analysis

Relationship between violation and road type

H0 : There is no relationship between violation and road type

H1 : There is a relationship between violation and road type

P value = 0.007 (<0.05)

Reject H0 at 5% significance level.

Violation depends on the road type

One-w

ay ro

ad

Two-

way

road

T ju

nctio

n

Cros

s ju

nctio

n

Mor

e th

an fo

ur w

ay ju

nctio

n0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

79.4%

60.0% 63.8% 65.2% 63.9%

20.6%

40.0% 36.2% 34.8% 36.1%

Violation

No violation

Road Type

Perc

enta

ge

Analysis and Interpretation (ctd)

Relationship between violation and vehicle type

H0 : There is no relationship between violation and vehicle type

H1 : There is a relationship between violation and vehicle type

P value = 0.048 (<0.05)

Reject H0 at 5% significance level.

Violation depends on the vehicle type Ca

r

Mot

or B

ike

Thre

e-whe

eler

SUV

Van

Bus

Heavy

veh

icle

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

26.0%31.7%32.1%35.2%

40.4%43.9%55.0%

74.0%68.3%67.9%64.8%

59.6%56.1%45.0%

No violation

Violation

Vehicle Type

Perc

enta

ge

Analysis and Interpretation (ctd)

Relationship between violation and age of the vehicle

H0 : There is no relationship between violation and age of the vehicle

H1 : There is a relationship between violation and age of the vehicle

P value = 0.622 (>0.05)

Do not reject H0 at 5% significance level.

Violation is independent of the age of the vehicle

New Moderate Old0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

70.7%66.3% 64.1%

29.3%33.7% 35.9%

Violation

No violation

Age of the vehiclePerc

enta

ge

Analysis and Interpretation (ctd)

Relationship between violation and gender of the driver

H0 : There is no relationship between violation and gender of the driver

H1 : There is a relationship between violation and gender of the driver

P value = 0.047 (<0.05)

Reject H0 at 5% significance level.

Violation depends on the gender of the driver Female Male

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

83.3%

65.8%

16.7%

34.2%

Violation

No violation

Gender of the driver

Perc

enta

ge

Analysis and Interpretation (ctd)

Relationship between violation and time

H0 : There is no relationship between violation and time

H1 : There is a relationship between violation and time

P value = 0.022 (<0.05)

Reject H0 at 5% significance level.

Violation depends on the time

Non-peak hours Peak hours0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

70.3%61.6%

29.7%38.4%

Violation

No violation

Time

Perc

enta

ge

Analysis and Interpretation (ctd)

Relationship between violation and number of passengers

H0 : There is no relationship between violation and number of passengers

H1 : There is a relationship between violation and number of passengers

P value = 0.347 (>0.05)

Do not reject H0 at 5% significance level.

Violation is independent of the number of passengers

One p

asse

nger

Two

pass

enge

rs

Thre

e pa

ssen

gers

Four

pas

seng

ers

Five

pas

seng

ers

Mor

e th

an fi

ve p

asse

nger

s0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

69.3% 67.3% 65.3%75.0%

57.1% 55.6%

30.7% 32.7% 34.7%25.0%

42.9% 44.4%

Violation

No violation

Number of passengers

Perc

enta

ge

Model Fitting Binary logistic regression model

Logit (Pi) = -0.653+0.386 Time(1) – 0.857 Location(1) + 0.051 Location(2) – 0.127 Location(3) – 0.174 Location(4)

Here,

Pi = Probability of violating a traffic law Time(1)= Peak hours

Location(1)= One-way Location(2)= Two-way

Location(3)= T-junction Location(4)= Cross junction

Eg:- Consider a vehicle at a one way road in peak hours

Logit (Pi) = -0.653+ 0.386(1)-0.857(1)+0.051(0)-0.127(0)-0.174())

Log (Pi/1-Pi) = -1.126

Pi/1-Pi = exp(-1.126)

Pi = 0.245

Thank You