evaluation of transport safety policies in commercial motorcycle operation in nigeria

Institute for Transport StudiesFACULTY OF ENVIRONMENT

A Model for the Evaluation of Transport

Safety Policies in Commercial Motorcycle

Operation in Nigeria

A PhD research work undertaken by

Aluko O.O

Under the supervision of

Astrid Gühnemann; Paul Timms

ITS, University of Leeds

Research Background and

Objectives

• Commercial motorcycles play important role

in developing countries’ transport

– Accessibility

– Employment

• Lack of regulation and enforcement lead to

significant safety problems

Objectives:

A. Identify and understand factors

contributing to the safety problem and their

relationships (focus on violations)

B. Develop a dynamic model to understand

how driver behaviour develops and is

influenced by external conditions

Case-study peculiarities

Unavailability of data

Opposing views about the benefit of the mode

• Here: Nigeria

(Ado Ekiti)

• Similar issues

encountered

in most

developing

countries

• Safety often

analysed without

considering

possible

feedbacks

Fieldwork survey

Interviews

Quantitative data extraction

Interviews were

conducted to obtain

mental pictures of

stakeholders about how

the system is operating.

This helps to provide

reference modes, initial

conditions, and

constants

Data analysis

Nvivo Data analysis

Helped to identify themes and linkages

Helped to provide an audit trail of the analysis process

Data analysis (cont’d)

Development of causal

network Generation of a narrative

• … more violations (10) led

to more enforcement

capacity (1) which led to

reduced drivers’ income

(7)… This was because

violations (10) offered some

financial benefits too

(increased drivers’ income

(7)).

Generation of dynamic hypothesis

Excerpt from the narrative

“Whenever violations increased,

more officers were drafted to

increase enforcement capacity

(1) and match the problem. This

obviously would result in

increase in the probability of

detection (4) and violation would

go down…In this way,

increasing enforcement capacity

(1) could reduce the total

number of violation (10)”

Corresponding hypothesis

Officers enforce law by

detecting and arresting

violators.

Causal loop diagram

number ofdrivers

awarenessof high job

returns

ease ofjoiningtrade

competitionfor

passengers

targetincome working

period

hirepurchseand rent

drivers'income

fatigue

high jobreturns

violations

alcoholand drug

use

availablefree time

level oftraining

risky anddangerous

drivers

+

++ +

+

+

-

-

Drivers'

populatio

n loop

Drivers'population

loop

+

-

+

+

+

+

+

+

competitionreducedrivers'

population

trade is

strenuous

loop

expensive

ownership

options loop

+

+

+

+

+

+

deterrenceeffect ofsanction

-

workcapacity

+

+

--

+

willingness

to give time

for training

+enforcement

coverage

corrupt practicesin regulation and

enforcement

politicalinfluence

dodgingarrest prosecution

rate

probability ofdetection

arrests leadingto prosecution

+

+

+

-

-

-

+

+

+

+

nationalcorruption

index

+

deterrenceloop

detection

loop

+officers'benefitfrom

rent paid

-

+ rent toofficers'

loop

time fortraining

loop

+

earningpressure

+

+ ...not a

lifetime

trade

thriftsaving

+

+

<enforcement

coverage>

fine andbribe paid

++

<fine and bribe

paid>

-

experience-

SD Submodels (Modules)

Stock and Flow model

AdditionalOfficers'Support

draftingofficers

initialworkforce excess

supportremoval

TargetPerception

time forremoval

change intarget

time toreducetarget

EnforcementWorkforce

net hiretotal legal

enforcement

time toraisetarget

time to draftmore hands

initial target<public perception

about risk in operation>

<publicperception

about risk inoperation>

<public perception

about risk in operation>

<initialattention>

rest

<equivalence of number ofofficers motivated for

overtime service>

enforcementsize.

enforcement

coverage.

<Attention To

Mode>

Enforcement sub-model

Baseline Results Example

Result

0.6 .

2,000 .

40 .

0.3 .

1,000 .

20 .

0 .

0 .

0 .3

3

3

3

3 3 33

33

33

33

2

2

2

2

22

22 2 2

22

2 2

1

1

1

1 1 1 1 1 1 1 1 1 1 1 1

0 130 260 390 520 650 780 910 1040 1170 1300

Time (Week)

Tendency to Violate : .test_baseline .1 1 1 1 1 1 1 1 1

total violations : .test_baseline .2 2 2 2 2 2 2 2 2

enforcement coverage : .test_baseline .3 3 3 3 3 3 3 3

Baseline result

interpretation:

• Tendency to violate

• Total violations

• Enforcement coverage

• Total drivers

• Driver income

6,000 .

2,000 .

3,000 .

1,000 .

0 .

0 .

2

2 2 2 2 2 2 2 2 2 2 2 2 2

1

1

1

1

1

11

11

11

11

11

0 130 260 390 520 650 780 910 1040 1170 1300

Time (Week)

total drivers : .test_baseline .1 1 1 1 1 1 1 1 1 1

drivers' income : .test_baseline .2 2 2 2 2 2 2 2 2

Result

0.6 .

2,000 .

40 .

0.3 .

1,000 .

20 .

0 .

0 .

0 .3

3

3

3

3 3 33

3

3

3

3

3

3

2

2

2

2

22

22 2 2 2

22

2

1

1

1

1 1 1 1 1 1 1 1 1 1 1 1

0 130 260 390 520 650 780 910 1040 1170 1300

Time (Week)

Tendency to Violate : .test_double_recruitment .1 1 1 1 1 1 1 1

total violations : .test_double_recruitment .2 2 2 2 2 2 2 2 2

enforcement coverage : .test_double_recruitment .3 3 3 3 3 3 3

Double recruitment

rate:

• Insignificant changes to

tendency to violate

• Insignificant changes to

total violations

• Significant additional

enforcement coverage

Graph of doubled recruitment rate scenario

Responsiveness Testing


Remove expensive

ownership options:

• Minor changes to tendency to

violate

• Substantial reduction in total

violations

• Significant reduction in


Result

0.6 .

2,000 .

40 .

0.3 .

1,000 .

20 .

0 .

0 .

0 .3

3

3

3

3 3 33 3

3 33

33

2

2

2

2

22

22 2

2

22 2 2

1

1

1

1 1 1 1 1 1 1 1 1 1 1 1

0 130 260 390 520 650 780 910 1040 1170 1300

Time (Week)

Tendency to Violate : .test_ownership .1 1 1 1 1 1 1 1 1

total violations : .test_ownership .2 2 2 2 2 2 2 2 2

enforcement coverage : .test_ownership .3 3 3 3 3 3 3 3

Graph of removal of expensive ownership

options scenario

Scenario 3

Raise prosecution rate:

• Substantial changes to

tendency to violate

• Less than expected reduction

in total violations



Result

0.6 .

2,000 .

40 .

0.3 .

1,000 .

20 .

0 .

0 .

0 .3

3

3

3

3 3 33 3

33

33

3

2

2

2

2

22

22 2

2 2 2 2 2

1

1

1

1 1 1 1 1 1

1

1 1 1 1 1

0 130 260 390 520 650 780 910 1040 1170 1300

Time (Week)

Tendency to Violate : .test_raise_prosecution .1 1 1 1 1 1 1

total violations : .test_raise_prosecution .2 2 2 2 2 2 2 2

enforcement coverage : .test_raise_prosecution .3 3 3 3 3 3 3

Graph of increase in prosecution rate

scenario


Combination of increased

prosecution and removal

of expensive ownership

options:

• Substantial reduction in

tendency to violate

• Substantial reduction in total

violations



Result

0.6 .

2,000 .

40 .

0.3 .

1,000 .

20 .

0 .

0 .

0 .3

3

3

3

3 3 33 3

3 3 33

3

2

2

2

2

22

22 2

2

22 2 2

1

1

1

1 1 1 1 1 1

1

11 1 1 1

0 130 260 390 520 650 780 910 1040 1170 1300

Time (Week)

Tendency to Violate : ..test_ab .1 1 1 1 1 1 1 1 1 1

total violations : ..test_ab .2 2 2 2 2 2 2 2 2 2

enforcement coverage : ..test_ab .3 3 3 3 3 3 3 3 3

Graph of combination of increased

prosecution and removal of expensive

ownership options


Extracts from findings

SDM can be used in modelling the system

The entry method into the trade contributes to the system problem substantially

Improving sanction is not the same thing as increasing enforcement capacity

A leverage is achieved by a combination of measures

evaluation of transport safety policies in commercial motorcycle operation in nigeria

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