2024 RS_1 - Basic Concepts_Updated F.pdf

Module 1: Basic Concepts of
Road Safety
www.ctl.uniroma1.it
info@ctl.uniroma1.it
Road Safety
A.A. 2023-2024
Module 1
Dr. Stephen Kome

Mod. 1: Basic Concepts of Road Safety
• 1.1 – Crashes and indicators
• 1.2 – The Magnitude of the Problem
• 1.3 – Main factors affecting probability of
accidents and injuries
• 1.4 – The Pillars of road safety
14/12/2024
Mod. 1 Slide 2

1.1 – CRASHES AND
INDICATORS
Basic Concept of Road Safety
14/12/2024
Mod. 1 Slide 3

What is a road accident?
14/12/2024
Mod. 1 Slide 4

What is a road Crash?
14/12/2024
Mod. 1 Slide 5
➢ Road crashes, also known as traffic collisions or
motor vehicle accidents, are incidents that occur
on public roadways involving at least one
vehicle in motion.
➢ These crashes can result in property damage,
injuries, or fatalities.
➢ Road crashes can involve various types of
vehicles such as cars, trucks, motorcycles,
bicycles, and pedestrian

Random Events
2-6
14/12/2024
Mod. 1 Slide 6

Rare Events
Relative Proportion of Accident Events
HSM, 2010
14/12/2024
Mod. 1 Slide 7

What is Safety?
Subjective safety
• Perception
• Values vary among
observers
Objective safety
• Quantifiable
• Independent of the
observer
14/12/2024
Mod. 1 Pagina 8

Changes in Objective and Subjective
Safety
HSM, 2010
14/12/2024
Mod. 1 Slide 9

What is an indicator?
14/12/2024 Slide 10
“An indicator is a variable, or a combination of variables,
selected to represent a certain wider issue or
characteristic of interest” (Gudmundsson et al.,2016)

Road accidents indicators
• Absolute indicators are measures of:
– Number of Crashes during the observation period
– Number of fatalities during the observation period
– Number of injuries during the observation period
• Relative indicators are measures of:
– Crash risk
– Crash severity
14/12/2024
Mod. 1 Slide 11

Example: road accidents, injuries and
fatalities in Italy in 2021
• In Italy, in 2021, 151.875 injury crashes
occurred, causing 2.875 fatalities and
204.728 injuries
• 8 fatalities every day - 1 fatality every 3 hours
• The estimated social cost is over 24
billions Euro, 1.6% of GDP (2013)
Let’s update these figures together!

Example: evolution in Italy, 2001-2016
In Italy from 2001 there has been a strong decrease of
the number of road fatalities (-53%) and injuries (-33%)
7096
3283
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
400,000
0
1,000
2,000
3,000
4,000
5,000
6,000
7,000
8,000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
Nr
Injuries
Nr
Fatalities
Road Fatalities Road Injuries

Example: comparing different time
periods in the day
14/12/2024
Mod. 1 Slide 15
Number of fatalities by hour of day in the EU, 2015
(CARE - 2017)

Relative indicators
How we compare the safety level e.g.
in different areas?

Accident Risk indicators
• Are used to make comparisons between
different elements of the network or between
different areas/regions
• Are obtained by dividing the frequency of
accidents (A), fatalities (F) and injuries (I) by
a measure of exposure to risk (E)
14/12/2024
Mod. 1 Slide 17

Measures of exposure to risk
• For networks (or areas):
– Population
– Vehicles
– Passengers * km
• For elements (i.e. road sections and
intersections) of the road network:
– Traffic flows
14/12/2024
Mod. 1 Slide 18

Types of Accident Risk Indicators
• Accidents Rate (AR = A / E)
• Injury Rate (IR = I / E)
• Fatality Rate (FR = F / E)
14/12/2024
Mod. 1 Slide 19

Accident Risk Indicators for
areas/regions
Relates the number of accidents A and the
number of Inhabitants, Vehicles and
Passengers * kms
• AR = A / Population
• AR = A / Vehicles
• AR = A /Passengers * kms
14/12/2024
Mod. 1 Slide 20

Accident Risk Indicators for Road
Sections
Relates the number of accidents A the length
L of the road section and the annual average
daily traffic flow, AADT:
AR = A / (L x AADT)
14/12/2024
Mod. 1 Slide 21

Accident Risk Indicators for Road
Intersections
Relates the number of road accidents A
divided by the total entering annual average
daily traffic flow AADT:
AR = A / AADT
14/12/2024
Mod. 1 Slide 22

Accident Severity indicators
• The Injury Index (I.I.) expresses the average
number of injuries (I) in a given period of time
every 100 accidents (A)
I.I. = (I / A) x100
• The Mortality Index (M.I.) expresses the
average number of fatalities (F) in a given
period of time every 100 accidents (A)
M.I. = (F / A) x100
14/12/2024
Mod. 1 Slide 23

1.2 – MAGNITUDE OF THE
PROBLEM
14/12/2024
Mod. 1 Slide 24

Summary
• World level
• European level
• National level
Mod. 1 Pagina 26

How serious is the problem?
1.19 millions road traffic deaths per year
99,167 road traffic deaths per month
3,306 road traffic deaths per day
138 road traffic deaths per hour
One road traffic death every 25 seconds

Leading causes of death in 2016 vs 2019
Mod. 1 Slide 30
(WHO, 2018)
(WHO, 2023)

10 Leading Causes of Death by Age Group,
United States─ 2020
Mod. 1 Slide 31
Data Source: National Vital Statistics System, National Center for Health Statistics, CDC., 2020

Evolution at world level1
Mod. 1 Slide 32
WHO estimated number of road traffic fatalities, 2000–2021
(WHO, 2023)

Evolution at world level2
Mod. 1 Slide 33
Number of motor vehicles and rate of road traffic death per 100,000 vehicles: 2000-2016
(WHO, 2018)
Number and rate of road traffic death per 100,000 population: 2000-2016
(WHO, 2018)

WHO: Fatalities per 100.000 inhabitants in 2016
Mod. 1 Slide 34
(WHO, 2018)

Evolution in WHO Regions1
Number of road traffic fatalities by WHO region 2016
(WHO, 2018)

Number of road traffic fatalities by WHO region and country-income level, 2021
(WHO, 2023)
Mod. 1 Slide 36

Road traffic fatality rate per 100 000 population by WHO region and country income level, 2021
(WHO, 2023)
Mod. 1 Slide 37

Percentage change in estimated road fatalities, by WHO region, 2010–2021
(WHO, 2023)
Mod. 1 Slide 38

WHO: Population, fatalities, vehicle fleet, and
paved roads by country income status (World)
(WHO, 2023)

WHO: Trends in road fatalities in low, middle
and high income countries
(WHO, 2018)
Number of countries increasing or decreasing fatalities in 2013-2016

Proportion of road traffic deaths by age
range and country income status
(WHO - 2015)
Mod. 1 Slide 41

Fatalities by type of user
(WHO, 2023)

Key Facts in Africa
14/12/2024
Mod. 1 Slide 44

Estimated road traffic fatalities per 100
pop, 2021
Mod. 1 Slide 45

Change in fatality rate by WHO region
(2010 t0 2021)
24/02/2021
Mod. 1 Slide 46

Change in road user death type by WHO
region (2010 t0 2021)
Mod. 1 Slide 47
(ETSC -2023)

African Countries with laws that meet best
practice
Mod. 1 Slide 48

14/12/2024
Mod. 1 Slide 50
Magnitude (See WHO App)
Android
iOS

1.2 - MAIN FACTORS
AFFECTING PROBABILITY OF
CRASHES AND INJURIES
14/12/2024
Mod. 1 Slide 51

Summary
• Some definitions
• Factors affecting exposure
• Factors affecting accident rate
• Factors affecting injury severity
14/12/2024
Mod. 1 Slide 52

Some definitions
• Exposure
– The volume of activity generating risk; the amount
of traffic and travel
• Probability of accident
– Accident rate (as an approximation) =
• Consequence/injury severity
– The extent of damage; the severity of personal
injuries; the number of fatalities
• Injury risk
– The probability of being injured in an accident
Number of accidents
Exposure

Understanding risk factors
• What is a risk factor?
– a variable or feature of the road transport system
that is associated with a higher chance to get
involved in a crash or a higher chance to get
injured in a road crash (SafetyCube, 2017)
• A measure of the strenght of the association
between exposure to a risk factor and an
adverse outcome is Relative Risk

Relative Risk
• Relative risk compares the probability of an
adverse outcome in an exposure group to its
probability in an unexposed group
• It can be expressed as the ratio of the
probability of the adverse outcome in the
exposure group to its probability in the
unexposed group
• It helps us in understanding if the exposure to
a risk factor increases, decreases or does not
affect the probability of e.g. dyeing

Relative Risk - Example
• We collect data and find that:
– 40% of drivers involved in an accident and not
fastening their seatbelt die after the accident
– 5% of drivers involved in an accident but fastening
their seatbelt die
• Relative risk = 0.40 / 0.05 = 8
• Drivers not using the seatbelt are 8 times
more likely to die in case of accident than
drivers using their seatbelt

Relative Risk - Exercise
Fatally
injured
Not
fatally
injured Total
Pedestrians hit by cars
traveling at 40 miles per hour 40 10 50
Pedestrians hit by cars
traveling at 20 miles per hour 5 45 50
Total 45 55 100
• A study found that the relative risk of a
pedestrian being killed by a car increases
dramatically with speed.
Exposed
Not Exposed

Relative Risk - Exercise
• Risk of Death for Pedestrians Hit by Cars
Traveling at 40 mph = 40 / (40+10) = 0.8
• (Risk of Death for Pedestrians Hit by Cars
Traveling at 20 mph) = 5 / (45+5) = 0.1
• Relative Risk = 0.8 / 0.1 = 8

The main factors affecting road safety
Exposure
Type/Mode Mixture
Amount
Accident rate
Injury severity
Vehicles Road Users
Infrastructure
Vehicles Road Users
Infrastructure
14/12/2024
Mod. 1 Slide 59

Exposure
Type/Mode Mixture
Amount
Accident rate
Injury severity
Vehicles Road Users
Infrastructure
Vehicles Road Users
Infrastructure
14/12/2024
Mod. 1 Slide 60

Percentage of variation in accidents counts by county and month in
Norway explained by various variables. Source: Fridstrøm et al 1993, 1995
8.1
5.2
4.8
0.3
1.5
7.2
6.1
66.8
0 10 20 30 40 50 60 70 80
Random variation
Unexplained systematic
variation
Rules for accident reporting
Long term trend
Month
County
Weather and daylight
Traffic volume
Explanatory
factor
Percentage of explained variation
14/12/2024
Mod. 1 Slide 61

The amount of travel
• The unit of measurement is generally the
volume of traffic (number of vehicles using a
road unit time)
• Generally, it takes account of motor vehicles
(for pedestrians and cyclists, there are no
reliable estimates on the movement)
14/12/2024
Mod. 1 Slide 62

Mathematical function
• The relationship between accidents and traffic
volume is:
• where:
– N is the number of accidents
– Q is the volume of traffic
–  is a constant
– b is the elasticity (% change in N, if Q varies 1%)
b
Q
N 
=
14/12/2024
Mod. 1 Slide 63

Typical relationships between traffic volume and the expected number of
accidents
0
5
10
15
20
25
30
0 5 10 15 20 25
Traffic volume (arbitrary values)
Expected
number
of
accidents
(arbitrary
values)
Property damage only =
Traffic 1.1
Injury accidents =
Traffic
0.9
Fatal accidents =
Traffic
0.7
14/12/2024
Mod. 1 Slide 64

Exposure
Type/Mode Mixture
Amount
Accident rate
Injury severity
Vehicles Road Users
Infrastructure
Vehicles Road Users
Infrastructure
14/12/2024
Mod. 1 Slide 65

Choosing mode of transport
Relative
rate
of
injury
(self
=
1)
Relative injury risk (Dk, G, UK, Nl, N, Sw)
Elvik, 2002-2008
14/12/2024
Mod. 1 Slide 66

Exposure
Type/Mode Mixture
Amount
Accident rate
Injury severity
Vehicles Road Users
Infrastructure
Vehicles Road Users
Infrastructure
14/12/2024
Mod. 1 Slide 67

The mix of road users
• Very often (especially in urban areas and at
intersections) different categories of road
users use the same area for travel
• The interaction determines danger especially
for vulnerable road users (e.g. pedestrians
and cyclists)
• The accident rates depend on the proportions
between the groups
14/12/2024
Mod. 1 Slide 68

An example
• For pedestrians and cyclists, we have (Brude
and Larsson, 1993):
• where:
– N1,2 is the number of accidents involving groups 1
and 2
– Qi is the volume of traffic of group i
–  is a scale constant
– b and c are coefficients to be estimated
c
b
Q
Q
N 2
1
2
,
1 

=
14/12/2024
Mod. 1 Slide 69

Numerical values
• where:
– MV is the volume of motorvehicles
– PED is the volume of pedestrians
– CYC is the volume of cyclists
65
,
0
52
,
0
acc
.
72
,
0
5
,
0
acc.
ped.
0000180
,
0
0000734
,
0
CYC
MV
N
PED
MV
N
cyc 

=


=
14/12/2024
Mod. 1 Slide 70

Exercise
• If PED increases from 500 to 1,000 and MV
increases from 5,000 to 10,000 (total traffic is
doubled) → what happen to the number of
pedestrian accidents
• If PED increases from 100 to 1,000, what
happens to the risk for pedestrian (number of
pedestrian accidents per pedestrian exposed)?
• If MV increases from 2,000 to 10,000, what
happens to the risk of a MV hitting a
pedestrian?
14/12/2024
Mod. 1 Slide 71

Comment
• The relationship between accidents and
exposure is, in this case, strongly non linear
• It shows that:
– each category of users is safer (i.e., the accident
rate decreases) if there are more users from the
same group → «Safety in numbers»
– The total number of accidents increases more
than proportionally with interacting traffic volumes
14/12/2024
Mod. 1 Slide 72

Examples
• If PED increases from 500 to 1,000 and MV
increases from 5,000 to 10,000 (total traffic is
doubled) → the number of pedestrian
accidents increases by a factor 2.33
• If PED increases from 100 to 1,000, the risk
for pedestrian (number of pedestrian accidents
per pedestrian exposed) drops by 50%
• If MV increases from 2,000 to 10,000, the risk
of a MV hitting a pedestrian is reduced by
more than 50%
14/12/2024
Mod. 1 Slide 73

Exposure
Type/Mode Mixture
Amount
Accident rate
Injury severity
Vehicles Road Users
Infrastructure
Vehicles Road Users
Infrastructure
14/12/2024
Mod. 1 Slide 74

The type of infrastructure
Area Road type DK FN UK N NL S USA
Rural Motorway 1.0 1.0 1.0 1.0 1.0 1.0 1.0
Main 4.0 2.9 2.9 2.3 1.3 1.3 2.7
Collector 4.7 3.2 - 3.5 3.6 2.3 4.6
Access 5.7 6.1 5.1 5.5 7.2 1.3 8.7
Urban Main 11.0 7.9 7.2 5.2 - 2.1 5.7
Collector 9.1 6.8 - 6.5 18.3 4.0 5.6
Access 10.0 7.3 7.1 12.1 9.5 3.1 8.8
All All 4.6 3.7 4.4 4.0 - 2.2 4.6
Relative risk of injury accidents (Motorway = 1)
Elvik,1991-2008
14/12/2024
Mod. 1 Slide 75

Design features
• Many design features affect safety level:
– Cross section (e.g. number and width of lanes)
– Vertical and horizontal alignment
– Size and regulation of intersections
– Type of parking
– Road surface
– Pedestrian crossings
– ........
14/12/2024
Mod. 1 Slide 76

Width of the road
• The effect of road width depends on whether
you are in an urban or a non-urban (rural)
area:
– in rural area width plays in favor of safety (the
wider space allows for more safety at high speeds)
– in urban it is the opposite (the greater width makes
it difficult crossings the road)
14/12/2024
Mod. 1 Slide 77

Road Intersections
• The accident rate increases if ...
– ... an intersection has more legs
– ... a higher proportion of traffic enters the
intersection from the minor road
• Roundabouts reduce the severity of accidents
14/12/2024
Mod. 1 Slide 78

Curves
The accident rate depends on the radius and the number of
curves per km
Accident rate, based on Norwegian data
14/12/2024
Mod. 1 Slide 79

Effect of access point density on injury accident rate
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
0 10 20 30 40 50 60 70
Access points per kilometre
Accident
rate
Access points density
14/12/2024
Mod. 1 Slide 80

The environmental conditions
Factor Value Relative
accident rate
Light Daylight 1.0
Dark - vehicles 1.0
Dark - pedestrians 2.1
Dark - cyclists 1.6
Surface Dry 1.0
Wet 1.3
Wet - snow 1.5
Snow or ice covered road 2.5
Relative risk of injury accidents in different
environmental conditions Elvik,1976-2009
14/12/2024
Mod. 1 Slide 81

Exposure
Type/Mode Mixture
Amount
Accident rate
Injury severity
Vehicles Road Users
Infrastructure
Vehicles Road Users
Infrastructure
14/12/2024
Mod. 1 Slide 82

The vehicle
• Many vehicle related factors affect the
accident rate:
– Braking capacity (eg ABS, Electronic Brake
Control)
– Stability (eg, tires, suspension, Electronic Stability
Control and Traction)
– Ergonomics (driver's position, position of
information and control devices)
14/12/2024
Mod. 1 Slide 83

Other factors
• Type of information (e.g. tire pressure,
warning about outside temperature)
• Advanced Driver Assistance Systems:
enhance the driving skills, intervene to take
control of the vehicle, monitor the physical
and psychological condition of the driver (e.g.
Collision Avoidance, Cruise Control, Vision
enhancement, Driver Monitoring, Lane
Control)
• Daytime running lights
14/12/2024
Mod. 1 Slide 84

Some considerations
• In the case of the vehicle, it is more difficult to
estimate the weight of each risk factor
• Effect of "risk compensation": It is
demonstrated that road users are prone to
adapt their behaviour to risk factors and road
safety measures to a greater or lesser extent
(e.g., I have the ABS -> I drive faster and / or
brake later)
14/12/2024
Mod. 1 Slide 85

Exposure
Type/Mode Mixture
Amount
Accident rate
Injury severity
Vehicles Road Users
Infrastructure
Vehicles Road Users
Infrastructure
14/12/2024
Mod. 1 Slide 86

Relationship between annual driving distance and accident rate in three
studies
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
0.0 5000.0 10000.0 15000.0 20000.0 25000.0 30000.0
Annual driving distance (km)
Accidents
per
million
kilometres
Middle-aged
Older (65+)
Middle-aged
Older (65+)
Middle-aged
Older (65+)
Hakamies-Blomqvist
Langford
Alvarez
Distance driven
14/12/2024
Mod. 1 Slide 87

Some considerations
• Risk for older drivers > middle-aged drivers
• Limitations of studies
– Limited samples and self-reported crash
involvement
• The low mileage bias
– Older drivers drive less distance annually
compared to younger drivers
– Most of their driving occurs on high-risk congested
streets
• Frialty bias
– Higher likelihood to be in crash database
14/12/2024
Mod. 1 Slide 88

Fatal Crash Involvement by Driver
Age
14/12/2024
Mod. 1 Slide 89

Age and gender of car drivers
Elvik,1996-2008
14/12/2024
Mod. 1 Slide 90

Some considerations
• The risk for young drivers and elderly is
higher than other age groups
• Up to the age of 30 years accident rate is
higher for men than women, the opposite
from the age of 30:
– women drive less than men
– women drive smaller cars (increases the risk of
injury)
– women drive more in towns and cities
– .... other?
14/12/2024
Mod. 1 Slide 91

Health conditions
Effects of medical conditions on accident rate
3.71
2.06 2.01 1.96
1.84
1.09
1.19 1.17
0.00
0.50
1.00
1.50
2.00
2.50
3.00
3.50
4.00
Sleep apnoea Alzheimer's
disease
Severe mental
illness
Any drug
presumably
abused
Epilepsy Any visual
impairment
Any hearing
impairment
Any locomotor
disability
Relative
accident
rate
(unimpaired
drivers
=
1.0)
14/12/2024
Mod. 1 Slide 92

Alcohol Elvik,1985-2005
14/12/2024
Mod. 1 Slide 93

Some considerations
• In some studies seems to emerge a lower risk
to low concentrations of alcohol (not
confirmed)
• The ordinate scale is logarithmic: at
concentrations of 2 g/l the risk of accident
increases by a factor of 100!
• The effect is more severe on fatalities and
injuries
14/12/2024
Mod. 1 Slide 94

Alcohol & drug
Effects of acute impairments on accident rate
1 1.4
29
1.4
6.7
12
60
153
0
20
40
60
80
100
120
140
160
180
No drug Any single
drug
Combinations
of drugs
BAC 0.2-0.5
g/l
BAC 0.5-0.8
g/l
BAC 0.8-1.3
g/l
BAC > 1.3 g/l BAC > 0.8 g/l
and drugs
Relative
accident
rate
14/12/2024
Mod. 1 Slide 95

Speed
Severe damage
All accidents
Fatal
Elvik et al, 2004
Effect of the average speed (V0 = 80 km / h)
Change
accidents
Change average speed km / h
14/12/2024
Mod. 1 Slide 96

Exposure
Type/Mode Mixture
Amount
Accident rate
Injury severity
Vehicles Road Users
Infrastructure
Vehicles Road Users
Infrastructure
14/12/2024
Mod. 1 Slide 97

Infrastructure role
• The infrastructure does not affect always the
the consequences of a road accident
• The most important element is crash barrier
• Peculiar features of crash barriers are: shape,
size, material, anchor
14/12/2024
Mod. 1 Slide 98

Exposure
Type/Mode Mixture
Amount
Accident rate
Injury severity
Vehicles Road Users
Infrastructure
Vehicles Road Users
Infrastructure
14/12/2024
Mod. 1 Slide 99

Relationship between typical mass of vehicle and probability of driver
(pedestrian, cyclist) injury in injury accidents
0,0
10,0
20,0
30,0
40,0
50,0
60,0
70,0
80,0
90,0
100,0
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
Typical mass (kilograms)
Probability
of
getting
injured
Truck
Bus
Passenger car
Taxi
Station wagon
Van
Small motorbike
Moped
Large motorbike
Bicycle
Pedestrian
The type of vehicle
Effect of the type and mass of the vehicle
Norvegia
14/12/2024
Mod. 1 Slide 100

Risk of own injury, risk of injuring others and total risk of injury in two car
crashes as a function of mass of car
1,00
1,00
1,00
0,55
0,60
0,65
0,70
0,75
0,80
0,85
1,75
1,65
1,60
1,55
1,50
1,40
1,25
0,93
1,00
0,95
0,97
1,00
1,05
1,00
0,00
0,20
0,40
0,60
0,80
1,00
1,20
1,40
1,60
1,80
2,00
2,20
<850 900 1000 1100 1200 1300 1400 >1500
Mass in kilograms
Relative
injury
risk
to
drivers.
Smallest
cars
=
1.00
Own
Others
Total
The mass
Effect of vehicle mass on themselves and on others
14/12/2024
Mod. 1 Slide 101

1.02 1.02 1.03
0.92
1.01 0.98
0.84
0.78
1.06
0.85
0.70
0.33
0.00
0.20
0.40
0.60
0.80
1.00
1.20
0 1 2 3 4 5 6
Relative
injury
risk
(set
to
1.00
for
cars
without
EuroNCAP
score)
Number of stars (5 = maximum)
Relationshipbetween EuroNCAPstarsand injury risk (Kullgren et al 2010)
All injuries
Fatal and serious injuries
Fatal injuries
Vehicle crashworthiness
14/12/2024
Mod. 1 Slide 102

The pedestrian
Effect of impact speed on the probability of death
of pedestrian Pasanen, 1991
14/12/2024
Mod. 1 Slide 103

The pedestrian
Effect of impact speed on the probability of
death of pedestrian Rosen et al, 2011
14/12/2024
Mod. 1 Slide 104

Other protective measures
• The helmet reduces the risk of injury by 25%
• The protective suit 30% (helmet + suit = 50%)
• Seat belts reduce the risk of injury by 20-
30%, risk of death by 40-50%
• The air bag reduces the risk of death by
12/14% (with / without belt)
14/12/2024
Mod. 1 Slide 105

2024 RS_1 - Basic Concepts_Updated F.pdf

More Related Content

Similar to 2024 RS_1 - Basic Concepts_Updated F.pdf (20)

Recently uploaded (20)

2024 RS_1 - Basic Concepts_Updated F.pdf