Safer City Streets – Global Benchmarking for Urban Road Safety Alexandre Santacreu, Pedro Homem de Gouveia

Segurança da Circulação em Meio Urbano – LNEC, 29.11.2018

Intergovernmental Organisation

59 member countries

Think Tank

Policy analysis Research Statistics

Annual Summit

Forum for Ministers, industry

“The Davos of Transport"

3

IRTAD LAC

IRTAD

International Traffic Safety Data and Analysis Group

2018

ITF Roundtable on Cycling Safety

33 Experts

16 Countries

4

5

2018

ITF Roundtable on Cycling Safety

33 Experts

16 Countries

Safer City Streets the global traffic safety network for liveable cities

Global

database

Network of experts

Safer City Streets the global traffic safety network for liveable cities

49 cities

8

20-21 April 2017

1st meeting

in Paris

28 cities

20 other

organisations

9

Ministerial Summit 23-25 May 2018 Leipzig

transport safety & security

Montreal

New York City

Guadalajara Mexico City

Bogota

Buenos Aires Melbourne

Auckland

Edmonton

Vancouver Calgary

Dublin

Barcelona Rome

Belgrade

Stockholm

Riga

Berlin

London

Paris

Copenhagen

Warsaw

The Hague

Brussels

Madrid

Milan

Zurich

Lisbon

Fortaleza

31 cities

Safer City Streets database

One publication for seven key questions 1. Are city streets dangerous?

2. Can we measure urban road safety

performance?

3. Can we monitor performance?

4. Which factors are driving road safety

performance?

5. Are cities confronted with specifically urban

road safety challenges?

6. What is the impact of mode shift on public

health?

7. Which recommendations can we make?

11

12

Top level results

1 2

3

Fatalities per 100 000 population, 2011-2015

14

0.5

1

2

4

8

16

32

Rate per 100 000 resident population

loga

rith

mic

sca

le

0.5

1

2

4

8

16

32

Rate per 100 000 resident population Rate per 100 000 daytime population Whole country

loga

rith

mic

sca

le

0.5

1

2

4

8

16

32

Rate per 100 000 resident population Rate per 100 000 daytime population

loga

rith

mic

sca

le

0.5

1

2

4

8

16

32

Rate per 100 000 resident population Rate per 100 000 daytime population Whole country

loga

rith

mic

sca

le

0.5

1

2

4

8

16

32

Rate per 100 000 resident population Rate per 100 000 daytime population Whole country

loga

rith

mic

sca

le

0.5

1

2

4

8

16

32

Rate per 100 000 resident population Rate per 100 000 daytime population Whole country

loga

rith

mic

sca

le

15

Road fatalities, changes from 2006-10 to 2011-15

-49

%

-47

%

-36

%

-30

%

-29

%

-26

%

-26

%

-25

%

-21

%

-21

%

-20

%

-19

%

-19

%

-18

%

-18

%

-18

%

-16

%

-15

%

-12

%

-7%

-7%

0%

-50%

-40%

-30%

-20%

-10%

0%

City

-49

%

-47

%

-36

%

-30

%

-29

%

-26

%

-26

%

-25

%

-21

%

-21

%

-20

%

-19

%

-19

%

-18

%

-18

%

-18

%

-16

%

-15

%

-12

%

-7%

-7%

0%

-50%

-40%

-30%

-20%

-10%

0%City

Whole country

-49

%

-47

%

-36

%

-30

%

-29

%

-26

%

-26

%

-25

%

-21

%

-21

%

-20

%

-19

%

-19

%

-18

%

-18

%

-18

%

-16

%

-15

%

-12

%

-7%

-7%

0%

-50%

-40%

-30%

-20%

-10%

0%City

Whole country

16

Analysis by mode

Modal shares of road fatalities, by city and by population density group, 2013-2015

17

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

AucklandCalgary

MelbourneEdmonton

BrusselsLisbon

GuadalajaraMontreal

RomeMexico City

ZürichBuenos Aires

VancouverBerlin

New York CityRiga

WarsawFortaleza

Greater LondonMilan

The HagueCopenhagen

Paris areaStockholm

Bogotá D.C.Dublin City

MadridBarcelona

Inner LondonParis City

pedestrian bicycle powered-2-wheeler other road users

Are cities confronted with specifically urban road safety challenges?

19

• Vulnerable Road Users (VRUs) represent 8 out of 10 urban

traffic fatalities – but 4 out of 10 at a national level,

typically.

• Consequently, specific topics take precedence: traffic

calming, speed limits, direct vision lorries, etc.

20

9 10

12 13 13 14 1517

35

57

34

6

89 10 10 11

15 1517

2426

3032

1922

2831

4551

67 71 73

97

161fa

talit

ies

pe

r b

illio

n k

ilom

etre

tra

velle

d

9 10

12 13 13 14 1517

35

57

34

6

89 10 10 11

15 1517

2426

3032

1922

2831

4551

67 71 73

97

161fa

talit

ies

pe

r b

illio

n k

ilom

etre

tra

velle

d

9 10

12 13 13 14 1517

35

57

34

6

89 10 10 11

15 1517

2426

3032

1922

2831

4551

67 71 73

97

161fa

talit

ies

pe

r b

illio

n k

ilom

etre

tra

velle

d

9 10

12 13 13 14 1517

35

57

34

6

89 10 10 11

15 1517

2426

3032

1922

2831

4551

67 71 73

97

161

41

10

41

16

23 23

911

8

28 28

21 21

49

fata

litie

s p

er

bill

ion

kilo

met

re t

rave

lled

City Whole Country

9 10

12 13 13 14 1517

35

57

34

6

89 10 10 11

15 1517

2426

3032

1922

2831

4551

67 71 73

97

161

41

10

41

16

23 23

911

8

28 28

21 21

49

fata

litie

s p

er

bill

ion

kilo

met

re t

rave

lled

City Whole Country

Risk of fatality per unit distance travelled, 2011-2015

Are city streets dangerous?

21

• Living and travelling in cities appear to be safer, regardless

of the choice of indicator, in comparison to rural areas

• Yet most urban populations express a fear of cycling and a

fear of letting their children walk to school

• In this sense, we recommend creating an environment

where people are and feel safe

Fatalities per billion passenger-kilometre

2011-2015 average

ITF Safer City Streets database

Median

/5 cities: Auckland,

Barcelona, Berlin, Greater London,

Paris Area P2W riders have a fatality risk

4x that of

pedal cyclists

What is the impact of mode shift on public health?

23

• The answer requires the collection of mobility data and the

analysis of crash matrices

• Provisional results highlight the risk of using P2W (not only

to riders themselves but also to third parties, namely

pedestrians)

• The true answer requires the consideration of physical

activity benefits from active travel

28

Gender and age

29

0.8 1.1

1.4 1.7 1.7

1.8 2.1

2.3 2.4

2.5 2.5

2.6 2.7 2.7 2.7

3.0 3.0

3.1 3.2 3.2

3.3 3.4

3.5 3.7

3.9 4.0

4.8

VancouverLisbonZürich

StockholmMontreal

CopenhagenInner London

BerlinNew York City

Paris CityAucklandWarsawBrussels

MelbourneGreater London

The HagueMexico City

RigaBelgrade District

Buenos AiresBarcelona

CalgaryParis area

MilanRome

GuadalajaraFortaleza

Ratio between male and female fatalities per unit population, 2011-2015

31

Casualty rate per billion kilometres travelled by age and by mode

Source: Transport for London

http://content.tfl.gov.uk/safe-

streets-for-london.pdf

Can we monitor performance?

32

• Year-on-year changes in fatalities rarely are statistically

significant

Relying on fatality data alone makes it impossible, in most

cities, to monitor safety year-on-year

• Changes in casualties in some user groups often reflect the

changes in the size of this group

Without mobility data, we can’t monitor road user risk

33

Beyond fatality counts

34

4329

2824

2321

191919

1717

1610

877

66

32

BerlinMelbourne

ZürichCopenhagen

Paris areaInner London

CalgaryVancouverStockholmEdmonton

Greater LondonParis CityAucklandMontreal

LisbonBrussels

BarcelonaBelgrade District

RigaWarsaw

16.28.3

4.0

StockholmMelbourne

Barcelona

Ratio between serious injuries and fatalities, 2011-2015

Ratio between MAIS3+ injuries and fatalities, 2011-2015

Which factors are driving road safety performance in cities?

35

• Population density is associated with safety. It is likely to be

a confounding factor which also drives high PT mode share,

lower vehicle speeds and shorter trip distances.

• Where more people cycle, a better road safety performance

is observed. Some causal links are likely to work both ways.

Which recommendations can we make?

36

• Set ambitious targets on fatal and serious injuries

• Focus on VRUs and develop meaningful VRU safety

indicators

• Collect robust and comparable serious injury data

• Consider safety as a key to mode shift and vice versa

37

Source: Transport for London

2018 Vision Zero Action Plan

Safe streets unlock alternative transport modes

Obrigado. Pedro Homem de Gouveia pedro.gouveia@cm-lisboa.pt www.itf-oecd.org