Safer City Streets – Global Benchmarking for Urban …Safer City Streets – Global Benchmarking...
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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"
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IRTAD LAC
IRTAD
International Traffic Safety Data and Analysis Group
2018
ITF Roundtable on Cycling Safety
33 Experts
16 Countries
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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
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20-21 April 2017
1st meeting
in Paris
28 cities
20 other
organisations
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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?
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12
Top level results
1 2
3
Fatalities per 100 000 population, 2011-2015
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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
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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
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Analysis by mode
Modal shares of road fatalities, by city and by population density group, 2013-2015
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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?
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• 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.
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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?
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• 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?
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• 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
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Gender and age
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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
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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?
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• 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
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Beyond fatality counts
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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?
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• 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?
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• 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
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Source: Transport for London
2018 Vision Zero Action Plan
Safe streets unlock alternative transport modes
Obrigado. Pedro Homem de Gouveia [email protected] www.itf-oecd.org