17

1.2. ricardo marqués

Embed Size (px)

Citation preview

Page 1: 1.2. ricardo marqués
Page 2: 1.2. ricardo marqués

Question 1

● Is there any effect of cyling infrastructure in bicycling safety? – Vehicular cyling says no

– Macro-evidence from countries is quite good (Netherlands, Denmark...)

– Meso-evidence from cities is not so good (Example: Pasanen report)

– Micro-evidence from particular infrastructure ¿?¿

Page 3: 1.2. ricardo marqués

Question 2

If infrastructure creates safety

● Is it an additive linear effect?

or

● Is it a non-linear “quantum” effect

Page 4: 1.2. ricardo marqués

Question 3 (safety in numbers)

● Are the streets safer because there are many cyclists?

or

● There are many cyclists because the streets are safer?

Page 5: 1.2. ricardo marqués

Seville as case study

Daily trips

Length of bikeways

Page 6: 1.2. ricardo marqués
Page 7: 1.2. ricardo marqués

Methodology● Multi-linear regression analysis:

RISK = ao + a1X1 + a2X2 + ...

● Variables– RISK: Total number of accidents involving bicyclists

and motor vehicles each year

– KM: Total length of bikeways in km

– TRIPS: Million of bicycle trips per year

– JUMP:● = 0 before 2007● = 1 after 2006

Page 8: 1.2. ricardo marqués

Data

(*) Estimated assuming the number of trips is constant

Page 9: 1.2. ricardo marqués

Numerical results 2006-2013

Page 10: 1.2. ricardo marqués

Graphical results 2006-2013

Page 11: 1.2. ricardo marqués

Numerical results 2000-2013

Page 12: 1.2. ricardo marqués

Graphical results 2000-2013

Page 13: 1.2. ricardo marqués

Some considerations

● The variable JUMP is the best explanatory variable.● The variable TRIPS is the worse one.● The best model is RISK-KM+JUMP, with JUMP

significant to a 90%.

● We interpret these results as suggesting that “networking” the bikeways is important by itself, and that there is not a big causality between TRIPS and RISK

Page 14: 1.2. ricardo marqués

Networking

Page 15: 1.2. ricardo marqués

Safety in numbers?

Jacobsen (2003)!!!

Page 16: 1.2. ricardo marqués

; a0

Page 17: 1.2. ricardo marqués

CONCLUSIONS● There is a clear correlation between infrastructure and

cycling safety.● Networking seems to play an important discontinuous role

in this correlation.● Explains why macro- and micr-analysis gives different

results?● Jacobsen's safety in numbers theory is quantitatively

confirmed. ● How causality goes: From infrastructure to safety and from

safety to number of cyclists or vice-versa?