The evolution of bicycle mobility in France

Francis Papon- 27 May 2011

The evolution of bicycle mobility in France

Francis Papon 22 septembre 2016


Data sources

•  Sales: Chambre syndicale then CNPC since 1890 •  Fleet: Impôt sur les vélocipèdes 1893 to 1959,

National Travel Surveys: 1966 to 2008 •  Traffic: national highways 1903 to 1960, Paris since 1997 •  Accidents: ONISR since 1982 •  Trips and modal share: national and local travel surveys

in urban areas since 1976


French bicycle market 1992-2006 Sales Frenchsupply Imports Exports

1992 2878528 728035 2150493 307279

1993 3199100 667600 2531500 275600

1994 2935569 873850 2061719 400720

1995 2870000 1040000 1830000 381150

1996 2351026 992160 1358866 342000

1997 2242900 1092900 1150000 239400

1998(*) 2435000 1300000 1135000 206000

1999(*) 2584000 1334000 1250000 270000

2000(*) 2690000 1580000 1110000 330000

2001(*) 2290000 1273000 1017000

2002(*) 2422000 1228000 1194000

2003(*) 2747000 1242000 1505000

2004(*) 3087000 1375000 1712000

2005(*) 3702200 1238200 2464000

2006(*) 3250000 1060000 2190000

Source:FIEV


Bicycle traffic peaked 1935-1955 on French highways

Source:Barles,2004CumulatedtrafficintensityonnaGonalhighways(perday)


0

50

100

150

200

250

1970 1980 1990 2000 2010

Accidents

Bicycles

FataliGes

Injured

Seriousinjury

A decreasing involvement of bicyclists in accidents in France

Source:ONISR

Basis100in1995

In1970:795killedand13157injuredIn2009:162killedand4379injured


Travel surveys in France

•  Over 100 surveys in French cities from 1966 to present (Certu, Dreia) but bicycles only since 1976

•  5 National Travel Surveys: 1966-67, 1973-74, 1981-82, 1993-94, 2007-08 (Insee, Soes, Inrets) home to work trips 1959

•  Old surveys only known from publications


Local travel surveys 1976-1998 and 1999-2007

Côte Basque

Fort-de-France

Montpellier

Brest

Béthune

Besançon

Maubeuge

Pau

Savoie

Vienne


A general decline of bicycle trips

0,00

0,05

0,10

0,15

0,20

0,25

0,30

1 2 3 4

Elbeuf

Amiens

Aix-en-Provence

Belfort

Dunkerque

Lorient

Nancy

Orléans

Reims

Valence

Clermont-Ferrand

Etang-de-Berre

Grenoble

Rennes

Rouen

Toulon

Valenciennes

bicycle trips per person per day

76-82 83-90 91-98 00-07

Rennes

Rouen


0,00

0,05

0,10

0,15

0,20

0,25

0,30

0,35

1 2 3 4

Nantes

Saint-EGenne

Strasbourg

Bordeaux

Toulouse

Lille

Marseille

Lyon

Paris

PeGtecouronne

Grandecouronne

Île-de-France

A recent rise in some of the largest cities

bicycle trips per person per day

76-82 83-90 91-98 00-07

Strasbourg

Lyon

Toulouse

Marseille


A rising national bicycle fleet

0

5000000

10000000

15000000

20000000

25000000

30000000

1880 1900 1920 1940 1960 1980 2000 2020

Source:CNPCandnaGonaltravelsurveys


Bicycle narrow share of trips

0

200

400

600

800

1000

1200

1973-1974 1981-1982 1993-1994 2007-2008

PublicTransport

Car

PTW

Bicycle

Walk

milliontripsperweek

3,9%

4,2%2,7% 2,8%

Source:naGonaltravelsurveys


Bicycle narrow share in mileage

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

1973-1974 1981-1982 1993-1994

Other

PublicTransport

Car

PTW

Bicycle

Walk

millionpassengers-kilometresperweek


1,8% 1,5% 0,9%


Evolution of bicycle mobility in France 1959-2008

1959 1967 1973-76 1981-82 1993-94 2007-08

Bicycle fleet ‘000

9 167 14 600 13 133 21 270 26 700

Bicycle share (%) in Home to work trips

9 7 5 4 2,7 2,2

Bicycle trips per person per day

0,15 0,13 0,13 0,08 0,08

Bicycle mileage (km) per person per year

116 98 102 83 97



Main means share 1920 -2008 Source:biographiesinnaGonaltravelsurvey2007-08


All bicycle use indicators 1890 -2010 Source:diversebase100in1995


Thank you


French transport biographic survey

•  Retrospective surveys use people’s memory •  Other studies in France outside transport •  Transport biographies in UK, Switzerland, Germany •  In France biographic survey in NTS 2007-2008 •  1150 grids filled •  One line per year •  One column for each variable: dwelling place,

household size, number of children, number of motorcycles, number of cars, main activity, activity place, main transport means

•  Two aims: historical and longitudinal


Main home to work means share in Britain 1890-1998

Source:Pooley&Turnbull,2000


sample of dwellings (30,000)

respondent households (20,000)

individuals living in the households

vehicles [cars&vans, quads, motorcycles, bicycles]

commuting trips to work, school or kindergarden

KISH (18,500) vehicle diary

(1 week)

daily trips 1 weekday and

1 or 2 weekend day

long distance trips

biography

GPS survey

The French National Travel Survey 2007-2008

1,150 grids filled at the end of 2nd visit

1st visit

2nd visit

Between visits


Comparability with historical cross section surveys (1) Biases in biographic survey

Problem !  Mobility definition:

Only one main mode to a regular place (work or education), or other trips, per year

Solution Comparison of main transport mode for three groups -those commuting to work -those commuting to education -others


Comparability (2): Biases in biographic survey

Problems

!  Geography: Only 17 regions were surveyed

!  Sampling: Over-sampling of multi-car households

!  Structure: The structure of the population from the biography sample differs from the actual structure that existed then

Solution

Weighting correction for recovery of the sample


Comparability (3): Biases in biographic survey

Problem !  Survival: Only

survivors in 2008 from 1907 to 2002 generations were recorded

Solution !  Survival rate

weighting !  Extrapolating

backwards previous generations behavior


Source:NTS1993-1994,regulartrips,NTS2007-08,biographies1988-00

Biographies yield reliable modal share for regular trips

Comparison biographies vs cross section surveys


Source:NTS2007-08,biographies

Decade vs age (bicycle share in %)

Biographies: bicycle main means modal share



Decade vs generation (bicycle share in %)




Generation vs age (bicycle share in %)



Estimation of an age-period model

•  Different generalized logistic model tested •  To estimate main means share •  Many variables difficult to know in the past •  Low effect of generation, high effect of period •  Age-period model easiest model to estimate past modal

share, taking into account past age groups share •  Walk is reference mode •  Confidence intervals computed for other modes •  Bicycle share highest in 1930’s and 1940’s

The evolution of bicycle mobility in France

Science

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