Changing Travel Behaviour

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Changing Travel Behaviour. Phil Goodwin Centre for Transport and Society, UWE Bristol. ‘Changing’ is ambiguous. ‘Changing’ as a description of what is happening, whether we will it or not ‘Changing’ as an active intervention, with intent to make things different - PowerPoint PPT Presentation

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Changing Travel Behaviour

Phil GoodwinCentre for Transport and Society, UWE Bristol

‘Changing’ is ambiguous

• ‘Changing’ as a description of what is happening, whether we will it or not

• ‘Changing’ as an active intervention, with intent to make things different

An axiom: travel behaviour does change, and therefore it can be changed

Cars & Traffic in GB

0

10

20

30

1950 1960 1970 1980 1990 2000

Car

s, m

illio

ns

0

100

200

300

400

500

600

Tra

ffic,

bill

ion

vkm

CARS +1177%

TRAFFIC +815%

In one lifetime, car ownership and use have changed enormously

The change has been to establish a domination by car

Passenger Travel in GB, billion pkm

0

200

400

600

1950 1960 1970 1980 1990 2000

BUS - 50%

CAR +993%

CYCLE - 83% RAIL +26%

Trends show the net effect of a churn: but individuals change in either direction

Proportion of people in households whose car ownership increased or reduced

0%

10%

20%

30%

40%

50%

60%

70%

80%

Cars reduced No change Cars increased Net increase

Source – 1988 and 1991 South Yorkshire Panel surveys

Trip rates also can increase or reduce

% of people in groups with similar numbers of trips per person

0%

10%

20%

30%

40%

50%

60%

same band increase decrease

Source – London Panel Survey Spring and Autumn 1976

All the time, people are changing the method of transport they use

Main Commuting Mode, % of commuters

2.40.90.942.40.21.40.21.110

4.31.21.953.40.41.80.41.29

5.61.32.658.70.52.70.41.68

6.51.73.563.90.73.60.62.07

7.42.34.567.80.74.40.92.56

8.52.85.370.80.95.41.22.95

10.63.47.273.41.56.71.63.44

12.93.99.476.32.28.41.94.93

16.46.213.979.33.111.52.65.62

22.19.425.083.14.716.53.97.81

at least n years

9.73.37.466.91.56.21.43.3ave. yr

walkcyclecar pass.

car driver

m’cycbustuberail

Even relationships change(eg between car ownership and age)

Household Car Ownership by Cohort

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87

Age of head of household

Ca

rs p

er

ho

useh

old

1961-65

1951-55

1941-45

1931-35

1921-25

1911-15

1901-05

1970

1995

And between car ownership and income

Relationship between Car Ownership & Income

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 50 100 150 200 250 300 350 400

Total weekly expenditures, 1989 £

Car

s p

er h

ou

seh

old

Declining Income

Rising Income

Declining Income

Rising Income

1911 - 14

1961 - 65

1931 - 35

Policies have big effects(though more complex than intended)

• Increases in road capacity induce traffic• And capacity reduction reduces traffic• Price changes (fuel, fares, congestion

charging, vehicles) all influence traffic• ‘Soft’ measures change individual

behaviour substantially and can reduce traffic if supported by other policies

• Park and ride reduces traffic in the centre (but may increase it elsewhere)…

Induced traffic: SACTRA, 1994

an average road improvement induced roundly 10% of the base traffic in the short run, and about 20% in the long run, and there were some schemes with induced traffic at double this level.

the biggest levels of induced traffic were on the alternative routes that the schemes were intended to relieve.

And the opposite? – Cairns et al 1998

Practical experience of capacity reduction

Changes in traffic

-150 -130 -110 -90 -70 -50 -30 -10 10 30

Average: -22%

Central case: -11%

PRICE?Elasticities wrt Fuel Price per Litre

Literature Review

-0.30-0.10traffic volume

-0.60-0.25fuel consumption

long termshort term

Fares affect patronage

Dynamic Bus Fare Elasticity

-1

-0.9

-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0 1 2 3 4 5 6 7 8 9 10

Years following fare change

Ela

stic

ity

-0.88 -0.88-0.84

-0.6

-0.4

-0.86 -0.87

-0.81

-0.75

Short run (1-year)

Long run

-0.9

Effect of soft measures on individual choices, if induced traffic prevented

• 11% reduction in national traffic volume

• 21% reduction in urban peak period traffic (13% off-peak)

• 14% reduction in non-urban peak traffic (7% off-peak)

Park-and-ride in 9 citiesOverall Traffic Effects per Intercepted Car

-10

-5

0

5

10

15

20

25

30

35

Brig

hton

Cam

brid

ge

Cov

entr

y

Nor

wic

h

Ply

mou

th

Rea

ding

Shr

ewsb

ury

Yor

k

aver

age

km

urbanextra-urbannet

How fast does behaviour change?

The early research:Frequency of life events enabling choice

Conclusion

Travel behaviour is very much more volatile and changeable than is often thought, significantly sensitive to transport policy (whether intended or not) and a decision to 'leave behaviour alone' simply does not exist. Behaviour does and will change, and everything that Government chooses to do, or chooses not to do, has an impact on these changes.  The scope for making things better (or, indeed, worse) by changing behaviour is substantial, and unavoidable…

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