Cairns, S; Sloman, L; Newson, C; Anable, J; Kirkbride, A; Goodwin, P; (2004) Smarter choices - changing the way we travel. UCL (University College London), Department for Transport: London, UK.

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Abstract

Summary: In recent years, there has been growing interest in a range of initiatives, which are now widelydescribed as 'soft' transport policy measures. These seek to give better information and opportunities,aimed at helping people to choose to reduce their car use while enhancing the attractiveness ofalternatives. They are fairly new as part of mainstream transport policy, mostly relativelyuncontroversial, and often popular. They include:. Workplace and school travel plans;. Personalised travel planning, travel awareness campaigns, and public transport information andmarketing;. Car clubs and car sharing schemes;. Teleworking, teleconferencing and home shopping.This report draws on earlier studies of the impact of soft measures, new evidence from the UK andabroad, case study interviews relating to 24 specific initiatives, and the experience of commercial,public and voluntary stakeholders involved in organising such schemes. Each of the soft factors isanalysed separately, followed by an assessment of their combined potential impact.The assessment focuses on two different policy scenarios for the next ten years. The 'high intensity'scenario identifies the potential provided by a significant expansion of activity to a much morewidespread implementation of present good practice, albeit to a realistic level which still recognisesthe constraints of money and other resources, and variation in the suitability and effectiveness of softfactors according to local circumstances. The 'low intensity' scenario is broadly defined as aprojection of the present (2003-4) levels of local and national activity on soft measures.The main features of the high intensity scenario would be. A reduction in peak period urban traffic of about 21% (off-peak 13%);. A reduction of peak period non-urban traffic of about 14% (off-peak 7%);. A nationwide reduction in all traffic of about 11%.These projected changes in traffic levels are quite large (though consistent with other evidence onbehavioural change at the individual level), and would produce substantial reductions in congestion.However, this would tend to attract more car use, by other people, which could offset the impact ofthose who reduce their car use unless there are measures in place to prevent this. Therefore, thoseexperienced in the implementation of soft factors locally usually emphasise that success depends onsome or all of such supportive policies as re-allocation of road capacity and other measures toimprove public transport service levels, parking control, traffic calming, pedestrianisation, cyclenetworks, congestion charging or other traffic restraint, other use of transport prices and fares, speedregulation, or stronger legal enforcement levels. The report also records a number of suggestionsabout local and national policy measures that could facilitate the expansion of soft measures.The effects of the low intensity scenario, in which soft factors are not given increased policy prioritycompared with present practice, are estimated to be considerably less than those of the high intensityscenario, including a reduction in peak period urban traffic of about 5%, and a nationwide reductionin all traffic of 2%-3%. These smaller figures also assume that sufficient other supporting policies areused to prevent induced traffic from eroding the effects, notably at peak periods and in congestedconditions. Without these supportive measures, the effects could be lower, temporary, and perhapsinvisible.Previous advice given by the Department for Transport in relation to multi-modal studies was that softfactors might achieve a nationwide traffic reduction of about 5%. The policy assumptionsunderpinning this advice were similar to those used in our low intensity scenario: our estimate isslightly less, but the difference is probably within the range of error of such projections.The public expenditure cost of achieving reduced car use by soft measures, on average, is estimated atabout 1.5 pence per car kilometre, i.e. £15 for removing each 1000 vehicle kilometres of traffic.Current official practice calculates the benefit of reduced traffic congestion, on average, to be about15p per car kilometre removed, and more than three times this level in congested urban conditions.Thus every £1 spent on well-designed soft measures could bring about £10 of benefit in reducedcongestion alone, more in the most congested conditions, and with further potential gains fromenvironmental improvements and other effects, provided that the tendency of induced traffic to erodesuch benefits is controlled. There are also opportunities for private business expenditure on some softmeasures, which can result in offsetting cost savings.Much of the experience of implementing soft factors is recent, and the evidence is of variable quality.Therefore, there are inevitably uncertainties in the results. With this caveat, the main conclusion isthat, provided they are implemented within a supportive policy context, soft measures can besufficiently effective in facilitating choices to reduce car use, and offer sufficiently good value formoney, that they merit serious consideration for an expanded role in local and national transportstrategy.AcknowledgementsWe gratefully acknowledge the many contributions made by organisations and individuals consultedas part of the research, and by the authors of previous studies and literature reviews which we havecited. Specific acknowledgements are given at the end of each chapter.We have made extensive use of our own previous work including research by Lynn Sloman funded bythe Royal Commission for the Exhibition of 1851 on the traffic impact of soft factors and localtransport schemes (in part previously published as 'Less Traffic Where People Live'); and by SallyCairns and Phil Goodwin as part of the research programme of TSU supported by the Economic andSocial Research Council, and particularly research on school and workplace travel plans funded bythe DfT (and managed by Transport 2000 Trust), on car dependence funded by the RAC Foundation,on travel demand analysis funded by DfT and its predecessors, and on home shopping funded byEUCAR. Case studies to accompany this report are available at: http://eprints.ucl.ac.uk/archive/00001233/

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