SUSTAINABLE SUBURBAN TRAVEL – DO DEVELOPERS HOLD THE KEYS? Martin Gibson Transport Research Institute, Napier University Isle of Wight Council 1. ABSTRACT For many years, urban transport issues have been the focus of attention for policymakers and researchers, and more recently rural transport issues have gained more prominence. This polarisation of transport by geographical location has left suburban areas in something of a no-man’s land, and research into transport in suburbs has been limited, particularly in the UK. However, the importance of the suburbs is beginning to be appreciated in relation to planning for sustainable travel. In the US there is renewed concern about the impact sprawling suburbs have on car dependency, and in the UK the need for research in this area has been highlighted recently by both the Joseph Rowntree Foundation and the Independent Transport Commission. Government policies aimed at reducing car use mean that car dominated suburban developments are now deemed inappropriate, which raises issues of whether different forms of development would be more sustainable, what changes should be made to improve sustainability of new residential areas, and how acceptable sustainable development patterns would be to consumers. This paper reports on research examining relationships between the built environment, transport infrastructure, residential location choices and sustainability of travel, and discusses the relevance of developers to ensuring suburbs encourage sustainable travel. Initial findings on travel behaviour and attitudes in suburbs from analysis of National Travel Survey data suggests while residents of low density areas travel significantly further than those living at high densities, the relationship between land use and travel behaviour is not a straightforward one. These results are presented and discussed in the context of previous suburban studies, and a methodological framework for more detailed analysis of travel behaviour and attitudes in suburbs is put forward. © Association for European Transport 2002 2. SUBURBIA IN THE UK AND THE NEED FOR RESEARCH INTO SUBURBAN TRAVEL Love them or loath them, the suburbs are an important part of modern society. They house the majority of the British population (Hansard HC, 1999) and occupy a large area of the UK. Increasingly they not only house people, but workplaces and leisure destinations as well. For many years transport in the suburbs has not been the focus of significant attention for researchers and policy makers, with urban and rural areas often seen as higher priorities. Most Victorian and inter-war suburbs were served by efficient public transport, serving the primary travel need of suburb to city commuting, with many shopping journeys being possible on foot. As car use grew, the low densities of many suburbs absorbed most of the impact of travel changes, but as we enter the twenty first century, the strain is beginning to show in many suburban areas, with some streets becoming as congested those in city centres. Changes in shopping patterns and education, increases in car ownership, suburbanisation of housing and employment and numerous other factors have led to a situation where a variety of transport problems are affecting suburbs, and the travel habits of suburban residents are putting increasing pressure on those living in other areas. In many parts of Europe, it is common to find the middle classes living in city centres, while peripheral areas have large amounts of social housing. This model is typified by cities like Amsterdam and Paris. In the US suburbs have typically been built at very low densities, with the aim of accommodating car use being influential in their design. The UK has been influenced to a degree by both the European and American models, but typically policy approaches have followed the prototypical American model more closely, despite its apparent limitations with regard to sustainability. This has lead to urban forms designed to simultaneously accommodate car use and mitigate against its worst effects on the immediate area. Against this background current government policy seeks to arrest the growth in car use, and promote modal shift to more sustainable forms of transport, and a reduction in the need to travel, and journey distances. The significance of the built environment appears to be significant. This paper will discuss the evidence on this issue, and describe research currently underway to further investigate the influence of the built environment, and discuss the possible role of developers in securing a more sustainable transport future. This research into the sustainability of travel in suburbs is timely, with two major reports drawing attention to problems in the suburbs, and government policy starting to show a shift away from support of car dominated suburbs. The 1998 Joseph Rowntree Report “Sustainable renewal of suburban areas” (Gwilliam et al., 1998) highlighted various problem areas in suburbs, with transport being one of the key issues involved in suburban decay. The report’s authors highlighted the lack of research into suburbs as part of the UK © Association for European Transport 2002 urban picture, suggesting “of analysis of changes, threats and opportunities for the suburbs as a whole, there has been very little” (Gwilliam et al., 1998, p. 64). More recently the Independent Transport Commission highlighted problems in suburbs of poor accessibility for those without cars and congestion suffered by car users – its view was that the situation would grow worse over the coming decades (Independent Transport Commission, 2001). Suburban travel is one of the key areas that the ITC intend investigating. Government policy in recent years has started to reflect concerns over car based suburban development, this can be seen in planning guidance which sets down minimum densities, promotes mixed use development and supports reduced parking standards (Department of the Environment Transport and the Regions, 1998, Department of the Environment Transport and the Regions, 2000, Scottish Office, 1999). Most research into suburban travel issues has been carried out in the US, where problems relating to suburbs have been acute for many years. While this research gives a useful base, the cultural context is significantly different, and results do not necessarily transfer to the UK context. 3. CONVENTIONAL SCHOOLS OF THOUGHT ON SUBURBAN TRAVEL AND URBAN FORM The suburban transport debate is dominated by two main ideas, with most authors suggesting one or other of these explains the difference in travel behaviour between cities and suburbs. They can be broadly categorised as follows: • • As density decreases, so does accessibility and viability of local services/public transport, hence car use increases. Differences in travel are related to income and lifestyle – well off households drive more, want to drive more, and are more commonly found in suburbs – they don’t drive because they live in suburbs, in fact they may choose the suburbs in part because they permit the levels of car use they seek. Findings of various authors broadly support the first idea. Newman and Kenworthy’s research (1989)is some of the most extensive into transport energy use and urban form, and has been the subject of comment by many authors, as well as influencing government. They compared transport energy use in 32 world cities, and concluded there is a string correlation between overall density and energy use, even controlling for income, fuel cost and vehicle efficiencies. Holtzclaw (1997) found that doubling residential density reduces VMT and car ownership by between 14% and 16%, and 9% and 16% respectively. This figure is greater if associated factors such as increased transit frequency are considered. The figures were found to hold at various densities (ie by doubling very low densities or relatively high densities). The effect of household income is assessed, but while density is found to have a smaller impact among higher income brackets, the reduction in VMT is still © Association for European Transport 2002 substantial. Regional Alliance For Transit (RAFT) models of “traditional development patterns” impact on travel suggests that if this form of development were integrated into public polices, in 15 years VMT could be reduced by 6%, based on a conservative model (Lewis, 1998). Frank et al. (2000) have gone a stage further than most and analyse the link between land use and emissions of private vehicles. Their study shows a significant negative relationship between household density and vehicle emissions. UK studies have relied mainly on the rather restricted National Travel Survey data. This can be analysed by density, but only within certain density bands across the whole country, with no opportunity to specifically analyse any particular area, or area type. ECOTEC (1993) found that increased density reduced distance travelled to work and total car use, and increased the proportion of travel to work made by public transport. Regardless of income, car use is generally lower in high-density areas. Cooper et al. (2001a) found that even in a highly car dependent survey group respondents in higher density areas were more likely to walk to work or the shops than those in lower density areas. A modelled densification along transport corridors showed a 14-19% decrease in VMT, or a 28% increase if coupled with substantial improvements to public transport in the corridors. (Cooper et al., 2001b) However some authors have found that any links between land use and transport appear to be weak or non-existent, and support the hypothesis that lifestyle is the significant factor. Gordon (1997) suggests that Newman and Kenworthy’s work is affected by two or three unusual cities (particularly Singapore and Hong Kong) and variation in petrol pricing, which he claims accounts for more of the variability in energy use than density (results within Newman and Kenworthy’s research did, however, include values controlled for petrol price variation). Analysis of National Travel Survey data, and census travel to work data did show reduced travel distance to work in higher density areas, although the effect was not very strong. Boarnet and Sarmiento (1996) found little evidence of a link between land use and non work travel, suggesting residential location and thus nearby land use characteristics should be regarded as endogenous in travel behaviour models. In an article critical of opponents of suburban sprawl, Hayward (1998) contends that rather than residential density being the driving force behind increased private vehicle travel, it is in fact a measure of rising affluence and changes in work habits that has been the primary cause of the increase, and thus programmes of densification would be fruitless. 4. RETHINKING THE APPROACH TO INVESTIGATING TRAVEL IN SUBURBS Some authors have gone beyond these two ideas, suggesting the situation is really rather more complex than either would suggest.. © Association for European Transport 2002 Boarnet and Sarmiento (1996) conclude links between land use and non work travel are weak, however they also indicate that the relationship between land use and travel behaviour is complex, and non-work travel is poorly understood. Susan Handy highlights the lack of consideration of attitudinal influences in assessing land use and travel, suggesting these need to be considered as well as a variety or urban structure variables in order to explain more accurately differences in travel between areas (Handy, 1996). The diversity of potential influences on travel patterns is highlighted by research into the cultures of mothering and car use in suburbs of Sydney. It is suggested that understanding the culture in which travel decisions are made is imperative (Dowling, 2000). Crane (1996) suggests that standard urban models assume residents never think about their second job, and highlights the need for a less simplistic approach to modelling residential location choice is needed. Even in terms of urban form variables, many authors highlight numerous macro and micro factors which are believed to influence travel. Rather than just looking at key macro variables like density, aspects such as provision of convenience shops within neighbourhoods, reduction of garden sizes, narrowing of streets, and removing cul-de-sacs are also suggested (Adler, 1995, Cervero and Radisch, 1996, London, 1996) Stead (2001) has carried out one of the most detailed analyses of the linkage between land use, socio-economic factors and travel patterns in the UK. His multiple regression analysis of National Travel Survey data revealed that socio-economic characteristics explained around half of the variation in travel distance per person, while land use characteristics explain around one third of the variation. While this supports the thesis that socio-economic variables are more relevant, it highlights the fact that independent of these variables, land use explains quite a high proportion of travel distance. Stead also notes the complexity of the relationships between land use variables, and with non-land use variables, suggesting combinations of land use measures may create synergies which have significant impacts on travel, and that non-land use measures may compliment the effect of land use policies. Based on this evidence from the literature, and the limitations of the simplified, “single issue” concepts in consistently explaining a sizeable amount of the variability in travel, it is suggested that looking at suburban travel as a complex system will provide more useful insights into travel behaviour. Rather than a simple explanatory factor, or combination of several factors, the differences between suburban and urban areas are seen as the product of a complex system comprising a large number of interrelated factors. The system incorporates factors such as location choice, work/home relationships, density, mixed use (or lack thereof), public transport infrastructure, street layout, household income and family structure. The literature clearly indicates that trying to take a simple approach to solving a complex problem is unlikely to provide the most useful results. The role of the housing market is perhaps key to understanding the complexities of the problem. Understanding subtle © Association for European Transport 2002 segmentation of the market may provide insights into underdeveloped markets, and potential models for urban forms which engender more sustainable travel patterns. What has only been touched on by previous authors is the potential effects of other transport interventions on behaviour in different types of urban settings. It may be that the impact of changes to development patterns per se may be small, but that they would create an environment which allowed for more sustainable travel when residents are given sufficient incentive to change their travel behaviour. 5. ANALYSIS OF SECONDARY DATA In the initial stages of the research, various secondary data sets were analysed. This has involved the British Social Attitudes Survey (BSA) and the National Travel Survey (NTS). The BSA has been used primarily for background information, but will probably be integrated with other data later in the process Simple correlations between various factors in the NTS were analysed in order to begin to assess the strength of relationships between factors such as density and distance travelled, identify potential for further analysis, and identify variables which can be transferred to census data to define areas for primary data collection. Following this answer tree analysis was performed to draw out patterns in the data and identify potential subgroups. 5.1 Relationships between travel and urban form On first inspection the NTS data appears to support the proponents of densification. Figure 1 shows how average household VMT rises significantly as postcode sector population density decreases, with households living at low densities (<5pph) on average driving four times the distance of households living at high densities (>70pph). Total distance travelled by all modes shows a similar pattern (figure 2), although the disparity between the highest and lowest is rather less, with those living at the highest densities travelling slightly more than twice the distance of those at the highest. This supports the idea that suburban residents travel further than their urban counterparts, and that a greater proportion of travel is made by car. However, analysis provided in table 2, reveals relatively weak correlations between distance travelled and density. This suggests that while travel may be less sustainable in the suburbs, there is no strong direct link between density and distance travelled. Similarly there is only a weak correlation between household car ownership and residential density, despite households in the lowest density band owning on average twice the number of cars owned by residents of the highest density areas. © Association for European Transport 2002 There is very little sign of any systematic pattern in the relationship between density and household income, with little correlation between the two variables. Household income does show a strong correlation with both total travel distance, and travel by car, however the degree of accuracy in recording household income for the NTS is relatively low, so it is difficult to draw definitive conclusions. Average number of children per household generally increases with density, although there is very little correlation between number of children and density. This suggests that the relationship between lifestyle variables (such as income and number of children) and density is more complex than it first appears. © Association for European Transport 2002 r ve do an 9 75 4.9 7 to 9 60 9.9 5 to 9 50 9.9 4 to 45 4.99 4 to 9 40 9.9 3 to 9 35 4.9 3 to 30 9.99 2 to 9 25 4.9 2 to 20 9.99 1 to 9 15 4.9 1 to 10 99 . o9 5 t 99 . o4 1t 1 r de Un 4000 3000 2000 1000 Mean HH distance travelled - all modes 2000 1000 0 Mean HH distance travelled - Car Driver Figure 1 – Mean household distance travelled as car driver and population density 3000 Pop. Density (Pers/hec) 5000 r ve do an 9 75 74.9 to 9 60 9.9 5 to 9 50 9.9 4 to 9 45 4.9 4 to 9 40 9.9 3 to 9 35 4.9 3 to 9 30 9.9 2 to 9 25 4.9 2 to 9 20 9.9 1 to 9 15 4.9 1 to 10 99 9. to 5 99 . o4 1t 1 r de Un Pop. Density (Pers/hec) Figure 2 – Mean household distance travelled by all modes and population density © Association for European Transport 2002 Table 1 - Correlations between selected socio-economic, urban form and travel variables HH Distance travelled HH Car Driver .800 distance Population -.183 density* Number of .523 HH cars HH Income .467 No. of .230 children in HH HH Car Populatio n density* Driver distance Number of HH HH cars Income -.212 .609 -.215 .468 .080 -.071 .028 .561 .104 .134 * Population density is based on number of persons per hectare, measured at postcode sector level All values are Pearson Correlation “r values”, and are significant at the 0.01 level. Table 3 – Correlations between selected urban form and travel variables for middle income families sub-group HH Car distance Population density* Number of cars HH distance HH Car travelled distance driver .712 -.254 HH .241 driver Population density* -.261 .377 -.187 All values are Pearson Correlation “r values”, and are significant at the 0.01 level. © Association for European Transport 2002 Table 4 – Correlations between total household distance travelled and household distances to work HH Distance travelled HH Average distance to .252 work HH Cumulative distance to .304 work All values are Pearson Correlation “r values”, and are significant at the 0.01 level. © Association for European Transport 2002 Following on from this analysis, a sub group from the data set was analysed. This group contained middle income households with one or more children. Thus at a basic level this sub-grouping controls for income and lifecycle stage. Correlation analysis of distance travelled and density within this group which can be seen in table 3 is rather interesting. Whilst none are particularly strong, total household distance travelled and car driver distance are notably stronger than those for the whole sample, suggesting that density per se may have more effect on this particular group. However, the correlation between density and number of cars is weaker than that for the entire sample. This may indicate that car ownership is more stable across varying densities for this group, but car ownership per se does not have such a great effect on travel behaviour. Given the magnitude of the differences it would be unwise to draw any conclusions from this, but it does warrant further investigation. These results are primarily intended to provide pointers for further statistical tests which are currently being undertaken. Answer tree analysis has provided some useful insights into sub-groups of the data, as well as demonstrating that land use and accessibility variables do have an impact across different socio-economic groups. Socio-economic group and car ownership are the dominant variables, but density was relevant in several of the trees, with several threshold values noted. These thresholds are generally higher for higher socio-economic groups. Car ownership and distance to work can fairly effectively predict overall travel distance, and their effectiveness is notably higher within suburban density bands. However, a ratio calculated from the analysis actually shows a slightly weaker correlation than one calculated by experimenting with combinations of the original variables. Accessibility of public transport featured in a few of the trees, and fairly consistently divided cases around 3 minutes walk time. The accuracy with which the variables used can predict travel is quite variable, with model risk of between 20 and 50%, though generally towards the lower end. This suggests that the variables seen as the “main” socio-economic and land use factors which influence distance travelled can still only explain a moderate amount of this variation. 5.2 Transfer to census data The second purpose of the NTS analysis was to identify variables which could be transferred to census data to allow more geographically accurate analysis, and define areas for primary data collection. The census only contains a limited amount of data relevant to travel, but some of the variables are common to NTS and census data sets, and thus a series of variables could be tested using the NTS data for suitability as indicators to highlight areas of relatively high and low sustainability. Suburban variables were be developed likewise to identify suburban areas from census data. Use of ACORN classification data was considered, but the implications for matching a current postcode based data set with an 11 year old ward based dataset made this © Association for European Transport 2002 option too complex, with any accuracy gain offset by possible loss in the conversion process. The relevant variables available in the census data set are • • • Distance to work Mode to work Number of cars To maximise the usefulness of these variables it is necessary to explore how much of the variability in distance travelled each can predict, and to combine them in these proportions into a sustainability indicator variable. Distance to work shows a moderate correlation with total distance travelled, with cumulative household distance to work showing a closer correlation than the household mean value, as can be seen in table 4. There is also a moderate correlation between number of household cars and total household distance travelled shown in table 2. These figures suggest that the variables investigated collectively provide a reasonable indication of the relative sustainability of travel between different areas. Further work to determine the best combination of these variables showed no significant gain through using them other than in an equally weighted ratio. The distance to work variable proved to have only limited use, as it is only available at ward level, whereas the analysis was to be conducted at enumeration district level. Instead the proportion of employees working outside of the district was used. This may introduce an element of error, as those living close to the district border may well make a short commute outside of the district, however in general this effect is likely to be fairly small. 6. METHODOLOGY FOR PRIMARY DATA COLLECTION While the analyses of NTS data referred to earlier, adds some additional insights to the data about suburban travel available from the literature, and lends support to the idea that the link between density is not a simple relationship, it still only gives a small part of the picture. By its nature the NTS is a general survey, not targeted specifically at certain areas, and identifying specific areas is not possible. The initial analysis does appear to confirm the hypothesis that many factors are involved in influencing the travel patterns of people in suburban areas. It may be that some of these are socio-economic, some are related to the built environment and transport infrastructure, and some due to psychological/perceptual issues. In order to examine the relative importance of these factors more closely, and to test the acceptability of measures to improve sustainability of travel in suburbs by addressing the underlying issues, primary data collection is being undertaken. In order to maximise the value of any survey work, the process through which survey © Association for European Transport 2002 areas was chosen encompassed quantifiable factors and subjective qualitative indicators. This process involved several stages, as follows: 1. Selection of cities/towns to consider for analysis. Originally this was to be informed by census data, but due to financial constraints a limited number of cities were considered, and detailed work to establish the suitability of Southampton for analysis was undertaken, with other short listed cities to be considered if Southampton did not provide suitable survey areas, 2. Highlighting suburban areas within the city. This was achieved using pre-selected indicators from the census data. Census boundary data from UKBORDERS was used to map suburban areas using ARCVIEW GIS and Map Explorer software. 3. Using sustainability indicators, suburban areas were graded into bands of relative sustainability. Areas of relative high and low sustainability within suburban areas were sought. 4. Areas selected were checked to see if they appear to meet the requirements of a suburb (as defined for the purpose of this study). This involved analysis of maps and aerial photographs, and information from estate agents, primarily gathered over the Internet 5. Each area was visited to check the findings of desk based analysis match the reality, and to allow for some of the more subjective features of suburbia to be assessed. A pilot survey is being carried out in July/August 2002 to test the survey design, and determine the most cost effective way to distribute the survey whilst maintaining a high response rate. Based on this pilot, any necessary modifications to the survey implement and the data collection process can be made. If changes are relatively minor, it may be possible to include pilot data in the final analysis. The main survey will be carried out in September 2002. The survey design will take the form of a self-completion questionnaire, and will be administered either through a call and collect arrangement, or a postal survey. It will gather data relating to travel behaviour, attitudes to access and mobility. The survey will couple information on travel behaviour with attitudes to travel and residential location choices in an effort to obtain a more complete picture of the reasons why suburban residents travel in a less sustainable manner than those living in denser inner areas. This methodology is rather different to most previous suburban studies. In general these have attempted to investigate one element of “suburban-nes”, such as density or street layout. Locations are generally chosen to reflect variation of this characteristic, and control for other differences. While this method has its merits, it only looks at a single issue, rather than the complex interrelation of issues which are believed to effect travel. By selecting areas of relative high and low sustainability, this study attempts to control for sustainability, and assess the characteristics of areas with different sustainability characteristics. Data will be collected relating to two of © Association for European Transport 2002 the main areas of trip production, shopping and commuting, from which it should be possible to identify specific trip types which are different (in length, mode, frequency etc.) between the survey areas. These differences can then in turn be related to differences in the urban form. For example, in suburb A households tend to drive to a supermarket 2 miles away in order to get basic shopping, such as bread and milk, whereas those in suburb B are more likely to walk to a local shop. Assessment of the two areas reveals most people in suburb A are within a 5 minute walk of the local shop, while residents of suburb B are between 10 and 15 minutes walk of the nearest shop. As such, they drive, but to a supermarket rather than the closer shop. Similarly it may be possible to relate a change in mode and distance used for clothes shopping to the proximity of an out of town shopping centre. 7. THE ROLE OF DEVELOPERS The initial stages of this research have shown a relationship between the built environment and sustainability of travel appears to exist. However the impact of the built environment is small compared to that of household income, which acts as the main determinant of travel distance and car use. However, while the direct impact may be small, it is hard to ignore the likelihood that forms of development which promote ease of car use over other modes provide an environment which is unsuitable for more sustainable lifestyles. Thus for those living in such areas, no real transport choice exists. Demand management measures or policies aimed at encouraging modal shift are unlikely to be effective where no viable alternatives to the car exist. What is not clear is which factors are significant in creating this “car only” urban form, and which could improve the viability of more sustainable forms of transport? It may be that developers need to change their approach to building suburbs, but to do so based on speculation could be counterproductive. This research should move forward our understanding of the changes that need to be made if sustainable transport is to become a reality. Developers may indeed hold the key to sustainable suburban travel, but in a conservative industry change is only likely to stem from strong direction from government, or a clear defined market for sustainable housing. It may be that such a market already exists, but is not being exploited by developers happy to follow a traditional route as long as they can sell houses. 8. ACKNOWLEDGMENTS The doctoral study this paper is based on is supported by a research studentship funded by the Go-Ahead Group. © Association for European Transport 2002 Its presentation has been made possible by support from the Transport Research Institute and Isle of Wight Council. 9. REFERENCES Adler, J. (1995) 15 Ways to fix the suburbs. Newsweek, 15 May 1995 Boarnet, M. and Sarmiento, S. (1996) Can land use policy really affect travel behaviour? A study of the link between non-work travel and land use characteristics. Working Paper 342. Berkeley: University of California Transportation Center. 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