Cycling Demonstration Towns
Acknowledgements Report authors: Andy Cope, Research and Monitoring Unit, Sustrans Lisa Muller, Research and Monitoring Unit, Sustrans Angela Kennedy, Research and Monitoring Unit, Sustrans Data analysis: Academic advisors: Research and Monitoring Unit, Sustrans Dr John Parkin, University of Bolton Matthew Page, Institute for Transport Studies, University of Leeds We would like to acknowledge the support of individuals at each of the towns who dealt with the collection of data, and the supply of such to the monitoring team. November 2009 i
Executive summary... 1 1. Introduction... 5 Overview of project... 5 Background... 5 Aims and objectives... 6 Project process... 8 Structure of report... 9 2. Methodology...10 Automatic cycle counters...10 Manual counts of cyclists...12 School travel surveys...12 Pupil Level Annual School Census...13 Bike It hands-up surveys...13 Local authority hands-up surveys...14 Behaviour and attitude surveys...14 Counts of parked bikes...15 Workplace travel surveys...15 Accident data...16 Travel Behaviour Surveys...16 Attributing change to the Cycling Demonstration Towns programme...16 3. Summary of overall findings...17 4. Aylesbury...24 Data availability in Aylesbury...25 Continuous automatic cycle counters...25 ii
Manual classified counts...27 School travel surveys...29 Counts of parked bikes...31 Cycle incidents...31 5. Brighton and Hove...33 Summary...33 Data availability in Brighton and Hove...34 Continuous automatic cycle counters...34 Manual classified counts...35 School travel surveys...36 Counts of parked bikes...38 Behaviour and attitude survey...39 6. Darlington...40 Summary...40 Continuous automatic cycle counters...41 Manual classified counts...42 School travel surveys...43 Local authority survey...43 PLASC...45 Travel behaviour survey...46 Cycling incidents...46 7. Derby...47 Summary...47 Data availability in Derby...48 Continuous automatic cycle counters...48 Manual classified counts...50 iii
School travel surveys...50 Counts of parked bikes...55 Behaviour and attitude survey...55 Cycling Incidents...56 8. Exeter...57 Summary...57 Continuous automatic cycle counters...58 Manual classified counts...60 School travel surveys...61 Workplace Travel Survey...65 Behaviour and attitude survey...66 TravelSmart data...66 9. Lancaster with Morecambe...67 Data available in Lancaster and Morecambe...68 Continuous automatic cycle counters...68 Manual classified counts...70 School travel surveys...73 Counts of parked bikes...75 Behaviour and attitude survey...75 TravelSmart data...76 Cycling incidents...76 10. Case studies...78 iv
Executive summary In 2005 Cycling England launched a Cycling Demonstration Town programme to invest in measures to stimulate increased levels of cycling. The first phase of the programme ended in March 2009. This report presents the findings of the project commissioned to monitor the Cycling Demonstration Town programme. The first part of the report addresses overall changes in cycling activity, based on core data collected in each of the six towns. This is followed by a series of case studies drawing together examples from across the towns, grouped into common themes. Overall changes in cycling activity Automatic counter data indicate an average change in cycles counted of +27% across all towns between January 2006 and projected to December 2009, based on data collected between January 2006 and March 2009 and relative to a 2005 baseline (2006 for Brighton and Hove). At the individual town level, the average change in cycles counted ranged from +2.4% to +56.8% Manual counts of cyclists indicate an increase over the project for three of the six towns, a decrease in two towns and a mixed picture for Lancaster (an increase) with Morecambe (a decrease) In three towns where counts of parked bikes were performed, counts increased in two towns, and decreased in the third The proportion of children cycling as the usual mode of travel to school increased in five of the six towns In schools receiving support to encourage cycling, the proportion of pupils cycling to school regularly increased, as did the cycling mode share, and, where additional surveys were performed, levels of cycling at these schools were generally maintained Household travel surveys in two of the six towns suggest increased cycling levels Workplace travel surveys in one of the six towns indicate an increase in journeys to work by bike 1
Table 1: Data included, a short description of the metric and a summarised expression of results for each area of activity Data source Data included WHOLE TOWN ACTIVITY Automatic Unweighted mean percentage change cycle relative to 2005 baseline (2006 for Brighton) counts calculated using data collected between January 2006 and March 2009 Manual Unweighted mean percentage change per cycle count Counts of parked bikes year in quarterly manual counts Range of change in counts of parked bikes counted on beats performed in three towns Socialdata household Household surveys in one town cycling trips per person per year travel Household surveys in one town survey Relative change in trips by cycle as main mode JOURNEYS TO WORK Workplace Workplace travel survey performed in one travel town surveys proportion of respondents for which cycling is the usual mode of travel to work CHILD POPULATION (<16) School Annual pupil-level survey, all schools, Census pooled data for 2006/07 and 2007/08 (PLASC) academic years data proportion of pupils for which cycling is the Hands up surveys of Bike It schools Hands up surveys of Bike It schools usual mode of travel to school Surveys of Bike It schools, pooled data from baseline surveys (in September 2006/2007) and ex-post surveys (in July 2007/2008) proportion of pupils cycling to school either every day or once or twice a week Surveys of Bike It schools, pooled data, change in cycling mode share between baseline surveys (in September 2006/2007) and ex-post surveys (in July 2007/2008) proportion of pupils for which cycling is the mode of travel to school on day of survey Short description of metric Result Cycle activity +27% relative to baseline Cycle activity +4% per year Cycle activity -9% - +32% change over project period Cycle activity +120% (from 15 to 33) Cycle activity +69% Cycling mode share for trips to work Cycling mode share for trips to school (SC) Number of children cycling regularly to school (HU) Cycling mode share for trips to school (HU) +5% or +0.4%-point (from 8.5% to 8.9%) +16% or +0.3%-points (from 1.9% to 2.2%) +126% or +14.6%-points (from 11.6% to 26.2%) +174% or +7.3%-points (from 4.2% to 11.5%) 2
Key findings of the Cycling Demonstration Town programme The effectiveness of targeting investment Cycling Demonstration Towns Changes in levels of cycling are greater in areas targeted by procycling investment The rate of growth in cycling on routes close to schools is greater than that observed on other routes in a town where the principal focus is on children and young people The rate of growth on routes close to key work places is particularly high where the project engaged with work places The importance of high quality provision A well-defined and well-promoted dense network of routes can stimulate notable growth in cycling activity in the area it serves High quality, well connected routes carry considerable volumes of cycle traffic; extending the connectivity of a route can stimulate growth in cycling across the day, even on a heavily used route Infrastructure linking a wider network through overcoming a barrier to cycling can be a focal point for cycling activity in a town Well monitored connecting infrastructure can provide a very useful basis for estimating total cycling activity Distribution of cycling activity In a town where modest levels of cycling activity are observed, and most promoted routes are segregated from motor-traffic, growth in off-carriageway cycling is observed Where conditions for cycling are favourable, and where a critical mass of cyclists already exists, additional growth in oncarriageway cycling activity can be observed Legitimisation of cycling on a traffic-free route previously inaccessible to cyclists has resulted in some degree of displacement from the road to the traffic-free route, but has generated an overall increase in use 3
A linear route serving and linked to multiple attractors generates shorter trips as well as end-to-end activity Evidence for growth in levels of cycling A suitable pro-cycling intervention can stimulate a marked change in the rate of growth of cycling activity on a route The rate of growth in cycling activity on a long-established, highquality route can be considerably enhanced through the effect of pro-cycling investment in a town Growth in cycling can be sustained over a long period of time on quality routes 4
1. Introduction Overview of project 1.1. In 2005 Cycling England launched a Cycling Demonstration Town programme to invest in measures to stimulate increased levels of cycling through combinations of physical infrastructure, promotion and other smart measures over a three-year period. The towns selected as Cycling Demonstration Towns were Aylesbury, Brighton and Hove, Darlington, Derby, Exeter and Lancaster with Morecambe. 1.2. In order to understand the impact of the measures being deployed in the towns, a programme of cycle activity measurement and monitoring was commissioned to collect robust data on changes in levels of cycling activity. Sustrans Research and Monitoring Unit, in association with the School of the Built Environment and Engineering at the University of Bolton, and the Institute for Transport Studies at the University of Leeds, submit this report as the principal output of the project to monitor changes in levels of cycling activity in the six towns. Background 1.3. The monitoring of cycle use is challenging because of generally low cycle traffic volumes (relative to road vehicle volumes). This is evidenced by the difficulty of detecting statistically significant changes in cycle usage in national data sets and other large data sets, despite their anecdotal documentation and regular detection on a project-by-project basis. The problem this presents is a risk that the impacts of any largescale programme may be undetected if an overly simple monitoring regime is used. 1.4. The work undertaken to monitor activity in the cohort of Cycling Demonstration Towns has been instrumental in helping to define suitable approaches to monitoring cycling at the town and city-wide level. In particular the project has served to demonstrate the viability of a variety of approaches to data collection, the relative importance of the contribution that each data source can make, the analytical possibilities 5
for the data, the nature of the indicators that can be effectively measured, and the way that the data can be used to answer the pertinent questions. 1.5. The project has also served as a key point of reference for the ways in which monitoring is conducted by local authorities; from the initial review stage in the context of a non-specialised delivery programme, and from the delivery stages in the context of best practice. This learning has been carried forward for the work in the Cycling City and Towns programme. 1.6. Fundamentally, this report presents the most complete and comprehensive assemblage of data on cycling for a number of towns looking at the impact of pro-cycling interventions in the UK. Aims and objectives 1.7. The aims as defined in the original monitoring project brief (Department for Transport) are: to give a whole town overview of changes in levels of cycle use it must allow for regular measurements of levels of cycling, and should cover: a variety of types of route (e.g. off-road routes, cycle lanes on main roads, quiet back-road routes) a variety of locations and/or corridors (e.g. corridors into the town centre, routes to important destinations such as colleges / universities, and routes used for local trips). 1.8. The stipulated responsibilities of the contractor are approximately commensurate with project objectives, and are presented in two distinct groups in the brief. Objective A the Monitoring Review, Monitoring Regime and Monitoring Plan: Reviewing (current monitoring activity) - to review the location of existing automatic cycle counters in the six Cycling Demonstration Towns; to understand what the different data collection streams are; to establish whether they are robust enough; to identify where the gaps are. 6
The Monitoring Plan - to recommend where additional cycle counters should be; to specify a monitoring plan for each town. This should specify locations for both manual and automatic counting sites; the desired frequency of manual counts; frequency of data collection from automatic counters; how data which is already being collected as part of school and workplace travel planning can be used; any additional monitoring mechanisms at schools and workplaces, such as cycle parking counts. The Monitoring Regime - should specify a management regime to ensure that data are properly collected, validated and recorded by the local authority; ensure that the monitoring regime is comparable across the six towns. Objective B Data analysis: To assist with the local authorities for each town to ensure that effective plans are implemented for monitoring cycling mode share to schools and workplaces; to carry out regular analysis of data on overall cycle activity for each town from automatic cycle counters and manual counts, as supplied by the local authority; to report on quarterly analysis of data for each town; to oversee an annual cycle user survey in each town covering gender split, level of experience of cyclists, reasons for cycling, journey purpose, car availability and other factors as agreed with Cycling England; to report on the results to Cycling England. 1.9. The monitoring project started with the premise that in order to be fit for purpose data collected to demonstrate the effectiveness of such a programme must meet the criteria of being: drawn from a wide range of sources to ensure that multiple indicators are generated sufficiently complex to be able to ensure that the data collected is robust under examination sufficiently simple and focused to ensure that the monitoring project is not excessively expensive. 1.10. Outputs at several levels are generated from the monitoring project, as specified in the project partners tender, including: 7
regular interim reporting for the benefit of all parties concerned so that the impacts can be tracked over the programme lifespan empirical demonstration of the veracity of the overall programme at its conclusion for Cycling England detailed analysis of the relative impacts of the specific interventions applied in the Demonstration Towns a whole town overview of the success of project implementation in each of the towns individually headline figures by which the success of the programme can be reported to the media the inclusion of outputs from this programme as inputs to the work of other bodies working in related areas (e.g. physical activity). 1.11. This report represents the primary output addressing the strategic aims of the project, and delivers the commitments made under the final item of objective B and the five lattermost outputs from the bullet points listed in the original tender document and cited above. Project process 1.12. The project largely adhered to the stipulated responsibilities of the contractor (or objectives), as detailed above, achieving a greater level of attainment in some areas, but reducing the influence of other matters where evidence suggested that this was the appropriate course of action. The conduct of a review of current data streams across the six towns at the outset of the project established the nature and extent of data collection, allowed gaps in the data portfolio to be identified, and facilitated an assessment of opportunities offered by existing data. A sound understanding of the strengths, weaknesses and opportunities enabled the synthesis of a detailed monitoring plan for the Cycling Demonstration Towns, allowing the contractors to ensure that data collection was fit-for-purpose (as rigorous as possible within the 8
constraints of cost and practicality), consistent, and comparable across the six towns. 1.13. The Monitoring Regime commenced with a Review of existing bicycle, transport and other monitoring data and activities. Arising from this, Monitoring Plan Development took place. Subsequent tasks concerned the delivery of the Monitoring Plan and the collection of data. The implementation of the Monitoring Plan involved the management of data acquisition from Automatic Cycle Counts and Manual Cycle Counts, plus School Travel Surveys, Workplace Travel Surveys, Behaviour and Attitude Surveys, and Cycle Parking Counts. Data from Automatic Cycle Counts and Manual Cycle Counts were summarised quarterly. Data from each of the study elements were summarised and presented on an annual basis. This report represents the final project task: we draw all the data sources together at the end of the study and analyse trends and the impact of specific interventions in an analysis based on three years of investment. This represents an interim analysis as funding will be carried forward in each of the six locations for a further three years. Structure of report 1.14. This report seeks to avoid any lengthy exploration of the rationale for monitoring, or of the degree of compliance with the monitoring plan (or otherwise) achieved by each town. We aim to concentrate solely on the data available and our interpretation of what it tells us about the impact of the enhanced funding regimes in each of the Demonstration Towns. Following a very brief description of the methodologies used, we present the material assembled for each town. In addition to a headline change figure, we present the indicators generated based on each of the sources adopted in the towns. We also present one or more studies focusing on particular themes across the towns. Extensive appendices of additional material are available. 9
2. Methodology 2.1. In all instances established monitoring procedures and tools, procedures and tools amended in line with the monitoring plan, or new data collection tools designed specifically for the monitoring project were implemented by the local authorities concerned, and data were supplied to the monitoring team. Where data have not been supplied by particular towns for particular data items, no commentary is presented in the text of the report. Automatic cycle counters 2.2. Data are collected from a network of automatic cycle counters in each of the towns. Counters are typically inductive loop based mechanisms, collecting continuous counts of cyclists on an hourly basis. 2.3. Within the towns the distribution of the automatic counters is planned on a pragmatic basis, using existing networks of counters, and areas receiving and areas not receiving the benefits of the intervention, but fundamentally aiming to capture the majority of the cycling flow to key destinations. There is no sensible formula to determine an appropriate density of counters in a given area, rather the number of counters was based in each case on a geographical analysis of the town to create appropriate cordons and screenlines and weighing up the data requirements against costs. No weighting is applied to the data in the absence of a suitable methodology. 2.4. Count data were used to calculate the average daily counts of cycles recorded at each counter location in each month of the time series. Within this report three expressions of average are used: the median daily count (based on seven days data), the week day median daily count and the weekend day median daily count. 2.5. The change in the count of cycles over the project period was estimated using methods to gain both an adequate level of detail at a specific site but also an overall expression of change, while being suitably robust towards temporary changes such as weather. 10
2.6. To express the change at each counter the seasonal slope estimator, a non parametric method for time series displaying strong seasonality and missing data, was used. This change was then expressed as a percentage of the median daily count across the entire time series (see appendix for a detailed technical explanation and source data). The average annual change as referenced throughout this report therefore refers to the typical percentage change in the median daily count over a typical year. 2.7. The number of counts from all counters in all towns was modelled using a regression approach. Data were adjusted for town, time of year, day of week, calendar effects and missing values. Based on days with recorded counts in 2008, counts were predicted for 2005 to 2009 to enable an expression of change over the entire project period. Changes from the baseline are calculated per town and for all towns. 2.8. Although the Cycling Demonstration Town project period is from October 2005 to October 2008, the requirements of the monitoring programme are to extend the period beyond these dates, into 2005 for a baseline, and into 2009 for the post-phase 1 period. 2.9. The network of continuous automatic cycle counters is the most valuable data source we have across the Cycling Demonstration Towns, not least because these data reflect actual rather than self-reported behaviour. However, data are highly variable in terms of consistency between towns and between locations within towns. 2.10. We have little evidence of counter validation for any of the towns, although in some cases we have been made aware of problems with counter loops not completely covering the path and other issues of detection. In the absence of robust validation, we acknowledge that count data may not be a truly accurate representation of the numbers of cyclists using a route at a given location. 11
Manual counts of cyclists 2.11. Twelve-hour manual counts of cyclists have been performed in all of the towns on a quarterly basis. Count locations typically form partial cordons around central areas. In most instances, all sites are counted on the same day. As far as possible, for each quarter in subsequent years, counts are performed during the corresponding week. 2.12. The change in manual counts recorded over the course of the programme was estimated using the non-parametric slope estimator, as described for the automatic counter data, applying it to the quarterly rather than daily counts. 2.13. Manual count data are most valuable in that manual counts can be performed in locations not suitable for the installation of automatic cycle counters and as such can provide a more complete picture of movement to and from central areas. These data can provide a broad picture of movement into and out of partial cordons on a typical day in each quarter. Counts are performed only four times a year, and as such, cannot be compared against a baseline in the early stages of the programme but become increasingly valuable as the time series of data accumulates. 2.14. Cordon coverage with manual counts varies greatly between towns. The completeness of the cordon influences the extent to which manual count data can be relied upon to provide a true reflection of movement into and out of town centres. School travel surveys 2.15. Three sources of data on travel to school are considered: the Pupil Level Annual School Census (PLASC), Bike It hands-up surveys; and local authority hands-up surveys. 12
Pupil Level Annual School Census 2.16. Data concerning the usual mode of travel to school is collected via PLASC. Schools with travel plans are obliged to provide data on mode of travel, whilst the question is optional for schools without travel plans. 2.17. We have several concerns about the use of PLASC data to make an assessment of change in mode of travel to school over time. The census asks about usual mode of travel. This fails to recognise that some children may cycle to school less frequently than they use other modes. The guidance on data collection suggests that data may be collected from either parents or children. The fact that the method of data collection can be variable between years limits its reliability as a means of assessing change in mode of travel over time. The guidance suggests collection of data in the autumn. Whilst the Department for Transport in their guidance recognise that mode of travel is likely to be influenced by season, the collection of data so early in the academic year may not provide a true reflection of travel across the year. 2.18. Data extracted from the Pupil Level Annual School Census (PLASC) for each of the towns are included in this report. The school travel question was introduced to PLASC in 2007. The data does not therefore represent a pre-project baseline. Given our reservations concerning data quality, we have not performed any detailed analysis of this data and have instead only cited the percentage of children stating to travel to school by cycle at each survey point. 2.19. In the case of Brighton and Hove, Derby and Darlington, data were taken directly from the PLASC results for each local authority. In the case of Aylesbury, Exeter and Lancaster with Morecambe, the relevant subset of data reported for Buckinghamshire, Devon and Lancashire respectively were extracted from PLASC. Bike It hands-up surveys 2.20. School travel data have been collected via hands-up surveys performed by Bike It officers active in schools in the Cycling 13
Demonstration Towns. All of the towns had a Bike It officer for the duration of the Demonstration Town project. A total of 129 schools were engaged in the Bike It programme during the Cycling Demonstration Town project. 2.21. In any given year, Bike It hands-up pre-surveys are usually performed during September, prior to intervention. Post-surveys are performed in July at the end of the summer term. In some cases, a further survey is performed at the end of the summer term of the second year of engagement. Bike It officers may survey the whole school, or the target age group. In either case, the same group of children are surveyed at the beginning and end of the first academic year of engagement. 2.22. In the surveys children are asked about their actual and preferred modes of travel to school, and their frequency of cycling. We acknowledge that there are limitations in comparing pre-survey data collected in September with post-survey data collected in July, where some seasonal influence on levels of cycling may be expected. This is addressed to some extent in schools where a second follow up survey is performed. 2.23. Data from schools beginning Bike It in the 2006/07 and 2007/08 academic years are reported herein. Data are included for 60 schools with at least a pre- and post-survey during the first year of engagement. Pre- and post-survey data are pooled across towns in aggregated analysis of Bike It data. Local authority hands-up surveys 2.24. Only in Darlington did data collection via annual local authority handsup surveys (as distinct from PLASC) continue throughout the programme. Data are included in the report from the 2004/05 academic year onwards. Behaviour and attitude surveys 2.25. Surveys concerning levels of cycling and opinions about cycling were distributed in several of the towns. The distribution mechanism used by 14
each town varies, and the approach used in each case is described in the appendix. 2.26. Where two iterations of the survey were performed during the programme, these are compared in the report. In towns where only a single iteration of a study was performed, these results are summarised in the appendix to this report. 2.27. Multiple iterations of behaviour and attitude surveys were performed in four of the six towns, but there was in some cases variability between delivery and format between iterations, and none of the towns had representative samples. We acknowledge that such variations limit the degree to which these surveys contribute to understanding the impact of the programme as a whole. However, behaviour and attitude surveys are locally valuable in understanding levels of cycling during the programme period in the towns where they have been delivered. Counts of parked bikes 2.28. Counts of parked bikes have been performed in several of the towns. The data collected were analysed to determine the number of bikes parked throughout the day the concentration of parking, and the length of time parked the duration. A beat based approach is used in each case, following the model for counts of parked cars. More detail is presented in the relevant appendix. 2.29. Counts of parked bikes a performed on a single day and are thus highly influenced by factors such as the weather. Workplace travel surveys 2.30. Surveys of workplace travel have been performed in several towns. The exact format of the survey varies between towns. Only in Exeter have two or more surveys been performed, and these are compared in the report. Where only a single iteration has been performed, the results of the survey are summarised in the appendix to this report. 15
Accident data 2.31. Data concerning accident rates (generally referred to as incident rates throughout the report) in some of the Cycling Demonstration Towns were extracted from the STATS19 record. Incident data for 2003-2005 and 2006-2008 were compared and assessed for significant change using the Chi square test. Travel Behaviour Surveys 2.32. In some cases, travel behaviour surveys have been conducted in towns through other projects running alongside the Cycling Demonstration Town. Where this is the case, and where data have been made available, relevant data are summarised within the report. Attributing change to the Cycling Demonstration Towns programme 2.33. In three of the towns, other programmes were active at the same time as the Cycling Demonstration Towns programme TravelSmart in Lancaster with Morecambe and Exeter, and the Sustainable Travel Demonstration Town (incorporating individualised travel marketing) programme in Darlington. 2.34. Attributing any change observed in the above data sources to the Cycling Demonstration Towns programme is challenging in itself. This becomes especially complicated when other interventions, the outcomes of which could reasonably include increases in levels of cycling, are active in the town at the same time. 16
3. Summary of overall findings 3.1. In this chapter, we present the overall findings of analysis of data collected across the Cycling Demonstration Towns. Data collected in each individual town are presented in the sections of the report following this overview. 3.2. For the purposes of aggregating data sources across all towns, measures of whole town activity are defined as those not relating to specific sectors of the population, and include automatic cycle counter data, manual counts of cyclists, counts of parked bikes and town level travel behaviour surveys. Data sources specific to population sectors include school and workplace travel data. Automatic counter data 3.3. All towns showed an increase in cycling activity, as measured by automatic cycle counters. The change across the towns for the period 2006-2009 ranged from +2.4% to +56.8%. The change in cycling activity in each town, and the average change across all towns is presented in Figure 3.1. 3.4. The percentage change in counts recorded over time projected to the end of December 2009 and the median daily count across all counters in each town are presented in Figure 3.2. 17
Figure 3.1: Percentage change in counts recorded by automatic cycle counters in each year of the programme against a 2005 baseline. Change in counts is projected to the end of 2009 using data collected between January 2006 and March 2009. 160 Percentage change relative to baseline 150 140 130 120 110 100 90 2005 2006 2007 2008 2009 Aylesbury Brighton and Hove Darlington Derby Exeter Lancaster with Morecambe All 3.5. The average annual growth in cycle counts relative to baseline data collected in 2005 (2006 in the case of Brighton and Hove) is +6.2%. For most towns, there is a consistent increase from year to year, with the exception of Aylesbury and Derby. 3.6. For Aylesbury, cycle counts increase each year to 2008, but decrease in 2009. This may be linked to disruption to one of the most well used cycle routes in Aylesbury due to infrastructure construction work during 2008. 3.7. For Derby, cycle count data collected in the first year of the programme indicated a decrease in counts relative to the baseline. However, counts increase in all subsequent years. Whilst we cannot speculate regarding the cause of this decline in the early phase of the project, automatic count data point towards an increase over time. 18
Figure 3.2: Percentage change in counts recorded by automatic cycle counters in each year of the programme against a 2005 baseline. Values above the bars indicate the average daily count across all counters and across the whole time series. 70 60 79 % growth in cycle counts 50 40 30 20 111 386 103 136 10 79 98 0 All Aylesbury Brighton and Hove Darlington Derby Exeter Lancaster with Morecambe 3.8. Analysis has been performed on data collected from a total of 104 counters across the towns. The change in counts of cycles recorded at each location are summarised in Table 3.1. Table 3.1: Number of automatic cycle counters and range of annual average change in counts recorded Town Total number of counters Counters with positive annual change (range) Counters with negative annual change (range) Aylesbury 12 8 (+1% - +13%) 4 (-3% - -13%) Brighton and Hove a 13 12 (+2% - +19%) 0 Darlington a 14 10 (+8% - +38%) 3 (-2% - -9%) Derby 15 14 (+2% - +17%) 1 (-2%) Exeter 27 20 (+4% - +24%) 7 (-1% - -3%) Lancaster with Morecambe 23 17 (+1% - +19%) 6 (-1% - -11%) All 104 81 (+1% - +38%) 21 (-1% - -13%) a 0% annual change at one counter 19
3.9. Of the total number of counters for which adequate data were available for analysis, the average annual change in the daily median count was positive for 78% of counters and negative for 20%. There was no change over time for 2% of counters. Manual count data 3.10. Manual count data collected across the towns indicate a mixed picture with respect to growth in cycling across the programme period. 3.11. Manual count data were collected from a total of eight partial cordons or screenlines: one each in Aylesbury, Brighton and Hove, Darlington and Derby; two each in Lancaster with Morecambe and Exeter. 3.12. Four partial count cordons indicated an increase in cycling activity (as represented by manual counts) of between +6% and +13% per year. Four partial count cordons indicated a decrease in cycling activity of between -2% and -5% per year. Counts of parked bikes 3.13. Counts of parked bikes data were provided by four towns. Amongst these, three found in increase in parked bikes, ranging from +8% to +32%, whilst the fourth found a decline of -9%. Household travel surveys 3.14. Comparable iterations of household travel surveys were performed in two of the towns during the project period. Both suggest an increase in cycling at the town level. In Darlington, cycling increased by +120% between 2004 and 2008 (from 15 to 33 trips per person per year). In Lancaster, the relative change in trips where cycling was the main mode of transport was +69%. Changes in cycling amongst children 3.15. Based on PLASC data collected for all schools in the towns in the 2006/07 and 2007/08 academic years, the proportion of children reporting that they usually cycle to school increased from 1.9% to 2.2% between the survey dates. 20
3.16. Pre and post survey data are available for a total of 60 schools engaged in Bike It. The proportion of children never cycling to school calculated from pooled pre-survey data (collected in either September 2006 or September 2007) was 79%, compared to 56% of children in the pooled post-survey data (collected in either July 2007 or July 2008). The proportion of pupils cycling to school at least once a week increased from 12% in the pre-survey to 26% in the post-survey (based on pooled data). 3.17. Data collected from those schools where a second follow up survey was performed 12 months after the first post survey suggests that, broadly, levels of cycling are maintained. Pooling data across all schools where three iterations of the survey were performed, the proportion of pupils reporting never to cycle to school fell from 81% in the pre-survey to 55% in the mid survey, remaining at 55% in the post survey. The proportion of children surveyed in these schools cycling to school at least once a week increased from 9% in the pre-survey, increasing to 26% in the mid survey and declining slightly to 25% in the post survey. 3.18. In terms of modal share, the proportion children surveyed reporting to have cycled to school on the day of the survey increased from 4%, based on pooled pre-survey data, to 11% in post-surveys. The proportion of children travelling to school by car on the day of the survey decreased from 39% in the pre-survey to 38% in the post-survey. 3.19. Approximately half of the observed increase in cycling is the result of a decrease in travel to school by car or bus, and half due to a decrease in travel to school by walking. The average %-point change in mode to travel on the day of the survey between pooled data from pre- and postsurveys in Bike It schools are presented in Figure 3.3. 21
Figure 3.3: %-point change in children stating to travel by each mode between preand post-surveys in Bike It schools (2006/07 and 2007/08 data pooled for pre- and post-surveys) 8 6 percentage point change 4 2 0-2 -4-6 Total car Total walk Total bus Total cycle Total train/other Changes in cycling to work 3.20. A comprehensive survey of mode of travel to work was performed only in Exeter. Annual survey data suggest in increase in modal share of 0.4%-point (from 8.5% to 8.9%) between 2006 and 2008. 3.21. Behaviour and attitude surveys performed during the project included questions on cycling to work, although the exact format of these surveys varied greatly between towns, and sometimes between iterations in the same town. 3.22. In Brighton and Hove, over 20% of respondents claimed to cycle to work in surveys performed in 2006 and 2008. In Derby, the proportion of respondents reporting that they cycle to work several times a week increased from 21% to 47% between 2006 and 2009. In Exeter, the proportion of respondents reporting to cycle to work several times a week increased from 15% to 16% between 2007 and 2009. In Lancaster, the proportion of respondents cycling to work several times a week was upwards of 40% in all survey iterations. 22
3.23. The range of surveys performed across the towns suggests an overall increase in commuting to work by cycle, although this remains a tentative conclusion given the variability in survey delivery. In several instances, data collected by cycle counters located close to key workplaces show an increase in cyclists counted at key commuting times (explored elsewhere in this report). 23
4. Aylesbury Summary The overall change in levels of cycling activity during the Cycling Demonstration Town project period, based on automatic count data, was +2.4% The annual average change in the number of cyclists crossing a partial manual count cordon around Aylesbury town centre was -4% School travel data show an increase in cycling in primary and secondary schools, and in Bike It schools Counts of parked bikes show a steady increase in the number of cycles parked at the station during the project period Data source Data included Result Positive / negative trend WHOLE TOWN ACTIVITY Automatic cycle counts Manual counts Counts of parked bikes CHILD POPULATION (<16) School Census (PLASC) data Hands up surveys of Bike It schools Hands up surveys of Bike It schools Figures relative to 2005 baseline Quarterly counts on a partial cordon around town centre, starting in Q3 2006: Estimated annual rate of change Annual counts of parked bikes at railway station (carried out in June, 2003 to 2009; reported relative to 2005 baseline; total spaces available =96) Annual pupil-level survey, all schools, pooled data for 2006/07 and 2007/08 academic years proportion of pupils for which cycling is the usual mode of travel to school Surveys of Bike It schools, pooled data from baseline surveys (in September 2006/2007) and ex-post surveys (in July 2007/2008) proportion of pupils cycling to school either every day or once or twice a week Surveys of Bike It schools, pooled data, change in cycling mode share between baseline surveys (in September 2006/2007) and ex-post surveys (in July 2007/2008) proportion of pupils for which cycling is the mode of travel to school on day of survey a Not significant (p=0.055) +2.4% a relative to baseline -4% per year +25% (from 51 to 64) +7%or +0.1%- points (from 1.5% to 1.6%) +234% or +20.4%- points (from 8.7% to 29.1%) +266% or +8.5%- points (from 3.2% to 11.7%) Positive Negative Positive Positive Positive Positive 24
Data availability in Aylesbury 4.1. During the Cycling Demonstration Town project, the following methods were used to monitor levels of cycling activity in Aylesbury: continuous automatic cycle counters manual counts of cyclists (quarterly) school travel surveys (Bike It and PLASC) counts of parked bikes at Aylesbury railway station. Continuous automatic cycle counters 4.2. During the Cycling Demonstration Towns project, data have been collected from 16 automatic cycle counters in Aylesbury. The locations of the counters are indicated in Map 1 appended to this report. However, the data sequence is only of sufficient length for an estimate to be made of change in count recorded over the project period at 12 of these sites. 4.3. The overall change in counts of cycles in Aylesbury relative to the 2005 baseline is +2.4%. 4.4. The construction of major infrastructure in the centre of Aylesbury during 2008 caused disruption to one of the busiest cycle routes in the town. This make have contributed to the apparent decline in growth of counts of cyclists observed between 2008 and 2009. Table 4.1: Change in cycle count in Aylesbury relative to 2005 baseline 2005 2006 2007 2008 2009 Change on 2005 baseline 100.0 101.6 109.4 110.9 102.4 4.5. The annual percentage change for each count location in Aylesbury is presented in Table 4.2 and in Map 2. Eight of the sites are located on Gemstone Routes. 25
Table 4.2: Aylesbury continuous count data - annual percentage change Counter Median Annual % change daily count 7-day 5-day w/e day Bicester Road North (Ruby Way) 113 +3% +1% 0% Bicester Road South (Ruby Way) 109 +10% +9% +3% Bierton Road (Sapphire Way) 61 +8% +7% +12% Vale Park Drive (Sapphire Way) 48-6% -5% -8% Mill Way (Pearl Way) 85 +8% +8% +9% Oxford Road (Cold Harbour) (Pebble Way) 73-3% -1% +3% Thame Road (California Brook) (Pebble Way) 229-13% -10% -9% Wendover Road Cycle Path (Amber Way) 96 +1% +2% +4% Elm Farm Underpass 135 +5% +5% +12% Griffin Lane (east side) 52 +4% +3% -6% Griffin Lane (west side) 52 +13% +13% -6% Manor Road 21-5% -4% +6% 4.6. The counters show a mixed picture of levels of change in cycling activity across Aylesbury. Eight sites exhibit an increase in levels of activity in the 7-day median daily count over the project period, and four exhibit a decrease, including the most heavily used of all of the sites. We postulate that the decrease observed in counts recorded on the Pebble Way is linked to disruption on the route close to the town centre during the construction of the Bourg Walk which began in early 2008, explored further in paragraph 4.8. The decrease in the count recorded on the Sapphire Way at Vale Park Drive is reportedly linked to the bypassing of the counter by cyclists opting to continue their journey into the centre of Aylesbury on an alternative route. 26
Manual classified counts 4.7. Manual cycle counts of 12-hour duration are performed quarterly at nine locations forming a partial cordon around the centre of Aylesbury, as indicated in Map 1. The counts are conducted over two days. The same group of sites is counted on the corresponding day in each quarter. The total count of cyclists recorded entering and leaving the cordon in each quarter of each year are presented in Figure 4.1. The count sequence shows an annual decrease of around -4%. Figure 4.1: Total count of cyclists recorded entering and leaving a partial cordon around the centre of Aylesbury 1200 1150 12-hour count of cyclists. 1000 800 600 400 200 555 619 512 527 284 260 523 461 547 556 438 459 280 289 391 434 519 471 527 544 1100 1050 1000 950 900 Estimated change in count. 0 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 850 2006 2007 2008 Total number of cyclists leaving cordon during 12 hour count period Total number of cyclists entering cordon during 12 hour count period Estimated change in total 12-hour count Extended discussion of count material for Aylesbury 4.8. Analysis of automatic cycle counters in Aylesbury shows an increase in counts against the 2005 baseline of +10.9% to the end of 2008, and +2.4% using data to the end of March 2009 (Table 4.1). Considering the individual automatic cycle counters (Table 4.2), the average annual percentage change is negative for four counters. Two of these (Thame Road California Brook and Oxford Road (Cold Harbour)) are located on 27
the Pebble Way. The Bourg Walk, which links several routes, including the Pebble Way, to the centre of Aylesbury, opened in April 2009. Due to its location, it is very likely that construction of the Bourg Walk caused disruption to cyclists accessing the town centre from the Pebble Way. This is possibly reflected by the downturn in numbers of cyclists recorded by the counters on this route. Based on an aggregation of all nine manual count sites, the partial manual count cordon around the centre of Aylesbury also suggests a decline the number of cyclists counted over time. 4.9. In order to explore these issues further, a more detailed analysis of both automatic and manual count data was undertaken. This shows that the annual average count at both counters located on the Pebble Way declines over the time series considered in the analysis (-3% and -13% for the counters located at Oxford Road (Cold Harbour) and Thame Road California Brook, respectively). The daily median count over the whole time series is 73 for the Oxford Road site and 229 for the Thame Road site. 4.10. A simple analysis was undertaken to calculate the percentage change between the same month in subsequent years. This proved particularly insightful for the Thame Road site. Sufficient data are available to calculate a median daily count for 10 months in 2007 and the same months in 2008. The median change in the daily median count across all available months was -21%. The decrease in counts between 2007 and 2008 is particularly marked from mid 2008 onwards. The same analysis was performed comparing six months in 2006 and the same six months in 2007. The median change in the daily median count across all available months was 2%. Percentage change between months in each pair of years are presented in Figure 4.2. 28
Figure 4.2: Percentage change in daily median count recorded at Thame Road California Brook for paired months in 2006, 2007 and 2008 20 % change in median daily count. 10 0-10 -20-30 -40 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec % change between 2006 and 2007 % change between 2007 and 2008 4.11. This analysis suggests that flows of cyclists on one of the most heavily used routes in Aylesbury have been influenced by infrastructural work through 2008. Analysis of future data from these count locations is necessary before any conclusion can be drawn with respect to changes in levels of cycling following the opening of infrastructure in April 2009. School travel surveys Bike It 4.12. In schools where Bike It began in 2006, the number of pupils surveyed who never cycle to school fell from 84% to 51% between the preproject hands-up survey performed in September 2006 and the follow up survey performed in July 2007. The percentage of pupils surveyed reporting that they cycle to school everyday or once or twice a week increased from 6% to 32% over the same period. 29
4.13. A third survey was performed in three schools in July 2008. Using data from only these schools, the percentage of pupils surveyed reporting that they cycle everyday or once or twice a week was 3% in the pre-project survey, 29% in the mid survey (July 2007) and 20% in the post-survey (July 2007). The percentage of pupils surveyed reporting that they never cycle to school was 90% in the pre-project survey, 60% in the mid survey (July 2007) and 69% in the post-survey (July 2007). 4.14. In schools where Bike It began in 2007, the percentage of pupils surveyed stating never to cycle to school decreased from 70% in the pre-project survey performed in September 2007 to 67% in the follow up survey performed in July 2008. The overall percentage of those surveyed reporting that they cycle to school everyday or once or twice a week did not change between the two survey dates (20%). 4.15. The response of pupils to the question how did you travel to school today? are summarised in Table 4.3. Data are reported for the pre survey and the post survey following the first year of engagement. Table 4.3: Percentage of pupils travelling by each mode on the day of the survey Percentage travelling by mode on day of survey a Survey date n Car Walk Cycle Other Aylesbury Pre 2006/07 2,832 37% 50% 3% 10% All towns Pre 2006/07 10,326 40% 48% 4% 8% Aylesbury Post 2006/07 2,007 39% 47% 12% 2% All towns Post 2006/07 8,662 39% 46% 10% 4% Aylesbury Pre 2007/08 574 43% 38% 5% 14% All towns Pre 2007/08 4,570 37% 52% 4% 7% Aylesbury Post 2007/08 656 40% 27% 12% 21% All towns Post 2007/08 4,538 34% 44% 14% 9% a Where percentages do not sum to 100 this is due to rounding 30