TravelWise Summerside: Sustainable Mobility Summit November 6, 2012 TravelWise Summerside:  How to Shift Transportation Choices in a Suburban Context Who I am Presenting on behalf of Jason and Steve Allison Miller, MCP, MCIP, RPP TDM Coordinator City of London Dr. Jason Gilliland & Stephen Fitzpatrick Human Environments Analysis Laboratory Department of Geography Western University

The EcoMobility Project The City of London engaged Londoners in adopting sustainable transportation in two neighbourhoods: Where is London TC funded 3 year project until end of 2011 Workforce Mobility Project (mainly employers) TravelWise Summerside (mainly residential)

Summerside Context We wanted to answer: How we work within a suburban context? Summerside is just one of many newly-built primarily residential neighbourhoods. Many people live in a similar context. To situate you: there is a commercial plaza right on the edge of the neighbourhood more stores on the other side of a major arterial/highway essentially and our city-wide multi-use pathway systems is accessible a km away from the northern edge of the neighbourhood. In this presentation, I will touch on our outreach activities but the focus will be on measurement – what worked and what didn’t work so well.

Key Activities Understand residents’ choices Promote short trips Determine behaviour change Little to no infrastructure changes

Marketing and Outreach Challenge Engage residents in a new development Solution Work with established community groups Tap into existing resources

Marketing and Outreach Tools Branding Maps (and other items we already had)

Special Events

Benefits wheel Delivered to all households, handed out at Community Church event and distributed through Homebuilders to potential home buyers. Front

Back Separated neigh. into 4 zones and used the midpoint for calculations Brought some

Newsletters: this was our closing piece this fall for residents to thank them for participating in the program and remind them how to keep it up. Also good for new residents to the neighbourhood.

Measurement Challenge Data Collection Methodology Gauging residents’ transportation choices Data Collection Methodology Test new forms of data collection Partner with University Test “new” counting technologies Run household phone surveys

 SOV – 84.5%   SOV – 65.3%  Baseline Mode Share  Bikes – 0.2%  Summerside Autumn 2009 City-Wide Winter 2010  SOV – 84.5%  Carpool – 14.8%  Bikes – 0.2%  Pedestrians – 0.2%  SOV – 65.3%  Carpool – 13.8%  Bikes – 0.5%  Pedestrians – 7.6% Started small. As a test, counts were conducted at 3 key entrances to the neighbourhood. Stretched the concept of our traditional counting procedure using boards to include vehicle occupancy. Conducting these counts lead us to notice where people were walking (a.k.a., walkway connecting to commercial plaza) and that residents were driving to the corner store (which is in the neighbourhood). So this showed opportunities to shift some short trips to active modes.

Baseline Walkway Counts Baseline Count for Walkway Saturday November 7, 2009 Southbound from Commercial Plaza 25 5    Includes 2 time periods: 10 a.m. to noon and 2 p.m. to 4 p.m. on a Saturday! Good example of the difficulty in getting colleagues with expertise in traditional counts to re-focus to capture “new” modes. Had the fellow who normally drives to the location and sits in his car with the board ticking off vehicles and sometimes vehicle class instead capture A.T.    29 9 Northbound from Neighbourhood

Baseline Counts Spring 2010 covered the neighbourhood with 12 students at 10 separate locations (intersections and walkways) to count and determine movements. We were there on two weekdays and one Saturday: captured mornings, afternoons, and weekday evenings. What we learned: It was resource intensive, there was training involved, boring work. Difficult to use this data and present it in a friendly way. Made the calculated decision not to conduct similar followup counts so that we could put our limited resources into promotion and incentive activities. Instead, we decided to repeat the neighbourhood counts this coming summer (2013). Advantage is that we are going back a few years later and can gauge if the change observed in the surveys has been sustained.

Automatic Counters Tried EcoCounter in two locations: Walkway into the adjacent commercial plaza (infrared counter) Bridge that crosses the Thames River to connect the area to the city-wide pathway system (infrared counter and a bike loop) Unfortunately came right at the end of the official project timeframe

Results: Bike Counts Location at the Bridge. Represents the bike loop data only. The infrared counter was vandalized. The other one was improperly installed at first, so it had to be removed and re-installed. Point is that colleagues loved working with new equipment and playing around with the data.

Results: Bike Counts

2010: Survey Results Almost 9 out of 10 residents who work outside the home drive to work. We also gathered data through a baseline survey conducted early summer 2010 of residents transportation habits, impressions of transportation options in their neighbourhood, and physical activity levels. It had a 48% household response rate. The majority of residents drove to work/school. Likewise, the majority of respondents did not think stores were within walking/cycling distance of their home. About 2 out of 3 residents do not think stores are within walking or biking distance from home

Results: Shared with Residents We shared the results with residents in a straightforward, easy-to-read format.

Follow-Up: Results Achieved Proportion or residents who walked to store in previous week increased from 29-41%! (*statistically significant, p<0.05) * The novel aspect of this study is that we repeated the phone survey one year later, after the initiatives. By comparing the follow-up results with the baseline results, we could test the effectiveness of the intervention. Our results were satisfying: we saw modest but statistically significant differences in responses to key questions. For example, the proportion of respondents who had walked to a store in the past 7 days rose from 29% to 41%, and the proportion of respondents who biked to a store in the past 7 days rose from 12% to 25%. (The follow up survey was conducted in Fall 2011. It had a 41% household response rate.) Proportion or residents who biked to store in previous week increased from 12-25%! (*statistically significant, p<0.05) *

Follow-Up: Results Achieved Residents who received our info package were more likely to walk or bike to the nearby commercial plaza (*statistically significant, p<0.05) Residents who received our info package were less likely to think area traffic made it unpleasant to walk (*statistically significant, p<0.01)

Results Achieved Targets Results 20% household participation rate 3% mode shift from SOVs 3% reduction in GHG and CACs ------------------------------------------------------- 3% reduction in household fuel use 41% household participation rate 16% mode shift from SOVs 7% reductions in GHGs, CACs, and household fuel use. ---------------------------------------------------- Based on UTEC: 690 tonnes CO2 emissions avoided 1070 kg of NOx, 10 kg of SO2, 815 kg of VOC, and 20 kg of PM2.5 Approx. 306,000L of fuel savings a year. Assuming the surveyees were honest…Overall during the project we saw: 41% household participation rate (based on % reporting walking to a store in the past 7 days in the final phone survey) 16% mode shift from SOVs (based on decrease in % reporting SOV to work or school in final phone survey) 7% reductions in GHGs, CACs, and household fuel use. -------------------------------------------------------------------------------- Based on avoided vkts, and assumed 40% of gasoline used is E10 blend (using UTEC): 690 tonnes CO2 emissions avoided 1070 kg of NOx, 10 kg of SO2, 815 kg of VOC, and 20 kg of PM2.5 Approx. 306,000L of fuel savings a year.

Other Benefits Achieved Community engagement Tied into other initiatives: Strengthening Neighbourhoods Strategy Smart Moves (Transportation Master Plan) Our Street Car Free Day Walk to Shop

Lessons Learned Relationship Building Counting equipment got Engagement takes time Relationship Building Counting equipment got colleagues excited! Methodology is repeatable It took longer than expected to figure out who the established neighbourhood players were. Let alone engaging residents. 2. Invaluable - these have been sustained beyond the project timeframe 3. This test of the Eco Counter equipment has led our Transportation Planning (Bicycle Program) and Parks Planning (pathway development) installing an additional 6 bike loops and 8 ped/bike counters in 13 on and off-road locations. 4. With appropriate resources, priorities, and economic climate (which we don’t currently have in London) components of this project are repeatable and worth the effort. Key Learning: People in more suburban locations do want to be active. Many already walk a lot for exercise. They just need some help figuring out that walking or cycling with purpose is even better.

Questions / Comments Allison Miller City of London AMiller@london.ca Dr. Jason Gilliland Western University jgillila@uwo.ca