Mode share targets for active transport are always a bone of contention when preparing a transport strategy. The targets for active mode share in the Queensland Cycle Strategy (2011 - 2021) and Connecting SEQ 2031 are often dismissed as unrealistic - nice ideas but not possible.
Part of the problem is that there is very little empirical evidence that is available to test active transport mode share targets. Mode share targets are most often tested/verified using a strategic transport model. However, none of the models we typically use in transport planning include active transport in the trip choice algorithm. Therefore we cannot use modelling alone to develop mode share projections. There is a need for a method to empirically develop realistic mode share targets.
One way is through citing evidence from other jurisdictions. Citing city-wide active transport mode share for world's best practice (like the Netherlands) is unlikely to win much support from anyone other than an active transport disciple. There is too much that is different between the structure of cities and the management of our networks for this to be a realistic comparison.
However, what is useful is comparing active transport mode share for different distance bands (trips less than 1km for walking mode share, and those less than 3km and 5km for cycling mode share). That way the structure of the city doesn't cloud the mode share argument. Citing Australian or American good practice active mode share for short trips as the target to aspire to can sometimes make a significant difference to active transport mode share for the city or region as a whole. The argument that this is not Europe can then be removed from the discussion. What is essential is that the strategic modelling incorporate these assumptions into their future modelling projections or the model will not register this change and will over-estimate the number of vehicle trips for short trips.
But the argument about active transport mode share targets is often due to the fact that it is very difficult to visualise a 6%, 3% or 1% cycling mode share for all day trips. We need to translate this from a percentage into a behaviour. A useful tool here is the household travel surveys (HTS) - an extremely valuable resource for transport planning and strategy.
Looking at an arbitrary example - Rockhampton. With a current cycling mode share of 1% what does this mean in behaviours. According to the HTS a resident of Rockhampton and Yeppoon make on average 3.4 trips per weekday. That translates into 17 trips per person for a typical work week. There are an average of 2.8 residents per household in Rockhampton. That makes 48 trips per household for a typical week (excluding weekends).
With an active mode share of 1% that equates to each resident making a one-way cycle trip every six weeks. Or each household making one return cycling trip a month (note that your daily commute to and from work is two trips, not one). This trip could be a recreational trip every two weeks (going for a bike ride = 1 trip), a trip to the shops once a month, or the kid cycling to school one day a month. These trips make up almost 70% of the trips made in a typical work week.
3% cycling mode share means every household makes 3 return cycle trips a month.
6% cycling mode share means every household makes 6 return cycle trips a month.
10% cycling mode share means one person in every household rides their bike to work/school/shops every day for half of the month.
When I was young most of us cycled to and from school. When we visited friends we walked or cycled. We rarely were driven anywhere. The National Cycle Strategy says that half of Australian households own one or more bicycles. If one resident of every one of these households were empowered to use their bicycle to make any trip at least once a week we would have more than a 3% daily cycling mode share.
When mode share is translated into behaviours in this way the targets seem so much more achievable.
1 comment:
Athol, I completely agree that we need to reshape the way we look at targets. For me it is part of returning strategy and policy as useful and relevant tools in achieving real, value for money outcomes for people. This is why I think that we need to take it further and look at function and geographically based targets that might be harder to measure and forecast but can be more readily translated from policy to plan. For example, I believe that we should be aiming for a 40-50% active transport share for journeys to work or school of less than 3km. I think that technology and big data collection can help us measure these if we can arrive at meaningful policy goals and target criteria rather than the old meaningless global pictures.
Also, as you know, models ain't models and some do active much better than others. We need out transport analysts and forecasters to be more open to alternative models that aren't so blindingly focused on motorised modes. Either that or we should be demanding that the "preferred" platform is brought up to speed.
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