Currently in London, 30% of bike journeys are taken by women. But for London to truly become a bicycle friendly city, it needs to be inclusive, and cycling needs to become a population-wide activity that includes large numbers of children, older adults, and women. There is a strong positive relationship between overall bicycle mode share of travel and female participation in cycling (Garrard, Handy and Dill, 2012), which is why we wanted to our part today to help call out the gender gap in cycling for International Women’s Day and #choosetochallenge city planners to take women’s needs into account in the planning of cycle networks.
We believe that more research to understand this relationship and what can be done to improve both bicycle mode share and gender equity in cycling is needed. While previous studies have been valuable in pointing to women’s stated preference for dedicated cycle routes, we wanted to add to this by providing new insights that uncover actual routes choices women make compared to men’s, but also what their experience was like on that route in terms of swerving/braking and road surface. To do this, we analysed data from our London community, which includes 81 female cyclists and 751 male cyclists over an 18 month period in London.
Our study revealed that female cyclists in London are choosing to travel on dedicated cycle routes in the UK capital, rather than roads, often at the expense of longer journeys. It also found that women tended to experience less braking and swerving on their journeys, and experienced a higher road surface quality on these routes.
Figures 1 and 2 show that women cyclists consistently favour dedicated cycle routes compared to men. The study also found that women tended to experience less braking and swerving on their journeys, and experienced a higher road surface quality on these routes (See Figures 3, 4 and 5 respectively).
Figure 1: Journeys made by female and male cyclists in the Waterloo area, with the cycle routes overlaid in dotted lines. It is clear to see that female cyclists favour cycle routes.
Figure 2: Journeys made by female and male cyclists in the Elephant and Castle area, with the cycle routes overlaid in dotted lines. It is clear to see that female cyclists favour cycle routes.
Figure 3: Logarithmic scale showing women that females spend less time on rough road surface, relative to male cyclists.
Figure 4: Logarithmic scale showing women that females spend less time braking relative to male cyclists.
Figure 5: Logarithmic scale showing women that females spend less time swerving relative to male cyclists.
HOW DID WE GATHER THE DATA?
The data See.Sense analysed in London was gathered from See.Sense’s award-winning, daylight visible bike lights which use advanced sensor technology to monitor the environment while a cyclist is riding, taking 800 readings a second from the device.
They help to make cycling safer for cyclists, by flashing faster and more brightly at moments of potential risk, while gathering information on road surface, braking, swerving, collisions, and more. The unique, real time data our lights collect can not only give insights into cyclist behaviour, but also precisely identify the experience of the cyclist, including swerving, braking, collisions, as well as road conditions in specific areas. To share anonymised ride insights, cyclists using the lights simply join the See.Sense community in the company’s free app and optionally create a profile which includes gender. Users can opt in or out of data sharing, but the majority of users opt in.
The project analysed data from 81 female cyclists and 751 male cyclists over an 18 month period in London. We recognise it would have been ideal to have had more women involved but as this was not a funded project, we could only analyse data from our customers who have opted into to share their anonymised data insights. It is possible to deploy our lights to larger numbers of women, this was successfully done in a recent funded project in Dublin for example that had 45% women.
The cycle routes were identified by using Open Street Maps, which is crowdsourced reporting of location of routes.
We would like to see planners consider gender data when planning cycling networks. The type of cycling infrastructure is important, but also the location of it in order to serve the type of journeys that women are making. Better data on women’s needs could help to better inform cycling network design at a time when London is devising ways to encourage more women, and marginalised groups, to cycle.
We plan to share the insights gained from this project with Transport for London. It is our hope that these insights will help encourage cities everywhere to take evidence-based actions to enhance people’s daily lives.
What are your thoughts on this research? Would you like to see city planners take women’s cycling data into account. Let us know what you think - email us at firstname.lastname@example.org or tweet us.
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