Due to its position as a global economic hub home to thousands of large employers, combined with its strong commitments to reduce CO2 emissions, London is a city in which cycling is often in the spotlight. This has been especially true over the last two years, as cycling has soared in popularity in the city with ‘record numbers’ getting on the saddle. Consequently, having data on how cyclists are moving in the city is more important than ever. See.Sense has undertaken several projects in London in recent years, working with employers, fleet operators and public bodies to provide data insights on cycling in the city.
One of our most innovative projects in London was conducted in partnership with Active City Network, a city of London based employer network represented by over 20 employers in the Square Mile.
The project ran from April to June 2019, with the aim of gathering data insights that would enable the Active City Network to better understand the experiences of cyclists in London, which would subsequently help ACN to more effectively promote an environment that encourages safer streets and active lifestyles. Subsidised See.Sense lights were provided to participants, who in return agreed to share anonymised ride insights. These ride insights were made possible through the patented AI-sensor technology in See.Sense lights, which monitor the rider’s environment up to 800 times per second, enabling situational awareness around the rider. This provides highly granular anonymised insights into the rider's experience, including braking, swerving, collisions, and road surface conditions.
Through the data insights collected across this project we uncovered several interesting findings in London. Particular attention was devoted to cycling on the bridges of central London, and through our speed data it was found that slower speeds were recorded at each end of Blackfriars Bridge, with northbound traffic light tailback evident in the data. On London Bridge, there was a clear distinction between the speed of northbound cycle traffic compared to southbound, potentially due to morning congestion. The effects of dedicated cycle infrastructure was also observable through See.Sense braking and swerving data. Southwark bridge, with its dedicated cycle lane, showed low rates of swerving compared to London Bridge, where cyclists travel in shared bus lanes.
Following the project's conclusion, information was shared with the Active Travel Network and with the City of London, providing powerful insights for evidence-based planning.
The project was also featured on BBC click.
Alastair Moss, Planning and Transportation Committee Chairman, City of London, said:
‘“There are some really interesting examples that have come out of this already. One is in relation to which bridges people are using. Where this data is showing for example that on London Bridge, compared to Southwark Bridge, the user experience might be less good, because on Southwark Bridge there is a better cycling experience in terms of the braking and less swerving which could indicate a propensity for accidents”.
In 2020, we also conducted our own independent cycling research in London, which aimed to better understand women’s cycling in the city. Through this, we found that women in London are more likely to ride on dedicated cycle infrastructure than men, and in fact will often go out of their way to do so, even at the expense of a longer journey. The data insights collected through this project also highlighted that women tended to experience less braking and swerving on their journeys, and experienced a higher road surface quality on these routes. These findings ultimately displayed the importance of considering gender data when planning cycling networks; a data subset that is too often overlooked.
Our work in London hasn’t been limited to only cycling. In 2021, we partnered with e-scooter fleet operator Dott to conduct an innovative project during the London e-scooter trials, using our patented technology to look at e-scooter rider safety and the safety of other road users.Through the data collected over the trial we were able to successfully identify areas with particularly high levels of e-scooter braking or swerving, finding that hot-spots of high swerving and braking were potentially indicative of an increased risk of collisions. Changes in road surface were also detected and areas possessing particularly poor road surface conditions were identified, with our data displaying that these areas also witnessed high levels of braking and swerving. You can read about our work with Dott in full here.
At See.Sense, our mission is to get more people cycling. This goal is shared by all our partners, from fleet operators to public bodies, who are contributing to making cycling safer and more inclusive. As displayed across our London projects, See.Sense data insights can provide evidence to aid transport planners target investment, enable micromobility fleet operators to understand how their fleet is operating, and help public bodies monitor behaviour change to understand the long term impacts of their interventions.
To find out how See.Sense technology and data services can help with rider and network insights please firstname.lastname@example.org and a member of our team will be in touch.
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