These exciting findings highlight how See.Sense data can be used to inform planning and decision making. In this case study, we will detail the locations and recommendations put forward in the research, and show how See.Sense data has been used to better understand cycling in Exeter.
The analysis used in this case study has been undertaken by Dr Lauren Ansell, University of Plymouth, using data from a period covering April - December, 2021.
What is the See.Sense, Co Bikes and University of Plymouth Project?
In April 2020, we partnered with fleet operator Co Bikes to undertake a world-first initiative to provide advanced data insights on their electric bike fleet - the largest such fleet in the UK. Through the project, Co Bikes in Exeter have been equipped with a See.Sense SUMMIT (Sensor Unlocked Micro-mobility Insight Technology) device. These SUMMIT trackers utilise our patented AI-sensor technology to gather granular insights into the experience of the rider.
The project has been the subject of a research project conducted by the University of Plymouth through the Environmental Futures and Big Data Impacts Lab. This research is using the See.Sense data insights gathered from Co Bikes’ fleet between April 2021 and December 2021 to provide an analysis of cycling in Exeter and identify optimum locations for new bike stations in the region.
Speaking on the project, Mark Hodgson, Managing Director of Co Bikes, stated:
“Our partnership with See.Sense is enabling an unprecedented view of our e-bike fleet in Exeter, and providing us with a greater understanding of how to optimise our e-bike fleet for cyclists in Exeter. By utilising See.Sense data, the University of Plymouth Impacts Lab has produced leading research into how our e-bike fleet is operating, and enabled us to gain a greater understanding of the experiences of cyclists in Exeter.”
Existing Bike Station Locations and Co Bikes Journey Data
The map on the left shows the locations of bike stations. Around each bike station, distances of 0.5 km and 1 km are indicated by blue and red circles. The map on the right shows popular bike journeys made, courtesy of the See.Sense trackers fitted to Co Bikes.
From image a. above, we can see that there are a lot of bike stations in the north-western and central part of the city, providing great access for the majority of people in the city. However, on the south and eastern sides of the city, bike stations are more sparse, with some members over a kilometre away from their nearest station.
Importantly, looking at the journey data (b.), we can see that Co Bikes are being used to travel across the entire city and beyond. And we are seeing lots of traffic in areas where no bike stations are currently available, such as Stoke Hill in the north of the city, and a larger region south of the city, between Ide and Exminster, and the main road to Topsham. Consequently, the research highlights the potential to expand the bike station network in the Exminster and south-western areas of the city - which are currently sparsely populated with bike stations.
Popular Destinations in Exeter
Heatmap showing the most popular co-bike destinations for December 2021. Bike stations within these areas are indicated by a white dot.
As well as tracking overall journey data, the most frequently visited destinations by the Co Bike fleet can also be observed. The image above shows a heatmap for December 2021. We can see that the city centre, particularly around Sidwell Street, is the most popular destination in the city. This is closely followed by Exeter Central, St David’s and St Thomas railway stations, as well as the university and county hall.
Almost all of the popular destinations shown in the image above have a bike station in the vicinity, yet there is one region in Marsh Barton which does not have a station.
This provides further evidence to support the research recommendations for more bike stations to be added in the southern areas of Exeter.
How, and when, are people using the Co Bike fleet?
As well as identifying the ideal locations for future docking stations, See.Sense data was also used to provide a unique insight into how cyclists were using the rental bikes.
Bike Usage Data
Graph showing average bike usage over the course of a day, for each day of the week.
The graph above shows the hourly usage of the Co Bikes fleet. The general trend is that usage is quite low in the mornings, before gradually increasing through the day and hitting a daily peak between 4 pm and 6 pm, then rapidly declining through the rest of the evening.
Interestingly, this suggests that people aren’t using the bikes to commute in the mornings, yet they seem to be using them at the end of the working day. Fridays, Saturdays and Sundays are the busiest days of the week, with 5 pm to 6pm on a Friday being the busiest hour of the entire week. A lot of people are using the Co Bikes as soon as the working week is done, be it to get home or to head into town.
Maps showing the locations in which speeds were recorded below 4 km/h and 12 km/h.
The data collected also enables speed to be studied. The vast majority of Co Bike journeys are travelling within the range of 5 to 24 km/h (the maximum bike speed with electric assist), with the most common speed around 15 km/h.
The slowest speeds, below 4 km/h, are concentrated around the city centre. It is notable that the maximum speed of 24 kph is achievable across the city, but it is also impressive to see how far out of the city some users travel, with bikes being ridden to Dartmoor National Park in the southwest, down both sides of the River Exe to the coast, and off the map eastward towards the East Devon Area of Outstanding Beauty.
The Power of Data
These recommendations by the University of Plymouth Impact Lab ultimately showcase the power of See.Sense data insights to inform planning and decision making. The data generated in Exeter from the Co Bikes fleet is not only helping to identify the ideal locations for future docking stations, but is more generally allowing Co Bikes and researchers to have a much greater understanding of cycling in the city.
Indeed, the granular nature of the data collected through See.Sense bike lights and GPS trackers allows for insights that go deeper than traditional data collection methods. In addition to the location, route and speed data that has been utilised for the Exeter research, See.Sense bike lights and trackers also collect sensor data on road surface, swerving, braking and more. This provides transport planners with a comprehensive data set for future analysis, enabling cities to improve safety, design and maintain cycle infrastructure, and target investment.
See.Sense Data Insights
We work with cities, fleet operators and employers, helping to transform cities for active travel and improve conditions for micro-mobility.To learn more, visit See.Sense Data Services
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