See.Sense partnered with a world-leading engineering consultancy AECOM, to demonstrate how the ride insights we’ve collected in Dublin can be used to create a 21st Century approach to the design of cycle infrastructure.
In this exciting R&D collaboration, AECOM was able to show how See.Sense data could be used to inform a Quality of Service assessment for Dublin’s cycle network and found that:
“The data provided by the lights is a useful tool for planners to develop cycle networks and also identify maintenance priorities”.
What is the Quality of Service assessment?
Cities around the world are investing to improve the quality of their cycle networks. A ‘Quality of Service assessment’ gives decision makers an understanding of how well the current network provides for the needs of cyclists. Once this is understood, it is possible to identify where investment in infrastructure will yield the highest return, improving urban mobility, air quality, health and increasing access to active travel. The current methodologies for undertaking Quality of Service assessments are labour intensive, involving large teams of personnel and can often take several months or even years to complete.
The National Cycle Manual in Ireland uses Quality of Service ratings as a measure of the degree to which the 5 needs of a cyclist are met. The 5 needs are:
These needs are then given a rating from D (poor) - A+ (good).
The Quality of service is measured through the following 5 characteristics of infrastructure which can be related back to the 5 Needs of Cyclists:
Number of adjacent Cyclists
Number of conflicts per 100m of Routes
Journey Time Delay
How can See.Sense Ride Insights help?
AECOM identified that the ride insights collected through the See.Sense project with Smart Dublin may be able to provide information on the more challenging, and time consuming, aspects of assessing the QoS for an urban area and focused on looking into the following characteristics of infrastructure:
Journey Time Delay
Pavement Condition reporting is ordinarily undertaken through visual inspections with pavements rate on a scale between from A+ to D.
AECOM used the See.Sense data to identify hot spot areas of poor road surface condition and undertook visual inspection to determine the accuracy of the data. They found a high level of correlation between the values in the See.Sense data and the scores (A+-D) they would give through visual inspection.
Following confirmation of this correlation, AECOM used the data to run their own modelling on areas of the city they were most interested in, in this instance, identifying areas where the cycleway has been interrupted by kerb and change in surface texture.
Journey Time Delay
As well as Pavement Condition, AECOM wanted to find out if the See.Sense location data could be used to estimate delays at junctions along a route to the south-east of the city, linking Trimelstown Avenue to Grand Canal.
A 10metre buffer was applied around the stop line of the junctions with the data points falling within that buffer analysed based on their value for speed.
10 metre buffer applied around stop lines
Delay at junctions (% results with speed <5kph)
AECOM also looked in to Journey time delay along a popular route to the north of the city, along Clontarf Road, finding that people choosing to travel by bicycle are travelling at higher average speeds that those choosing to travel by car.
In summary, AECOM found that, “The data provided by the lights is a useful tool for planners to develop cycle networks and also identify maintenance priorities, and that the data can be used to get a better understanding of a cities cycle network in terms of: Pavement Condition; Junction Delay; and Desire Lines.
Further potential also exists to look into both quantitative and qualitative information (received via in-app Surveys in the See.Sense mobile app) in regard to road user conflicts”.
We were proud to co-present this work at prestigious conferences European Transport Conference 2018, and Velocity 2019
Read our case study featured in AECOM's Unlocking Smarter Infrastructure publication here