https://www.cyclestreets.org/news/2021/07/25/mapping-ltns/

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Mapping modal filters and LTNs

MartinJuly 25, 2021Bikedata site, LTNs, Open dataNo comments

Modal filters - measures such as bollards, gates, cycle contraflows,
etc., are important ways to prevent motor traffic passing through
residential areas. They have been much in the news recently, but are
in fact very common, and have been in existence since at least the
1980s.

However, there is no national mapping data on where they are. It
turns they are in fact extremely common, found in pretty-much every
town or city. They are not a 'radical' or new measure. We set out to
prove this, and for the first time, have mapped them.

We have analysed street data to determine the locations of modal
filters across the UK, as well as which streets are through-streets
(i.e. capable of having through-traffic from one main road to
another). This work has now reached a beta (preview) level.

The resulting mapping, once publicly released, will be helpful for
anyone (e.g. citizens, councillors and council officials) trying to
introduce new LTNs - as it proves how common and widespread these
measures are. It will show where further work by local councils is
needed. The data on streets will also enable new research to be
undertaken on the socio-demographic effects of LTNs, for instance,
whether they disproportionately benefit or affect particular groups.

[cyclestreets172469-size350]  [cyclestreets150705-size350]
[cyclestreets150487-size350]  [cyclestreets67810-size350]
Modal filters of various types - (1) Bollards, or planters/gates/
gaps, (2) Continuations, (3) Bus gates, (4) No entry except cycles.

1. Mapping modal filters

We have undertaken complex analysis of OpenStreetMap to determine the
locations of modal filters. By analysing street patterns, to create a
map of where modal filters are located, we aim to show these are
entirely normal and widespread.

There is no widespread map data in the UK that ever states "Here is a
modal filter". Instead, maps only state the physical attributes of a
street, e.g. a residential street with bollards at one point.
However, bollards and gates can also exist in a context which has
nothing to do with modal filters.

As such, a dataset of modal filters can only be obtained by running
complex algorithm analysis to spot the typical street patterns which
create the concept of a modal filter. This is what we now have done.

Each of the modal filter types shown in the above example pictures
are represented, and you can see below an example from Cambridge.

We will shortly publish a blog post giving fuller details of the
analysis. But for now, you can read the technical details, and gain
access to the password-protected beta analysis, via this mailing list
posting on the OpenStreetMap talk-gb mailing list. The analysis is
quite complex and is not yet perfect.

We welcome feedback on this beta mapping. At present we estimate we
so far have achieved around 80-90% accuracy. You can right-click to
flag up a missed location, or click on an existing location to report
that it should not be a modal filter. We will review these, to enable
us to fix up any systematic shortcomings in our analysis, or
whitelist unusual street layout locations that our automated analysis
is otherwise unlikely to detect.

[cambridgemodalfilters]

An early iteration of this work resulted in coverage in the Guardian.
We have since gone on to refine the analysis further.

We plan to collaborate with an academic colleague in London to
produce a peer-reviewed paper on this new research.

2. Mapping through-streets

We also determine whether every street can be potentially used for
through-traffic ('rat-running') or not from one main road to another.

This is not a map of whether rat-running is actually happening, since
there exists no published data on that. It is a map of whether a
street is physically capable of seeing through-traffic.

  * Blueish-green shows where rat-running is not possible, due to
    modal filters or dead-ends;
  * Red shows where through-traffic is possible;
  * Brown shows where through-traffic is possible but there are also
    traffic-calming measures in place to deter it.

In technical terms, this is actually a completely separate analysis
to the modal filters work, and involves the use of car routing -based
testing between identified main roads, and the use of some heuristics
to eliminate unlikely situations. This work is at a slightly earlier
stage of maturity but will continue to improve, and we are already
getting pretty good results.

[cambridgeltnstreets]
Streets in terraced areas of Cambridge often prevent through-traffic,
as there are modal filters to stop it physically, or traffic-calming
has been installed to deter it.

We will similarly shortly be publishing a blog post giving fuller
technical details of the analysis.

Watch our talk

We gave a talk on both of these new datasets in early July, to a
regular meeting of active travel professionals and advocates from
around the UK, organised by Brian Deegan.

[ltnsintroduction]

Some background: What's changed on local streets over the last
decade?

This remarkable chart, using the official data from London
demonstrates the remarkable change in use of residential streets
since 2009.

That date correlates with the growth of mobile phones with free
satnav apps for drivers. Deliveries have also risen since, as a
result of online ordering.

[trafficgrowth]

Acknowledgements

Our research on modal filters and through-streets has been made
possible thanks to a grant from the Rees Jeffreys Road Fund. We are
most grateful to the Trustees of the Fund for their choosing to fund
this work.

[reesjeffreys-1]

The work was initially commenced thanks also to a small amount of
funding from #BikeIsBest, for whom we undertook initial analysis.

[ec5f7664c650]

Martin

Related Articles
Dublin Region Active Travel Challenge
London Cycling Data
Our talk at State of the Map 2019: Is the OSM data model creaking?

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