User guide for the Connected Neighbourhood Tool

Overview

The Connected Neighbourhood Tool helps you design a Low-Traffic Neighbourhood (LTN). This guide is written specifically for the Scottish version of the tool, but most of it applies elsewhere too. In this guide, we assume you are already familiar with the concept and purpose of LTNs. If you have any trouble using the tool, please email the maintainer at dabreegster@gmail.com.

The overall process of using the CNT looks like this:

  1. Choose your study area
  2. Add one or more neighbourhood boundaries
  3. Design your LTN with modal filters, one-way streets, turn restrictions, and sometimes by reclassifying main roads
  4. Explore the effects of your proposal
  5. Share your work with a colleague

Adding a neighbourhood

Start using the tool by going to https://cnt.scot/ and picking your study area on the map or from the list. The study areas are defined by Local Authority Districts.

To design an LTN, you first need to specify its boundary. Unless you’re working on a large circulation plan, the neighbourhood boundary will probably be a much smaller area than the entire study area shown. You can create multiple LTNs in one project, but you only need one to start.

Quick boundaries from severances

In some cases, the boundary you want will already be shown on the map as a coloured area. These areas are found automatically by dividing settlements on the map by severances – main roads, railways, and bodies of water.

After clicking one area, you can keep clicking adjacent areas to extend the boundary, in case the first boundary is too small.

Drawing manually

Alternatively, you can draw an area in more detail by picking at least three points on the map.

You can drag any of the red or grey points to adjust the boundary. Any point you drag becomes a red waypoint:

The red points snap the boundary to roads. Sometimes near a park or body of water without any roads, you may wish to draw the boundary in even more detail by turning off snapping. Click any red point to turn it blue, which you can drag anywhere you like:

When you draw a boundary manually, sometimes the resulting area doesn’t have a valid shape:

The 1st and 2nd point form long line-like “spurs” away from the area. Between red snapped points, the tool is trying to find the shortest distance path along roads. Sometimes that path on both sides of a point will use exactly the same roads, resulting in this spur. When you see this happen, you can keep dragging points around, introducing more points, and so on to fix the shape to match whatever you intend.

Prioritisation metrics

This feature is currently available in Scotland only.

Transport for London’s Strategic Neighbourhood Analysis describes an approach for prioritising LTNs by different metrics. The CNT exposes some of these metrics for the areas:

  • Population density – generally LTNs have greater benefit in denser areas
  • Collisions – using stats19 data about prior collisions involving pedestrians and cyclists, it may be important to target areas with existing problems
  • SIMD (Scottish Index of Multiple Deprivation) – depending on local priorities, areas with higher deprivation may be important
  • Points of interest – areas with a mix of residential and commercial land use can be important to improve walking and cycling
  • Car ownership – residents in areas with low car ownership are not benefitting from through-traffic

Depending on local priorities, you may want to use some combination of these metrics to decide where to prioritise creating an LTN. You can colour the areas by any of these metrics:

As you select or draw a boundary, all of these metrics are evaluated against your area:

Designing an LTN

After specifying a neighbourhood boundary, you are in the main editing mode. There are four editing controls available, but first you need to understand the cells and shortcuts shown on the map.

Understanding the map: cells

This example neighbourhood is bounded on all sides by a grey main road, where we assume the road is designed to handle a higher volume of traffic. The smaller coloured areas inside the neighbourhood are cells, showing internal connectivity for a driver. If a driver enters the neighbourhood by the blue arrow, they are only able to reach the area shown in blue; they can’t drive to the yellow or pink cells without exiting back onto the main road, then re-entering the neighbourhood somewhere else.

Another example is shown below. The orange cell is effectively a small cul-de-sac; a driver won’t enter unless their journey starts or ends there. They can’t access the larger blue cell.

Aside from these smaller cells, this neighbourhood mainly consists of the large blue cell. There are many points where a driver can enter and exit this cell. Because the blue cell stretches so far, a driver can enter from the south and drive all the way through to the north.

If understanding the cells as areas is confusing or inconvenient, you can modify the map style and colour the roads by their cell instead:

Understanding the map: shortcuts

To design an effective LTN, you must limit the traffic cutting through the neighbourhood. Shortcuts show the possible routes through a neighbourhood a driver might take when avoiding main roads. They do not include journeys starting or ending somewhere in the neighbourhood, just routes that pass through without stopping. These are shown in shades of red; the white streets are dead-ends and cul-de-sacs; a driver has no reason to go there unless their trip starts or ends there. The darkest reds show the streets most likely to see lots of traffic cutting through. The darkest red is along the long north/south street:

To understand why, you can use the Shortcuts tool at the top. If we inspect this street, we see one example shortcut from north to south:

The tool identifies 51 different shortcuts passing through this one street, showing the most advantageous shortcuts first – the ones that save the driver the most time by cutting through the middle of the neighbourhood. Most of the shortcuts are simple variations, changing the exact entrance or exit. There are also some shortcuts involving the western boundary:

The tool counts these shortcuts in a simple way:

  1. Find all entrances and exits onto streets from the main roads
  2. For every combination, calculate the fastest driving route, using the speed limit and length of each road. Main roads are penalised as having half their speed limit, to simulate delays in heavy traffic conditions.
  3. Any route that crosses a main road is discarded
  4. Count the number of routes crossing each street segment

The tool assumes a driver is equally likely to enter and exit the neighbourhood through any point, but of course this doesn’t reflect the real traffic patterns in the larger area. Maybe the northern boundary of this neighbourhood isn’t attractive for drivers, because there’s no reason to drive that way. (In this case, since the neighbourhood is just north of Aberdeen city centre and the north/south shortcut is parallel to an A road, it is likely a shortcut that happens in practice.) The tool’s assumptions are necessary to make due to a lack of detailed traffic pattern data, and because they can be calculated even as you start to edit the neighbourhood. The shortcuts simply show what is possible for drivers to do, not what is likely. You may need to apply your own local knowledge, judgment, or traffic counters to verify a shortcut is actually a problem in practice.

Editing: modal filters

Now that you understand shortcuts, let’s move on to the interventions you can propose to fix these problems. The main tool is the modal filter, or point closure. It stops drivers from passing through a street, while still allowing pedestrians and cyclists (and sometimes buses, emergency vehicles, etc) through. Let’s try adding a modal filter along the north/south shortcut:

Immediately after you click to add the filter, you’ll see the red shortcuts jump to the right, zig-zagging to avoid the new filter. If you add a second filter there, you’ll see a big change:

The blue cell has been split into a new yellow cell, making it clear that now the north/south shortcut is totally impossible.

You may have noticed the modal filter icons on the map are different. There are four types you can choose from:

In the scope of the tool, these all mean the same thing – a driver cannot pass through. You can use the different types to communicate more specific proposals. School streets are timed closures, but the tool will model the effects of the filter during school hours. When you place a filter on a street that currently has a bus route along it, you will automatically get a bus gate, which uses camera enforcement and doesn’t physically prevent vehicles from crossing. The specifics of the physical intervention are outside the scope of this tool – depending on width constraints, allowing adequate room for bin lorries to turn, and so on, the physical implementation of a filter could be a pocket park, removable bollards, concrete, etc. The LTN tool’s purpose is to focus on the strategic planning.

Editing: diagonal modal filters

Modal filters usually apply at one point along a street, but when you have a four-way intersection, you can click it to toggle through two possible diagonal filters. These allow traffic through the intersection only for some combinations of streets.

Editing: one-way streets

You can also change the direction of traffic flow along a street. This is helpful to retain through-traffic in one direction, but funnel it back out to a main road. Or sometimes a shortcut is only problematic in one direction.

You cannot create new cells only by introducing one-way streets, but you can influence shortcuts.

Editing: turn restrictions

You can restrict some turns through an intersection without outright preventing all movement. This may be useful to prevent unprotected turns to or from a main road when there is no room for a turning lane.

Note that existing turn restrictions are automatically added from OpenStreetMap data. There are some complex situations near dual carriageways that may not be detected correctly; please contact the team to report this problem if you encounter one.

Editing: main road classification

When you initially create a neighbourhood from its boundary, some roads count as main roads, shown in grey. The initial classification is taken from OpenStreetMap data. Main roads are intended to handle through-traffic, and so the tool does not calculate shortcuts along main roads, and the cells are determined by connections to main roads. In the example below, there are main roads surrounding the perimeter of the neighbourhood, which is typical, but there are also two north/south main roads in the middle, causing there to be cells on each side.

You may want to reclassify these main roads, and treat them like residential streets that should not carry through-traffic. This could make sense in the context of a larger circulation plan, a redesign to the strategic road network in the wider area, or when the main road is a high street with heavy foot and cycling traffic. No matter the reason, you can mark new main roads or erase main roads using one of the tools. In complex areas, it may be simplest to first Erase all main roads and then Mark as main along a route. After removing those two interior main roads, the neighbourhood looks like one big cell:

You can now make other edits and see the effects on cells and shortcuts through the entire area.

Exploring effects

As you design an LTN, you are already understanding the effects on traffic through the area, by paying attention to cells and shortcuts. You can also study the effects on the entire study area.

Effect on one journey

A common concern during public consultations is that a driving route that previously cut through a neighbourhood will become much longer or impossible after an LTN is created. You can use the route tool to evaluate journeys between a start and end point. The red line shows the fastest route before any changes you’ve made, and the blue line shows the new route accounting for your new modal filters, one-ways, and turn restrictions. When you see just a blue line, it means both routes are the same – your changes had no effect on this journey.

The choice of route and the estimated journey time is based on simple assumptions that drivers travel at the full speed limit, with no delays at junctions or due to traffic. This is of course unrealistic, but there is no openly available traffic data everywhere. Usually the fastest route stays on main roads, which have higher speed limits, but during heavy traffic, drivers are more likely to divert through a neighbourhood street. You can model this situation using the slider to slow-down main road traffic.

Effect on routes to one destination

Another concern during public consultations is the effect on residents within an LTN who drive. Previously they may have taken a shortcut through the neighbourhood to visit the city centre, but a new filter might make their journey slightly more inconvenient. You can use a tool to explore the change in journey times starting from everywhere in the neighbourhood going to one destination, designated by the orange X. Starting a journey from most streets isn’t affected by new filters, but a few streets are coloured red.

Hovering on one of the streets shows the journey before and after the changes. You can click any of these to open in the route tool and explore further.

Impact prediction

Suppose a large volume of traffic previously took a shortcut through a neighbourhood. After designing an LTN to address this problem, will those drivers stick to main roads, or is there a different detour through an adjacent neighbourhood they might try? To understand these possible spillover effects, we need to understand the overall patterns of traffic in the wider study area. Origin/destination datasets describe where journeys begin and end. The LTN tool’s impact prediction mode calculates the route each trip would take before and after your edits, and then identifies red streets in the entire study area that may experience higher traffic and green streets that should experience lower traffic. In the example below, there are two LTNs, shown as grey areas, each with new modal filters.

There are many assumptions and limitations with this analysis; it is not intended to replace a proper traffic model. It is simply a convenient tool to quickly estimate what main roads and other neighbourhoods might need attention. The limitations include:

  • The origin/destination data for Scotland comes from the 2011 home-to-work census data. 2011 is very old, this dataset has its own caveats, and home-to-work trips only account for a small fraction of traffic. There are no known better open datasets to replace this.
  • By default, this tool uses the “Calculate quickly” option, which samples only one journey between census zones, and weights the result based on the number of trips between the zones. “Calculate more accurately” takes longer, but simulates many journeys between zones.
  • In studies of real LTNs, counters show “traffic dissipation” over a long period of time, in which people previously choosing to drive change their travel behavior entirely – resulting in different destinations, walking or cycling or taking public transit instead, driving at different times of day, and so on. This analysis does not model any of that.

Sharing your work

All of your projects are stored in your web browser’s local storage. If you change devices or browsers or clear your browser’s storage, then you will not see your old projects. At any time, you can export a project to a file from the main screen:

This will download a GeoJSON file. You can email this, copy to Sharepoint, or otherwise transfer to somebody else. At the bottom of the very first Choose Project screen, you can then load this project from its file:

Multiple proposals

You may want to try a few different proposals for an LTN. Each alternate proposal will be in its own project. From the main screen, you can quickly copy a project and switch between projects.

Appendix

Changelog

As this tool is updated, major changes will be described here. See Github for detailed changes.

  • v1, 4 June 2025 - first main release
  • 12 June 2025 - detecting more shortcuts (see details) and more conveniently reclassify main roads along a route (see details)
  • 16 June 2025 - show a neighbourhood before any edits (see details)
  • 30 June 2025 - copy and switch projects quickly (see details)
  • 6 July 2025 - improve styling for pedestrianized areas (see details)

Credits

This is the second version of the A/B Street LTN tool, an open source project. This version, called the Connected Neighbourhoods Tool, has been funded by Transport Scotland and designed by Sustrans Scotland. The team includes:

This second version of the tool is an evolution from the original A/B Street tool, with many people to thank there. Of the dozens of users giving excellent feedback and shaping the tool’s development, particular thanks to:

This tool would not be possible without:

Some road signs images © Crown copyright.