Earlsdon Liveable Neighbourhood traffic data - Print version

The Earlsdon Liveable Neighbourhood scheme has been guided first and foremost by the priorities identified by residents that align to the core aims of the project. However, we have used traffic data and traffic modelling to contextualise what people have told us, and to understand the impacts on the wider traffic network. 

The data collected and analysed falls into five categories:

• Historic data – under the conditions laid down by the Planning Enquiry for the Friargate development, we are obliged to collect annual traffic counts in a number of streets in the area around Coventry station. This includes streets in Earlsdon.
• Pre-project data – information we gathered at a very early stage, before we knew the full extent of local concerns and priorities, but based on problems previously communicated to us by the community
• Responsive data – data that we gathered after the first round of community engagement (December 2022 to March 2023), which was used to provide a deeper understanding and context to some of the issues raised up to that point
• Modelling data – in determining and refining the proposals, we undertook traffic modelling to understand the wider impact on the road network of the potential changes. This included ruling out options that were never taken to public consultation, on the basis of the significant impact on traffic.  
• Ongoing monitoring data – this is the most recent data, and as yet has not been analysed as it is intended to provide a baseline for monitoring and evaluating the effects of the scheme.

Historic data

Under the conditions laid down by the Planning Enquiry for the Friargate development, we are obliged to collect annual traffic counts in a number of streets in the area around Coventry station. This includes streets in Earlsdon. This gives us a picture of how traffic volumes have changed in the area since data collection started in 2011. All speeds are recorded in Miles per Hour (mph). Speeds are shown as both mean (the average speed) and the 85th percentile. The latter means the speed that 85% of drivers travel at or below. If there is a large difference between mean and 85th percentile speeds, this suggests that excess speeding is an issue (compared to streets with a smaller range).

Pre-project data

Before the project started, we collected traffic data in local streets. This included pedestrian crossing data. This was guided by where we had received historic requests for traffic calming and pedestrian crossings to be installed. Each type of pre-project data is explained below, along with a summary of the results.

Automatic traffic counts – these count the number of vehicles each hour in each direction over the course of a continuous period – usually seven consecutive days and for 24 hours a day. Vehicles are broken down by “classification”, allowing us to understand the mix of vehicles – this means how many vehicles are buses, cars, lorries, motorcycles, and cycles. Like any survey method, classifications are not always 100% reliable, but the data provides a useful snapshot (and errors are resolved by conducting the survey over as long a period as possible).

Automatic traffic counts also record vehicle speed – again with potential for some error, like if two vehicles are passing over the survey point at the same time. Because the survey is undertaken at a single point, this means that the speeds recorded are only accurate for that precise location, and actual speeds will vary along a street due to different conditions. The practicalities of automatic traffic counts – collected using rubber tubes that disperse a wave of air when squashed by a vehicle – means that these have to be located away from junctions and other locations where vehicles might be manoeuvring. This in turn means that they are often located on the part of the street where we expect vehicle speeds to be highest.

Junction turning counts

These were undertaken at major junctions across the study area and beyond. These allow us to understand the different turning proportions at a junction. Turning proportions – how traffic in one direction may be busier than traffic making a different manoeuvre – can give context about how traffic flows through the wider network as a whole rather than what it is doing at a single location like at a traffic count site. Turning counts are more onerous to undertake, so results are often analysed only for a single day. While this may be more likely to incur seasonal variation, it is normally okay to accept this as the proportionality is more important than the actual numbers, and proportionality is less likely to change apart from where there are heavily seasonal trip attractors. Therefore, we do have to make sure that the single day surveyed is not subject to atypical events, such as a road closure on the strategic network or a football match at a nearby stadium. Midweek days are normally chosen to as being the most “traffic neutral” – less likely that people have taken Monday or Friday off for a long weekend or worked shorter hours, and Wednesdays are normally avoided in University areas as this is the traditional half-day for sports – so our analysis was undertaken on a Tuesday, specifically 28 June 2024.

Junction turning count locations

Use the links to jump to data

• Albany Road – Spencer Road – Newcombe Road (crossroads) [#ALBANY]
• Beechwood Avenue – Hartington Crescent (mini-roundabout) [#BEECHWOOD1]
• Beechwood Avenue – Rochester Road (crossroads) [#BEECHWOOD2]
• Earlsdon Avenue North – Albany Road – Earlsdon Avenue South – Earlsdon Street – Poplar Road (roundabout) [#EARLSDON1]
• Earlsdon Avenue North – Newcombe Road (crossroads) [#EARLSDON2]
• Hartington Crescent – Arden Street (tee-junction) [#HARTINGTON1]
• Kenilworth Road – Beechwood Avenue (tee-junction) [#KENILWORTH1]
• Kenilworth Road – Earlsdon Avenue South (traffic signals) [#KENILWORTH2]
• Warwick Road – Spencer Road (traffic signals) [#WARWICK]

Albany Road – at Newcombe Road / Spencer Avenue junction

Beechwood Avenue – at Hartington Crescent mini-roundabout

Beechwood Avenue – at Rochester Road

Earlsdon Avenue roundabout

Earlsdon Avenue North – at Newcombe Road

Hartington Crescent – at Arden Street

Kenilworth Road – at Beechwood Avenue

Kenilworth Road – at Earlsdon Avenue South

Warwick Road – at Spencer Road

Pedestrian crossing data

These were undertaken at the locations where we have historically received requests for pedestrian crossings to be introduced, namely:

• Beechwood Avenue – at Rochester Road
• Rochester Road – at Beechwood Avenue
• Earlsdon Street – at the Earlsdon Avenue roundabout

Beechwood Avenue at Rochester Road

Rochester Road – at Beechwood Avenue

Earlsdon roundabout crossing data

Responsive data

During the first round of engagement, an issue affecting some streets but not others was the perception of roads being used as “cut throughs” or “rat runs”. Some of these concerns were raised by residents in streets not in the first consultation area. Across a large part of the consultation area, many people told us about parking congestion in their road.

To understand these concerns, and contextualise how they may vary across the area, we obtained telemetric traffic data and undertook a parking beat survey.

Telemetric traffic data is available from data aggregators who primarily work for the motor vehicle insurance industry. The anonymised data they collect for their clients is available to be purchased by traffic authorities and consultants to assist in traffic analysis and modelling, providing a far richer source of information than can be obtained using traditional survey methods, and much more cheaply than more costly automatic number plate recognition surveys. One particular advantage of this type of telemetric data is that is can be obtained retrospectively, so data going back quite some time can be obtained. This can avoid the pitfalls of a planned survey to capture the same information – as one-off unusual events during that survey period may compromise accuracy. By being able to retrospectively obtain data, unusual events can be avoided by simply not selecting the affected period if known, or by capturing a sufficiently long period such that the overall patterns end up dominating the data. The data can be analysed to show on each street (or section of street) what proportion of observed vehicles did or did not make a stop in a particular area. This therefore gives an indication of which streets are more susceptible to being used as “rat runs” or “cut throughs”. For this study, the area chosen was slightly wider than the original consultation area. This was in response to concerns raised by people living just outside that original consultation area. The area designated was the area bound by the railway line, Kenilworth Road and Beechwood Avenue (inclusive). Any vehicle passing through this area but not stopping was classified as “through traffic”, and any vehicle that started or finished its journey in this area was classified as “local traffic”. Because the telemetric data relies on GPS, data closest to the railway line may be less reliable.

The data also provides speed information, and this is over the average of each link (i.e. street or section of street), and thus is more nuanced that the “point” speed data of a traditional automatic traffic count. The map below shows the average speed on each street or section of street, classified into colour-coded ranges to enable variance in speed to be clearly visible. Because the telemetric data relies on GPS, data closest to the railway line may be less reliable.

Parking survey

A parking beat survey was undertaken on all streets in the original consultation area. This method of survey uses manual enumerators who record part of a vehicle’s registration plate (so that they are not collecting personal data).  They do this on a regular “beat” of one hour. By matching partial registration plates across the survey period, it is possible to determine how long vehicles are parking for as well as parking occupancy during every hourly beat period. Because of Earlsdon’s busy “evening economy” scene, we undertook the parking beat survey over a longer period than usual – 6am to Midnight. We also did two surveys – one on a weekday and one on a Saturday. The table below shows the level of “parking stress” on each street, averaged out during different survey periods. Parking stress is the proportion of spaces taken up: the closer to 100%, the higher the parking stress. 

It is clear to see that the areas with the greatest parking stress are those closest to Earlsdon Street, namely:

• Arden Street
• Berkeley Road South
• Newcombe Road
• Osborne Road
• Providence Street
• Radcliffe Road
• Stanley Road
• Warwick Street

These streets all had parking stress regularly over 80%.  Parking stress above 85% is usually considered inefficient, as it means that motorists must excessively circulate for parking, contributing to congestion. This obviously affects people’s quality of life by making it more difficult to park close to their homes, and worsens air pollution. The streets where parking stress is greater at weekends may suggest shopping or leisure activities are a contributory factor to parking activity. This is clearly the case in Warwick Street off-street car park, which is much busier for parking at weekends, as is Beechwood Avenue.

This data was used to inform decisions about proposing to make some streets one-way, in order to increase parking by reducing yellow lines, however these elements of the scheme were not taken forward following public feedback. Residents may wish to organise a petition for a permit parking scheme, [https://www.coventry.gov.uk/parking-2/residents-parking-schemes/4] in line with our resident parking scheme policy.

Modelling data

In selecting the option to take to the second round of community engagement, traffic impacts were tested in the Coventry Area Strategic Traffic Model (CASM).  This led to some interventions being withdrawn before going back out to consultation, due to unacceptable impact on the wider traffic network.

Note that CASM does not cover every single street, as it is a strategic model.  CASM therefore is only able to test the impact of the proposed No Entry on Stoneleigh Avenue, but not the more localised traffic changes.

The traffic model output below shows the result of the scheme now being introduced.  The outputs are for each peak period during the working week.

While most of the traffic affected simply stays on Kenilworth Road for one extra junction, the model does predict that some users will choose different routes entirely.  The traffic redistribution appears to be greatest in the afternoon peak period.

The modelling does not suggest significant negative impacts at any junction.

The traffic modelling does not take into account modal shift that may occur as a result of the scheme.  Modal shift means people choosing different modes of travel by those having been made more effective or attractive as a result of interventions.  For example, many residents of Earlsdon Park Care Village told us that walking to Earlsdon Street was an option for them, but they chose to make the journey by car due to concerns about crossing the road or not having somewhere to sit and rest.

Ongoing monitoring data

As part of the Monitoring and Evaluation Plan for the project, a number of fixed traffic and pedestrian counters have been installed on lamp columns.  These will be used to compare user activity before and after the implementation of the scheme.  The regular Friargate monitoring surveys will also take place, and, where relevant, the pre-project data will be re-surveyed in due course.