New open data: Busiest times at Blackwall Tunnel

The Blackwall Tunnel (A102) is one of the busiest places on London’s road network. In recent years, journey times have increased and drivers can expect delays to their journey at some times of day. We’ve released this data to the open data community, to enable developers to build the information into their products.  

Our data shows the busiest times at Blackwall Tunnel so developers can include this information in journey-planning apps

What our data shows

*Follow this link to find the data.

1)    The busiest time in the northbound tunnel on a weekday is from 07:00 – 07:30. In heavy traffic conditions, drivers’ journeys could be 15 minutes quicker if they travelled between 06.30-07.00 instead of 07:00 – 07:30.

2)    The busiest time in the northbound tunnel on a weekend is from 13.30 – 15.00. In heavy traffic conditions, drivers’ journeys could be 15 minutes quicker if they travelled between 12.00-13.00 instead of 13.30- 15.00.

We have made this data available to the open data community so you can use it to create products which display the busiest times at the tunnel, allowing drivers to choose to travel outside of these periods or create products for planning quicker and more reliable journeys.

Tell us what you think

We encourage the community to provide feedback on our new data sets to help us continue to enhance and improve our open data products. Please let us know your thoughts in the comments section below or on our tech forum.

Traffic Data Hack Day – Event Review

As previously outlined in our post on March 30 on this blog, the Traffic Data Hack Day was hosted by Amazon Web Services on April 6. The event was attended by TfL employees, academics working within this subject area, data scientists, transport app developers and data visualisation developers.

Another key event in our engagement with those working with our open data, the day was split into two areas, with one focussed on visualising TfL data and the other on extracting data from the source and providing it for analysis.

I’ve not attended a hackathon or hack day before, so it was really interesting to see how they work and to meet participants from all sorts of backgrounds, including universities, consultancies, government agencies and other parts of TfL.

At the beginning of the day we split the focus into two areas; ‘EMR (Elastic Map Reduce)’ where the group was looking at ways to improve the feed of, access to and processing of the SCOOT data and ‘Redshift’ where the group made use of data that had been uploaded to the system and was ready to analyse.

teams working
A team working on ‘Redshift’ which made use of data that had been uploaded to the system and was ready to analyse.

Continue reading Traffic Data Hack Day – Event Review

Traffic Data Hack Day – Register Now

**Registration for this event is now closed**


TfL’s Urban Traffic Control System (UTC) uses 12,000 sensors located at junctions across the Capital to measure traffic flow. The data produced is used to drive SCOOT – the traffic light optimiser system – and on Wednesday 6 April we’re aiming to generate greater value from this as-yet untapped data source.

We want to configure a data processing engine for UTC data and begin exploring this large data set using the tools business users are familiar with, such as R Studio and Tableau, as well as event streams, map reduce type platforms and machine learning tools.

The event is part of our ongoing drive to work with the dev community to create great products from our open data, and offers an opportunity to learn and experiment with cloud tools in a safe, sandbox type environment. Experts from TfL’s Road Space Management team will be on hand to provide support.

Where and when

Venue: Amazon Development Centre, Leadenhall Court, One Leadenhall Street, London, EC3V 1PP

6 April 2016 09:00 – 17:00

Lunch will be provided, so please let us know any dietary requirements.

To register

Please confirm your attendance by Tuesday 5th April – you can register for the event here:

Venue for the hack day
Amazon are hosting the Traffic Data Hack Day on April 6 at the Amazon Development Centre in Leadenhall Street, London

Continue reading Traffic Data Hack Day – Register Now

London Collision Map and Improved Cycle Journey Planning

As part of a wider road safety strategy, last week we launched the London Collision Map and London collision data on our website and in our API, as part of our ongoing commitment to providing open data. We’ve also made improvements to cycle journey planning.

The new cycle journey planning features include:

  • Google street view images at every turn of the route to help cyclists prepare a ‘mental map’ of their route and visualise junctions before they make their journey.
  • The location and details of cycle parking at London rail stations including information on the number of potential spaces, the type of cycle parking and whether it is covered.
  • ‘Cycle route classifications’ for each section of the journey describing the type of cycling environment that cyclists will encounter along their route (e.g. Cycle Superhighways or routes through parks) helping them to be more informed about the journey they will be making.
  • Identification of steep hills along the route.

The other new feature, the London Collision Map, allows searches for road collisions across London, providing information about when and where they occurred, as well as the severity of the incidents, dating back to 2005. It uses STATS-19 casualty dataset, collected annually by the Department for Transport, and shows a significant reduction in the number of collisions over time.

Through this data we’re able to inform people about junctions and roads that have high numbers of collisions, and where road users should be particularly careful. The 2014 figures show that this number fell to its lowest level since records began, in line with the Mayor’s target to halve the number of people killed and seriously injured (KSI’s) by 2020.

The London Collision Map, showing fatal and serious collisions in 2014, around the area of St. James's Park Underground station.
The London Collision Map, showing fatal and serious collisions in 2014, around the area of St. James’s Park Underground station.

Continue reading London Collision Map and Improved Cycle Journey Planning

Improved Roads Open Data – Car Parks & JamCams

In my previous post on Roads Open Data I outlined the importance of providing quality data for London’s roads, particularly at a time when our Road Modernisation Plan is being implemented and we are urging drivers to check for disruption before they travel.

We continue to make improvements to our roads open data, with London Underground live car parking spaces availability now available through the Unified API, as well as live video JamCams that give a far better indication of how traffic is flowing in the Capital.

London Underground car parks

London Underground has over 60 car parks with over 11,000 spaces. With the help of our partners NCP and SmartParking, we have released live data showing available spaces for 25 of these car parks. We are seeing whether we can expand the feed to cover all London Underground car parks in the future.

We don’t have this showing on yet, but we’ve made the feed available as open data in the Unified API so that the dev community can have a head start.

You can get the full list of Car Parks from the Places API, which can also be searched by lat/long bounding box or radius. For each car park, we return information such as the address, opening hours, payment methods and facilities, and in some cases, the live occupancy. In the example below, Barkingside Station car park, the OccupancyUrl is returned, indicating that live data is available.

  "id": "CarParks_800491",
  "url": "",
  "commonName": "Barkingside Stn (LUL)",
  "placeType": "CarPark",
  "additionalProperties": [
    "category": "Description",
    "key": "NumberOfSpaces",
    "sourceSystemKey": "CarParks",
    "value": "46",
    "modified": "2016-01-07T15:45:43.153"
    "category": "Description",
    "key": "NumberOfDisabledBays",
    "sourceSystemKey": "CarParks",
    "value": "2",
    "modified": "2016-01-07T15:45:43.153"
    "category": "Meta",
    "key": "OccupancyUrl",
    "sourceSystemKey": "CarParks",
    "value": "",
    "modified": "2016-01-07T15:45:43.153"

The URL is based on the place id of the car park, for example “CarParks_800491” so if you know the Car Park id, you can go straight to the occupancy data. We use a separate URL because we have a much shorter time-to-live in our cache for the occupancy vs. the place data (60 seconds and 1 day respectively). In the example below, using Barkingside again, we can see that there’s no spaces available right now.

 "id": "CarParks_800491",
 "bays": [
     "bayType": "Disabled",
     "bayCount": 2,
     "free": 0,
     "occupied": 2
     "bayType": "Pay and Display Parking",
     "bayCount": 45,
     "free": 0,
     "occupied": 45
  "name": "Barkingside Stn (LUL)",
  "carParkDetailsUrl": ""

Continue reading Improved Roads Open Data – Car Parks & JamCams

Standardisation in roads open data

This week we have a guest post from Duncan Elder, an Associate with IBI Group and a specialist in transport data, spatial information and customer information systems.

In Part 4 of the series on the Unified API on this blog, Tim discussed TfL’s roads open data and gave guidance on how to build apps using this data. Having worked closely with TfL for some time now, this prompted me to expand upon Tim’s post with a look at a long-standing issue around this kind of data – standardisation.

Whilst it is widely agreed that data held by transport agencies should be made open, there remains a question over how easily this open data can be exchanged and used by various parties. UK public transport agencies have been rather ahead of the curve here, as the exchange of train, bus and tube information is underpinned by the use of standard approaches for describing data, such as exists with NAPTAN and TransXchange, and the equivalents in Europe; Transmodel, IFOPT and NeTex.

This means that in the UK we are used to seeing widely available public transport journey planners and information from a range of different providers, all of which would be unlikely to exist without a standardised approach from the various sources of open data which power these tools.

However, when it comes to roads open data things are much more complex, with the data held by public bodies less centralised, the number of miles of roads much greater than rail, and the number of possible sources of roads data far greater. This includes an increase in the use of crowd-sourced data, in addition to existing sources of road information, which adds to the difficulty in establishing a standardised approach to data provision.

Road data
Open data for roads is a complex proposition, with many more miles of road than rail and a far greater number of possible sources

Continue reading Standardisation in roads open data

Urban Traffic Data Hackathon – Nov 14-15

Roland Major, Enterprise Architect within TfL’s Information Management team, reports on the Urban Traffic Data Hackathon.

In the last post on this blog, Tim introduced the roads data available in our unified API, describing its importance as we encourage road users to check before travelling while we carry out our Road Modernisation Plan.

We continue to engage with developers to help us in making driving in London better, with innovative solutions to traffic, road disruption and planned works information through apps created from our open data. As part of our engagement with the developer community we held an Urban Traffic Data Hackathon on 14-15 November.

Supported by our Roads Space Management team, the event was planned in order to give us the opportunity to engage directly with developers to work on creative and innovative solutions to the challenges on London’s roads. In putting the Hackathon together, we worked with Data Science London (DSL), the largest data science community in Europe, and arranged for data scientists and innovators who are members of DSL to take part in the event.

Queen Mary University hosted our Urban Traffic Data Hackathon on 14-15 November
Queen Mary University hosted our Urban Traffic Data Hackathon on 14-15 November

Continue reading Urban Traffic Data Hackathon – Nov 14-15