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Smart Motorways CALibration and Optimisation, UK

To enable the calibration and ongoing optimisation of smart motorway schemes in England, the Highways Agency identified organisational changed required: a better ability to visualise and assess system performance and calculate and calibrate smart motorways operational parameters.

Congestion on the M6 highway

Mott MacDonald and TRL were appointed in 2011 to equip the Highways Agency and its technology asset support partners with the tools, processes and knowledge to achieve this aim.

Challenges

The SMCALO toolkit was the key software deliverable for the project. Web-based, the toolkit provided users with a secure access point to sets of data from live Highways Agency servers including MIDAS GOLD, HALOGEN and the Site Data Centre for optimisation calculations. Following the success of the toolkit a series of knowledge transfer sessions were arranged and completed.

The project team identified further requirements for providing additional support to smart motorways scheme delivery partners. The SMCALO toolkit has now been adopted by the Highways Agency and its delivery partners to calibrate and optimise smart motorway schemes without being reliant on external or third party support.

Solution

The task, which was completed in 2014, was delivered in stages with three key milestones – requirements definition, toolkit development and delivery, and knowledge transfer and training – were efficiently achieved.

With responsibility for the overall delivery we provided the:

  • Requirements definition report
  • Interim advice note
  • Scope of services
  • Delivery programme
  • Software architecture description
  • Software specification and design
  • Training programme and user manuals
  • Factory and site acceptance test
  • SMCALO toolkit

The toolkit also provides the Highways Agency with:

  • Simulation of signal output
  • Visualisation of traffic and signal data
  • Coordination of data analysis and secure storage of results
  • Automatic threshold suggestion
  • Detection of performance issues
  • Indicative performance measures
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