Client: Docklands Light Railway (DLR)

Year: 2012

The Docklands Light Railway (DLR) was built in the late 1980s and has grown and evolved over 30 years, including a suite of major improvements that were prepared for the 2012 London Olympics. The DLR has been a great success in supporting the regeneration of East London, but now often reaches capacity at key pinch points on the network in the peak whilst remaining quiet at most off-peak times. Transport for London (TfL), wanted to better understand demand and patronage for services, particularly to inform their plans to attract the off-peak market.  

SNC-Lavalin Transport Advisory, working with The Railway Consultancy (RCL), was commissioned to undertake a comprehensive review of the DLR market, with a particular focus on the off-peak.  For all of our market analyses we focus on understanding the customer – what drives their decisions and how we can influence those drivers. 

For this assignment we undertook a series of customer engagement exercises to collect primary data about these choices and behaviours. This data was collected through passenger surveys and focus groups and supplemented with further information collected from interviews with local government officials and businesses across the routes. 

This data was used to define our demand forecasting parameters for the inter-peak and evening-peak markets. Using these parameters we built a model using an approach consistent with TfL’s AM peak model, so that results and outputs would be in metrics familiar to TfL and their stakeholders. As well as providing a model to our client, we also made recommendations for increasing the use of the DLR at off-peak times. Subsequently the model was used to specify service levels for the recent re-franchising of the operation.

As a result of the quality of the main commission, TfL requested that we extend our remit to forecast potential demand for an all night service at weekends, to be integrated with the interconnected London Underground service.  We used night bus boarding data and journey time analysis, supplemented with a late night passenger survey, to predict how many passengers would use this service.

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Keith Foley
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