Transport for the North – Realising the Vision of the Northern Powerhouse

Richard Bradley, Head of Data Modelling and Appraisal for Transport for the North (TfN) detailed how new approaches to old problems could gain new efficiencies in transport planning. In April 2018, TfN became the first sub-national transport body with statutory powers to influence national transport investment decisions and fund scheme development.

The focus of his presentation was to illustrate how data and modelling is supporting the transformation of the North. Being part (in fact leader) of a team developing bespoke transport modelling software got him to work with some of the great leading innovators in the modelling industry and gave him the opportunity to see the nuts and bolts of what is in a model. Being a rugby coach at Rochdale Rugby Union Football Club for 23 years has helped him see the importance of having a clear vision and a clear set of goals that are firmly linked to business needs.

It was obvious from the onset that there needs to be a rebalancing of the economy to get the North up to the same growth level as a UK average. An independent economic review highlighted key northern capabilities and defined top-down targets for employment, population and economic growth by local authority geographies.

Transport for the North – Realising the Vision of the Northern Powerhouse

Richard Bradley

The initial analytics in the Northern Powerhouse Project identified where many billions of pounds worth of investment was needed to gain efficiencies and improvements, these analytics also highlighted the negative effects of using aggregate models. There were two areas of transport modelling that had to be considered in this ambitious project for the north.

Supply modelling where network and service capacity was modelled, and demand modelling where people and their travel patterns were modelled. Ideally for transport supply efficiency, there would be spatial and temporal detail that closely modelled congestion and delays that could be experienced. Then for travel demand, the modelling would have to incorporate individuals and their travel patterns segmented to best represent their travel needs and their willingness to pay for services. After the top-down targets were identified, the team started to look at connectivity issues and where key changes were required in major city regions.

To understand the level of improvement needed, other European cities were benchmarked to compare evolutions and provide insight to assist in the development of top-down conditional journey time targets for cities in northern England. It was clear to all concerned that the development of a new, more focused representation of travel requirements across the days and the seasons was needed. Temporal and spatial data from mobile phones was harvested and analysed to provide insight into how to provide different and dynamic daily transport profiles, then all of this was incorporated within one regional model.

Work is continuing but so far results have been encouraging and massive improvements have been made. Further improvement would arrive in the future when the North has proven it is a good economic case for investment.