Pedestrian Regeneration Analysis Model (PRAM) - Modelling the Effects of Pedestrians on Regenerating a Town Centre



Pedestrian Regeneration Analysis Model (PRAM) - Modelling the Effects of Pedestrians on Regenerating a Town Centre

Authors

A Chandra, P Sumner, A Michea, Colin Buchanan, UK

Description

A Pedestrian Regeneration Analysis Model (PRAM) to evaluate impact of large retail developments in attracting shopping trips to a town centre. PRAM has been developed over two years of study while applying the methodology on multiple case studies.

Abstract

Town centres have a historic role in providing a wide variety of retail facilities for residents of the surrounding area. The location of these retail development can have a considerable impact on level of activity within the town centre. Large developments attract substantial number of shopping visitors which may increase pedestrian footfall in the town centre and regenerate it, although the development may also draw trade away from existing retail within the town centre. The question which Colin Buchanan (CB) has been regularly asked is: how can these regeneration impacts be quantified?

CB has developed a Pedestrian Regeneration Analysis Model (PRAM) which can be used to evaluate the effects of large retail developments in attracting shopping visitors to a town centre. PRAM is a result of over two years of study and development while applying the methodology on multiple case studies. Till date, the model application has been developed for four different town centres around London and South East England, including Kingston, Dartford, Brighton and Woolwich.

For each of the above studies, a Saturday afternoon peak hour scenario model was developed representing peak retail activity. PRAM has two main components. The first component is a strategic model which identifies demand for the studied town centre relative to other competing town centres in neighbouring regions. The unit of attractiveness for each town centre is retail rateable value. PRAM also has a module which feeds back increase in shopping rateable value with increasing pedestrian density while converging the overall level of demand. The rateable value can increase if the quantity of retail floor space increases, and also if the quality of retail increases leading to more shopping visitors. A new retail development may have both of these effects.

The second component of the model includes a 'microscopic' model representing pedestrian movements around the town centre. It is noted that some visitors may visit more than one shop and the model represents a series of matrices to reflect the average number of shops visited at each stage (although trip chains themselves are not modelled). The pedestrians are assigned on the basis of an attraction based route choice model, which takes into account route length and overall path environment using PERS (Pedestrian Environment Review System, TRL) based scoring.

The demand model is segmented between visitors doing food and non-food shopping trips. It is also segmented between visitors that visit just one shop and those that visit multiple shops. There is also an extension to the demand to represent visitors to the town centre that visit for other leisure purposes eg a cinema or cafe.

The present paper describes, in detail, the methodology adopted for the development of above models, calibration and validation techniques, and overall lessons learned from the development of PRAM.

Publisher

Association for European Transport