The importance of upskilling our understanding of urban traveller behaviour

Abstract

Upskilling our ability to quantify urban traveller trip preferences and behaviour and incorporating these findings into urban transport policy development at all levels of government is a key requirement for successful transport project conceptualisation, planning, design, implementation, and evaluation. Transport planners and economists in South Africa have historically had limited insight into the trip making behaviour of urban and inter-urban travellers by means of their stated and / or revealed journey preferences. A consequence has been deficient transport project conceptualisation, design and operations planning for both public transport and roads schemes. The resulting adverse financial implications have been substantial and are enduring. Strategic urban transportation demand models that are used to provide scheme demand and revenue forecasts have developed the unenviable reputation of providing estimates that are far in excess of what has actually materialised, in large part due to inadequate mode and route choice behavioural modelling. The economic appraisals for urban transport projects, when undertaken, have not been transparent, and the provenance of key micro-economic measures such as the work and non-work related values of travel time (VTT) are uncertain. Transportation demand models cannot produce reliable demand forecasts without robust estimates of the value of travel time and cater for its heterogeneity with appropriate traveller market segmentation. Mode choice models themselves require careful design and a high degree of insight into trip making behaviour and user preferences and cannot forecast reliable mode shares without this. Using evidence from transport project case studies and recent research initiatives this paper demonstrates the importance and value for money proposition of upskilling our ability to quantify traveller preferences and incorporate these findings into urban transport policy, project design and operations, and transportation demand models.