A theoretical framework to evaluate the traffic impact of urban freight consolidation centres

Abstract

City logistics and goods movement using road freight is an outcome of the economic activities that sustain urban life. However, they produce negative externalities like traffic congestion and pollution. There are key areas within cities that are largely affected by logistics activities, such as commercial centres and retail districts. These locations attract many freight vehicles attempting to fulfil deliveries, often with limited parking supply. This results in long queues of delivery trucks waiting for parking spaces or illegal kerbside parking. Therefore, urban planners and decision-makers are motivated to initiate policies that can mitigate these impacts. Urban freight management policies like delivery time or truck size restrictions, and Urban Consolidation Centres (UCC) have been proposed as potential solutions. A UCC is a facility that allows deliveries to be consolidated before entering a busy commercial area. The focus of this study is to offer a theoretical framework for predicting the impact of a UCC on the number of freight trips attracted to a retail district in any city. A mathematical model is developed and used to analyse two possible policy cases concerning the location of a UCC: one where the UCC is located within the retail district, and another where the UCC is located outside the retail district. This model is subsequently applied to examine a retail district in Singapore using real-world data. The critical level of participation in a UCC scheme required for the retail district to experience fewer freight trips is characterised. The results show a diminishing marginal benefit associated with achieving greater consolidation by operating the UCC. This contribution offers a theoretical explanation for the traffic impacts of urban freight consolidation, and aids with the development an ex-ante evaluation of a UCC. The model may be readily applied to any city considering this initiative, by adjusting the model parameters for local conditions.