Modelling Sydney's light commercial service vehicles. (February 2017)

• Record Type: Journal Article
• Authors: Ellison, Richard B.; Teye, Collins; Hensher, David A.
• Is Part Of: Transportation research. Volume 96(2017)
• Page Start: 79
• Page End: 89
• Publication Date: 2017-02
• Subjects: Light commercial vehicles -- Tour choice -- Stop choice -- Destination choice -- Sydney data; Transportation -- Research -- Periodicals; 388.011
• DOI: 10.1016/j.tra.2016.12.002
• Languages: English
• ISSNs: 0965-8564

Abstract

Abstract: A frequently overlooked source of trips in Sydney (and elsewhere) is light commercial vehicles (LCVs) used by tradesmen and other service workers to travel to customers to provide commercial services. Although these trips have substantial differences from other types of trips (and vehicles), they are frequently included either as standard passenger vehicles or, alternatively, as freight, if they are considered at all. However, light commercial vehicle trips used for commercial services comprise a substantial number of vehicle trips, particularly in areas with large concentrations of businesses such as the Sydney CBD and other growing business precincts, and for this reason should be included in travel demand models. As part of a large project involving the development of a comprehensive model system for predicting passenger, service and freight travel in Sydney (MetroScan-TI), this paper outlines the estimation and application of a set of models for service vehicles. The model system includes four models, a tour generation model, a tour type model, a Statistical Local Area (SLA) choice model and a destination (or travel zone) choice model. These models are estimated using data from a subset of the Sydney Household Travel Survey (HTS) involving work trips using LCVs, as well as detailed land-use and employment data from the 2011 Australian Census. We obtain a set of behaviourally rich and geographically detailed models that incorporate feedback through the use of several inclusive value (logsum) parameters. In addition to the overview of the model system, this paper discusses the estimation results and their application to policies.