New ways of collecting urban freight traffic data and applications for urban freight policies and research

The current quality of data on urban logistics traffic patterns is poor. Data are scarce, heterogeneous, often old and expensive to collect. This research looks at new ways to collect urban freight data and make that data available to both policy-makers and academia. Three case studies are examined: Rotterdam, the Netherlands; Brussels, Belgium; and Barcelona, Spain. They help identify new sources of data from traffic and parking policies: automated number plate recognition cameras, an on-street delivery smartphone app, and a truck pricing scheme. Both the context in which new data sources of interest to urban logistics are produced, and the level of appropriation of these data by local stakeholders and the research community are examined. We then construct an analysis grid to evaluate the diversity of systems (technical and socio-technical) producing data relevant to urban logistics. This analysis framework can be used to facilitate comparisons between data sources and thus help future case studies. In the three cases, we found that local governments use the data more than researchers do. The issue of data dissemination raises questions about costs (who is to bear the cost of storing, maintaining and extracting data sets?) as well as regulatory questions. We conclude that local administrations should be encouraged to work towards harmonizing data collection methods and data sharing conditions in order to improve the quality and comparability of the data. Cities in countries with little access to new sources of data, such as France for regulatory reasons, should try to find ways to create data source opportunities. In all countries, urban freight research communities should be encouraged to use the now increasingly available data.