The current state of data on urban logistics traffic patterns is inadequate. The available data are often limited, inconsistent, outdated, and costly. Recent research explored innovative methods for collecting urban freight data and making it accessible to policymakers and researchers. It focuses on three case studies: Rotterdam (Netherlands), Brussels (Belgium), and Barcelona (Spain). These case studies reveal emerging data sources driven by traffic and parking policies, including automated number plate recognition (ANPR) cameras, a smartphone app for on-street deliveries, and a truck pricing scheme.
A recent study examined the context in which these new data sources are generated and the extent to which local stakeholders and the academic community utilize them. It then developed an analysis framework to assess the diversity of systems—both technical and socio-technical—that produce data relevant to urban logistics. This framework facilitates comparisons between different data sources, aiding future research efforts.
Findings indicate that local governments are more proactive in using these data than the research community. However, challenges related to data dissemination raise essential questions about costs (e.g., who should cover the expenses for storing, maintaining, and extracting datasets?) and regulatory considerations. The study recommends that local administrations work towards harmonizing data collection practices and data-sharing protocols to enhance the quality and comparability of urban logistics data. In countries where regulatory constraints limit access to new data sources, such as France, efforts should be made to create opportunities for data collection. Additionally, urban freight researchers should be encouraged to leverage the increasing availability of these data sources.
Key findings highlight that data from new sources, such as automated number plate recognition (ANPR) cameras, on-board units (OBUs), and delivery apps, are primarily used by local governments rather than researchers. These data sources, emerging from transportation policy initiatives to manage freight activities, often provide limited information due to their focus on specific aspects like vehicle monitoring or parking. For example, Rotterdam’s ANPR data only cover vehicles entering low-emission zones, while Belgium’s OBUs offer comprehensive spatial and temporal data but exclude light commercial vehicles.
The study emphasizes that despite the increasing availability of new data, traditional surveys and data-sharing with companies are still essential to capture comprehensive information on freight activities, such as cargo type, loading rates, and last-mile delivery methods (e.g., micro-mobility, e-commerce). Additionally, data access and dissemination issues raise financial and regulatory questions, including who bears the cost of data storage and maintenance and the conditions under which data are shared (e.g., through agreements or open data licenses).
Challenges in data access, mainly due to strict privacy regulations in countries like France and Germany, limit the use of advanced technologies for urban freight analysis. The research suggests local administrations should harmonize data collection methods to improve data quality and comparability. Collaboration with private stakeholders and adopting best practices from cities with more flexible data regulations could enhance urban freight data availability.
Ultimately, the research calls for the urban freight policy and research communities to leverage emerging data sources while also developing new skills to negotiate with private data providers. This approach would enable a more comprehensive understanding of urban logistics, thus supporting better policy-making and research.