The current lack of reference datasets of road traffic mobility for network simulation jeopardizes the reliability and reproducibility of vehicular networking research. We contribute to the ongoing effort to develop dependable and publicly available mobility traces through the following: (1) implementing an original version of the Simulation of Urban Mobility (SUMO) road network conversion tool that allows importing OpenStreetMap (OSM) data in a neat automated fashion; (2) generating an original dataset of road traffic in Bologna, Italy; and (3) providing a novel validation methodology that builds on open data provided by navigation service, which we leverage to assess the quality of the proposed Bologna dataset. These three contributions are expected to benefit the whole research community, since they not only provide a new ready-to-use realistic dataset that can be input to network simulators but ease the generation and validation of further vehicular mobility traces for networking research as well.

A lot of attention has been paid in the last years to urban freight transport (UFT) activities generated by specific market segments such as food, retail, or home deliveries, while relatively little attention has been paid to the transport of goods to and from construction sites in urban areas. Although transport of construction materials represents up to 30% of freight movements in cities and even more in terms of pollutant emissions. Using data collected over eight months in four construction sites, this paper provides a better understanding of the urban freight transport activity related to construction and presents the potential benefits of the implementation of construction consolidation centres (CCCs). A CCC is an innovative approach, which aims at increasing the efficiency and effectiveness of logistics processes by reducing the number of deliveries. Consequently, the use of a CCC in urban areas can reduce congestion and pollutant emissions due to construction freight movements. This paper presents results of CCC usage simulations for the four construction sites mentioned above. The results suggest that the distribution of goods to and from construction sites is peculiar as compared to other, better-known, urban supply chains and reinforce the call to researchers and decision makers from both private and public sides to devote more attention to this market segment.

Efficient logistics in urban areas is crucial for construction companies since building materials account for 30–40% of all construction costs and the space on site is highly constrained. To face these challenges, actions coming from both public and private decision-makers to find more sustainable solutions related to the distribution of building materials in urban areas become urgent. Although barely used in such contexts, can decision support systems be of support, and for who and for which purpose? This paper proposes a set of decision support systems addressing public and private decision-makers to improve the construction logistics and supply chain with evidence-based decision-making mechanisms. Those systems are, in particular, a public participatory geographical information system for determining the impact of policy measures, a consolidation center locator, a consolidation center planner, and an innovation measures selector. The paper explains how these decision support systems are settled and experimented from the analysis of pilot sites in European cities and in collaboration with the companies. Our diverse experiments demonstrate that data-driven decision-making is worth it to trigger thought on improvement measures for construction freight transport in urban area. We conclude that additional attention should be devoted to this specific sector.

Real-world data are key to the implementation and validation of urban transport models, and their availability and accuracy can dramatically affect the reliability of the resulting estimates. This paper discusses the potential of open data as a mean to gain insights in urban mobility, so as to supplement traditional methodologies that are often complex and expensive. We propose a methodology-fully based on publicly accessible data-for the development of Origin-Destination Matrices (ODMs). The methodology uses as input (i) a baseline morning-peak-hour ODM and (ii) road traffic count data. We test our proposed approach in a real-world case study, i.e., the city of Bologna, Italy. We also employ open geospatial data, from socioeconomic sources, to validate the ODMs, and find that these reproduce the typical urban travel demand profile in the target city during a whole day. Our results demonstrate the suitability of the methodology for transport policy design and urban planning. We also discuss current difficulties of gathering open data and the lessons learned when attempting to leverage such data.

This paper presents a model of a Local Energy Community (LEC) that is a set of users that share renewable sources and storage resources to satisfy energy demand while minimising carbon emissions and operating costs. The main contribution is the design of a planner that systematically assesses a target territory to cluster buildings into LECs while maximising an objective function. The planner leverages on a LEC simulation engine and the k-medoids clustering algorithm. The development demonstrate the feasibility of the approach and the results show the effectiveness of planner. It is worth noting that the planner paves the way for the implementation of a decision support system and the design of new business-oriented applications for smart urban and sub-urban areas in the energy domain.