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A park-and-ride (P&R) system is a set of facilities where private vehicle users can transfer to public transport to continue their journey. The main advantage of the system is decreasing the congestion in the central business district. This paper aims to analyze the most significant factors related to a Park-and-Ride facility location by adopting a combined model of Analytic Hierarchy Process (AHP) and Best Worst Method (BWM). The integrated model is applicable for complex problems, which can be structured as a hierarchy with at least one 5 × 5 pairwise comparison matrix (PCM) (or bigger). Applying AHP for at least 5 × 5 PCM may generate inconsistent matrices, which may cause a loss of reliable information. As a solution for this gap, we conducted BWM, which generates more consistent comparisons compared to the AHP approach. Moreover, the model requires fewer comparisons compared to the classic AHP approach. That is the main reason of adopting the AHP-BWM model to evaluate Park-and-Ride facility location factors for a designed two-level hierarchical structure. As a case study, a real-world complex decision-making process was selected to evaluate the Park-and-Ride facility location problem in Cuenca city, Ecuador. The result shows that the application of multi-criteria methods becomes a planning tool for experts when designing a P&R system.

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Cities play a fundamental role not only in the growth processes under the sustainability paradigm, but also as a driving-force behind economy and they constitute places of connectivity and innovation. More than two thirds of the European population live in urban areas and this percentage is continuously growing. Therefore, cities are fundamental hubs of the transport system, since most journeys start or end within urban areas. The direct consequence is that many of the negative transport externalities, such as congestion, road accidents and pollution, have the greatest impacts in these contexts. The European Commission emphasized integrated planning at all mobility level to enhance new forms of sustainable urban mobility, in order to reduce externalities associated with transport sector. In this view, the aim of this paper is to analyze the European guidelines for the development and the implementation of Sustainable Urban Mobility Plan (SUMP) and the corresponding Italian guidelines for the preparation of so-called “Piani Urbani della Mobilità Sostenibile” (PUMS). A comparative evaluation is proposed to emphasize the new paradigm of sustainable transport planning and highlight critical evidence between the European legal tools and their transposition at national level, also in the light of their recent updates. The results of this analysis lay the basis for the critical assessment of best practices and the review of related SUMP, in order to identify the key elements to assist traffic planners and managers in their decision-making procedures for the identification of successful strategies and the implementation of effective actions towards sustainable mobility.

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This paper presents the first results of an agent-based model aimed at solving a Capacitated Vehicle Routing Problem (CVRP) for inbound logistics using a novel Ant Colony Optimization (ACO) algorithm, developed and implemented in the NetLogo multi-agent modelling environment. The proposed methodology has been applied to the case study of a freight transport and logistics company in South Italy in order to find an optimal set of routes able to transport palletized fruit and vegetables from different farms to the main depot, while minimizing the total distance travelled by trucks. Different scenarios have been analysed and compared with real data provided by the company, by using a set of key performance indicators including the load factor and the number of vehicles used. First results highlight the validity of the method to reduce cost and scheduling and provide useful suggestions for large-size operations of a freight transport service.