This paper introduces a simulation model designed as a decision-making tool to assess and analyze various crowd management strategies with a focus on enhancing sustainability in airport operations. This model specifically addresses the challenges and risks associated with managing passenger flows within airport terminals. By simulating different scenarios, the model aims to provide valuable insights into how to effectively handle crowd dynamics and enhance overall terminal efficiency, safety, and sustainability. This case study was conducted at Henri Coanda International Airport, ARENA 12 simulation software being used in order to model the passenger flows within the airport terminal. Two scenarios were considered: The first one involves maintaining a fixed number of security and check-in desks for the two airline groups. In contrast, the second scenario allows for a variable number of security and check-in desks for the same airline groups. By optimizing resource allocation and minimizing waiting time, this model contributes to more sustainable airport management operations. Three measures of performance (MOPs) were selected to assess the system activity: the average passenger waiting time, the average passenger number queue length, and the average utilization rate. Comparing the results, we concluded that the second scenario shows a relative improvement in almost all performance measures when compared to the first scenario.

The quality of service in transport terminals is differently perceived by engineers, economists, transport operators and sociologists. The traveler's perception is nevertheless decisive. The quality of service is well connected with the inside design of terminals, with the facilities in terminals and with the provided service standards. In order to provide a high level of service, the activities taking place in the public transport terminal and the maximum travelers flow size must be carefully analyzed and dimensioned. The purpose of modelling is to find the best route for each traveler from origin (entrance) to destination (exit) through all the intermediate service points, taking into consideration the instant network conditions. In developing the model we consider the walking, the waiting and the serving time. Using a simulation program written in ARENA we determine the waiting time. For validation, the model is used to evaluate the performance level in Bucharest Basarab station. By comparing the total walking distance for the possible routes and the utility function that describes the utility of all activities from entrance to exit we can find the optimal route.

To make possible the integration and harmonization as well as the orchestration of independent logistics operations, smart platforms and platform ecosystems are necessary to effectively connect the providers of sustainable transport solutions and those who need them. Since the beginning of 2023, incoming EU regulations regarding minimum standards for EU Climate Transition Benchmarks demand large companies to also report their emissions caused by subcontracting services. In response to this opening, we surveyed the past and ongoing experiences, we identified as well as explored the barriers that may determine a hindering effect, and we proposed an integrative framework for platform-based business models for sustainable logistics (PBM-SL) so as to contribute to designing business models for logistics, with the purpose of assisting any interested party in developing such a model for transport and logistics and of facilitating the insertion of sustainability issues among different platform solutions to optimize freight flows and drive logistics to climate neutrality.

As automation technologies continue to advance within the automotive industry, urban road traffic is gradually shifting from conventional driving toward fully autonomous. This transition is supported by the progressive integration of partially automated functions, such as Adaptive Cruise Control (ACC) and lane-keeping assistance, which are already implemented in commercial vehicles and increasingly affect both individual driving behavior and overall traffic flow dynamics. The main purpose of this research is to evaluate the impact of automated vehicles presence in a complex signalized intersection under mixed traffic conditions, considering different penetration rates and demand levels. A review of previous modeling approaches from the literature was conducted, highlighting critical aspects to be considered in the design and simulation of road traffic. Field traffic data were collected and used as input for a microsimulation model developed in AIMSUN. A base scenario and a 20% growth scenario were analyzed to assess the impact of AV-ACC penetration, varying the AV-ACC’s rates in traffic composition. The results indicate that increased AV-ACC penetration rates, especially beyond 50%, contribute significantly to improving traffic stability and efficiency.

The transit through a Border Check Point of cargo vehicles supposes, in the case of the Romanian highway network, the carrying out of a process of weighing and verifying of transport licenses. The limited number of weighing equipment and the long duration of these processes cause large queues and long waiting times. A solution for these problems is to use smart equipment to identify the cargo vehicles and to separate the vehicles that require weighing from exempted ones. The separation process is made using external input data. The quality of received data can generate some dysfunctionality in the separation process. The discrete simulation model can be used to evaluate the influence of the uncertainty over the system serving parameters. A study case is developed for a real situation using real data collected from a Romanian Highway Traffic Control Center (HTMC). The results are used in the implementation of the new smart equipment in a Romanian Border Check Point.

Automated parcel lockers (APLs) are transforming urban last-mile delivery by reducing failed distributions, decoupling delivery from recipient availability, optimizing carrier routes, reducing carbon foot-print and mitigating traffic congestion. The paper investigates the optimal design of APLs systems under stochastic demand and operational constraints, formulating the problem as a resource allocation optimization with service-level guarantees. We proposed a data-driven discrete-event simulation (DES) model implemented in ARENA to (i) determine optimal locker configurations that ensure customer satisfaction under stochastic parcel arrivals and dwell times, (ii) examine utilization patterns and spatial allocation to enhance system operational efficiency, and (iii) characterize inventory dynamics of undelivered parcels and evaluate system resilience. The results show that the configuration of locker types significantly influences the system’s ability to maintain high customers service levels. While flexibility in locker allocation helps manage excess demand in some configurations, it may also create resource competition among parcel types. The heterogeneity of locker utilization gradients underscores that optimal APLs configurations must balance locker units with their size-dependent functional interdependencies. The Dickey–Fuller GLS test further validates that postponed parcels exhibit stationary inventory dynamics, ensuring scalability for logistics operators. As a theoretical contribution, the paper demonstrates how DES combined with time-series econometrics can address APLs capacity planning in city logistics. For practitioners, the study provides a decision-support framework for locker sizing, emphasizing cost–service trade-offs.