The rapid evolution of drone-assisted logistics for urban last-mile (ULM) delivery has garnered significant interest from both academia and industry. This article presents a comprehensive review of the state-of-the-art research and practical implementations of ULM systems, focusing on the use of unmanned aerial vehicles (UAVs) for the final stage of goods and parcel delivery in urban environments. The applicability of UAV-based logistics across various contexts, including urban and rural areas, is examined, with real-world case studies highlighted to demonstrate practical uses. Key methodologies and models employed in optimising UAV routing and operations are discussed, particularly those that enhance the efficiency and reliability of ULM. The critical advantages and limitations of drone-assisted last-mile logistics are analysed, providing insights into the operational, regulatory, and technological challenges. The discussion is further expanded by addressing emerging trends in UAV technology, as well as innovations in drone deployment strategies and the evolving regulatory landscape. In conclusion, potential theoretical advancements and future applications of ULM systems are outlined, with an emphasis on integrating drones into broader logistics networks and smart city frameworks. The insights offered aim to guide future research and practical developments in this rapidly advancing field.

This paper treats on-field observing data and then applying estimation procedures to estimate follow-up headway and critical headway at roundabouts....

This research is part of a broader investigation into innovative simulation-based approaches for improving traffic efficiency and road safety in roundabout corridors. These corridors, composed of successive roundabouts along arterials, present systemic challenges due to the dynamic interactions between adjacent intersections. While previous studies have addressed localized inefficiencies or proposed isolated interventions, this paper introduces possible replicable methodology based on a microsimulation and surrogate safety analysis to evaluate roundabout corridors as integrated systems. In this context, efficiency refers to the ability of a road corridor to maintain stable traffic conditions under a given demand scenario, with low delay times corresponding to acceptable levels of service. Safety is interpreted as the minimization of vehicle conflicts and critical interactions, evaluated through surrogate measures derived from simulated vehicle trajectories. The proposed approach—implemented through Aimsun Next and the SSAM tool—is tested on two real-world corridors: Via Aurelia Nord in Pisa (Italy) and Route de Marseille in Avignon (France), assessing multiple intersection configurations that combine roundabouts and signal-controlled junctions. Results show how certain layouts can produce unexpected performance outcomes, underlining the importance of system-wide evaluations. The proposed framework aims to support engineers and planners in identifying optimal corridor configurations under realistic operating conditions.

This research is part of a broader investigation into dynamic simulation-based approaches for enhancing traffic efficiency, road safety, and sustainability in roundabout corridors and/or road corridors in general. The study emphasizes the need to analyze road intersections as interconnected systems rather than isolated components, aiming to better understand and mitigate counterintuitive phenomena known as traffic paradoxes, including the well-known Braess Paradox. The first section introduces the main traffic paradoxes, exploring their definitions, real-world implications, and reproducibility in roundabout corridors. The second section focuses on a case study of the “SS1—Via Aurelia Nord” in Pisa (Italy), where converting a traffic-light-controlled corridor into a roundabout corridor unexpectedly led to increased congestion. This paradoxical outcome is analyzed within the broader context of network dynamics and sustainable mobility planning. Dynamic simulations were performed using Aimsun software, and a novel performance index—the “Celerity Roundabout Corridors” (CRC)—was proposed to quantify and detect these paradoxical effects. The findings highlight conditions under which roundabout corridors may generate inefficiencies despite infrastructural upgrades, emphasizing the importance of systemic, simulation-based evaluations for the sustainable design and optimization of urban traffic networks.

Intelligent Transportation Systems (ITS) play a central role in the development of more efficient, adaptive, and resilient road networks. Traffic control strategies have progressively evolved from traditional approaches toward more intelligent and adaptive frameworks. This paper presents a taxonomy-based perspective on intelligent traffic control strategies for road networks, organizing existing approaches according to three complementary dimensions: control scope, decision-making mechanism, and control architecture. Based on this framework, the paper discusses representative methodologies, including rule-based control, model-based methods, simulation-based optimization, data-driven and artificial intelligence-based methods, and emerging cooperative strategies enabled by connected and automated vehicles (CAVs). The analysis also examines key application domains, such as traffic signal control, ramp metering, CAV-based traffic management, and simulation platforms, highlighting their operational principles, advantages, limitations, and implementation challenges. Particular attention is given to the transition from local and reactive control toward coordinated, predictive, and learning-based traffic management systems. The paper identifies major challenges related to scalability, robustness, interpretability, safety, real-world deployment, and the gap between simulation performance and practical implementation. The proposed taxonomy also supports practical comparison and preliminary selection of context-specific strategies. Future directions point toward integrated and hybrid frameworks combining data-driven adaptability, vehicle–infrastructure cooperation, and digital twin technologies.

In this paper a methodology to design a last mile freight transport system in urban areas based on platoons of automated vehicles (AVs) and two levels of dynamic Split Up Locations (SULs) is presented. Each long platoon of AVs travels from the UDC to a first dedicated place, near the city centre, where the long platoon is split up into shorter ones: this place is called 1st level (external) SUL. Then each short platoon travels towards a 2nd level (internal) SUL, where it is definitely broken. 2nd level SULs are located on the border of pedestrian-only zones of city centres. Then each single AV continues the delivery trip to receivers in the pedestrian areas. After completing deliveries, each AV is redirected to the best 2nd level SUL. The destination 2nd level SUL is chosen in order to simultaneously minimize: the waiting times at SULs for the other AVs forming the platoon, and the travel time of each AV from the position of the last receiver to the SUL. Then AVs gather again into short platoons, that, at the 1st level SUL, reassemble into long platoons, which finally return to the UDC. Again, the 1st level SUL is assigned dynamically to the short platoons by the supervisor, following the same criteria adopted for the assignment of 2nd level SULs. The system design has been formulated as a three-echelon Vehicle Routing Problem with satellites, where two levels of SULs play the role of bi-level satellites and the UDC plays the role of the depot. The system has been designed by means of a micro simulator, especially as regards the choice of the destination SUL, as well as the aggregation of AVs in platoons. The simulator embeds: a clustering algorithm, a genetic algorithm, and a routing algorithm, that optimize: the positions of 1st and 2nd level SULs, the single AV routes from the 2nd level SULs to receivers, the large and short platoon routes. This framework is referred as the three-echelon (3E) dynamic scenario, which will be compared against two alternative scenarios featuring only a single level of SUL: a static scenario, in which AVs, after completing their deliveries, return to the same starting SUL, effectively maintaining the same platoon as on the outbound trip; a dynamic scenario; and the current situation.