With the acceleration of urbanization and the advent of autonomous driving technology, urban traffic systems are gradually evolving into a mixed traffic flow environment where Human Driven Vehicles (HAVs) and Connected and Automated Vehicles (CAVs) coexist. Conventional urban traffic control is primarily based on traffic lights with fixed or adaptive logic, as other means of actuation are not traditionally in use (except for tolling systems, which are rather indirect regulators). Traditional traffic signal control, however, is limited due to its rigidity; traffic lights are located at fixed spots with a strict operational mechanism (cycle time, phase order, offset), making them less efficient in managing a mixed traffic environment. To address this challenge, this paper follows a novel approach leveraging the Variable Speed Limit (VSL) control in the urban context. The control framework is based on Multi-Agent Reinforcement Learning (MARL), aiming to optimize road sustainability under mixed traffic flow conditions. This study employs a Centralized-Training Decentralized-Execution (CTDE) architecture, utilizing the Multi-Agent Proximal Policy Optimization (MAPPO) algorithm to address the curse of dimensionality and non-stationarity issues in large-scale urban road networks. This framework enables collaborative decision-making in both space and time through the use of shared parameters and global value function evaluation. The method is validated via realistic traffic simulation experiments in Simulation of Urban MObility (SUMO), demonstrating that the proposed control strategy can significantly reduce travel time, pollutant emissions, and improve traffic safety on the studied urban network under different traffic conditions.

A plethora of Artificial Intelligence (AI) based methods have been published for adaptive traffic control. However, the demonstration of real-world applications is often overlooked. An effective and widely accepted solution for traffic signalization is the use of Programmable Logic Controllers (PLCs), especially in safety-critical infrastructures. This paper presents a reinforcement learning (RL)-based traffic control system deployed directly on an industrial PLC, representing a fundamentally novel integration of AI in a deterministic control environment. In contrast to prior approaches that focus solely on optimization, our system ensures compliance with strict traffic safety rules by restricting the agent’s action space using a safety constraint matrix. Despite limited computational resources, the system achieved measurable improvements in CO2 emissions while maintaining safe and stable runtime behavior. The results confirm that AI-based control is not only feasible but reliable on PLCs when supported by appropriate architectural and safety mechanisms, opening pathways for further industrial AI deployments.

Road infrastructure has evolved to meet diverse needs over time. This makes modernizing traffic control systems also necessary in order to keep pace with technological innovations and changing user habits. This paper presents a novel design and implementation strategy for the next generation of traffic control systems, with particular emphasis on the challenges posed by the integration of automated vehicles. General flexibility in future traffic management, proper use of standardized communication protocols, and safety solutions are essential factors in addressing the traffic challenges of the coming decades. The system has been developed primarily for PLCs (Programmable Logic Controllers) and has been tested and verified, providing the advantages of safety elements and software safety solutions. The proposed system demonstrated efficient and reliable performance while the applied OPC UA (Open Platform Communications Unified Architecture) communication protocol assured robustness and secure client-to-PLC communication.

Platooning is generally known as a control method for driving a group of connected and automated vehicles in motorway context. Nevertheless, platoon control might also work on urban roads. One possible strategy to increase overall road traffic performance and to reduce congestion in urban traffic networks is to combine platooning with traffic signal control at intersections. The traffic flow can be maximized with coordinated scheduling of traffic signals together with platooning activities, resulting in decreased travel times and fuel consumption. This paper investigates several aspects of this combined control, such as the procedures for coordination and communication between platooning vehicles and traffic signals. Efficient algorithms are suggested to optimize platoon formation and dissolution at junctions and to change traffic signal phases depending on platoon arrival and departure times. The proposed solutions have been tested and verified with SUMO, a high-fidelity microscopic traffic simulator.

The present paper's focus is the V2X (Vehicle-to-Everything) communication between traffic light controller and road vehicles. After a brief review on the state-of-the-art V2X communication technologies and their feasibility for practical implementation, a brief description of their potential is discussed providing a working solution for SPaT/MAP (Signal Phase and Timing and MAP as intersection geometry) standard based communication, specifically for automotive proving ground usage. The main outcome of the proposed solution is a full y flexible traffic control system applying industrial PLC while ensuring a standardized V2X protocol. As a demonstrative HiL (Hardware-in-the-Loop) example, exploiting the elements of the traffic management system at the ZalaZONE Automotive Proving Ground, a GLOSA (Green Light Optimal Speed Advisory) scenario is presented with the developed SPaT/MAP V2X communication realizing a global optimum traffic control solution. The more, the whole framework is designed in a way that it is capable of using mixed reality components for testing purposes and realizing a digital twin for traffic lights. The method of virtualization for V2X communication is introduced using a co-simulation framework of three common software tools (SUMO, Veins, and OMNeT++).

The in situ application of the combination of different types of drugs revolutionized the area of periodontal therapy. The purpose of this study was to develop nanocomposite hydrogel (NCHG) as a pH-sensitive drug delivery system. To achieve local applicability of the NCHG in dental practice, routinely used blue-light photopolymerization was chosen for preparation. The setting time was 60 s, which resulted in stable hydrogel structures. Universal Britton–Robinson buffer solutions were used to investigate the effect of pH in the range 4–12 on the release of drugs that can be used in the periodontal pocket. Metronidazole was released from the NCHGs within 12 h, but chlorhexidine showed a much longer elution time with strong pH dependence, which lasted more than 7 days as it was corroborated by the bactericidal effect. The biocompatibility of the NCHGs was proven by Alamar-blue test and the effectiveness of drug release in the acidic medium was also demonstrated. This fast photo-polymerizable NCHG can help to establish a locally applicable combined drug delivery system which can be loaded with the required amount of medicines and can reduce the side effects of the systemic use of drugs that have to be used in high doses to reach an ideal concentration locally.

The testing of Connected and Automated Vehicles (CAVs) and that of the smart infrastructure (traffic control devices and vehicle sensors) in relation with CAVs will be supported by the development of a novel type of road traffic light management system at ZalaZONE Automotive Proving Ground.The system to be developed aims to allow a fully flexible traffic signal control during vehicle and system testing.The system shall provide a freely programmable open Application Programming Interface (API) towards the traffic light control units in contrast with traditional (rigid and closed) traffic control equipments.In this concept, each traffic light control unit will be made available via a remote control software running on a cloud system.

Road traffic congestion has become an everyday phenomenon in today's cities all around the world. The reason is clear: at peak hours, the road network operates at full capacity. In this way, growing traffic demand cannot be satisfied, not even with traffic-responsive signal plans. The external impacts of traffic congestion come with a serious socio-economic cost: air pollution, increased travel times and fuel consumption, stress, as well as higher risk of accidents. To tackle these problems, a number of European cities have implemented reduced speed limit measures. Similarly, a general urban speed limit measure is in preparatory phase in Budapest, Hungary. In this context, a complex preliminary impact assessment is needed using a simulated environment. Two typical network parts of Budapest were analyzed with microscopic traffic simulations. The results revealed that speed limits can affect traffic differently in diverse network types indicating that thorough examination and preparation works are needed prior to the introduction of speed limit reduction.

Urban commuters have been suffering from traffic congestion for a long time. In order to avoid or mitigate the congestion effect, it is significant to know how the introduction of autonomous vehicles (AVs) influence the road capacity . The effects that AVs bring to the macroscopic fundamental diagram (MFD) were investigated through microscopic traffic simulations. This is a key issue as the MFD is a basic model to describe road capacity in practical traffic engineering. Accordingly, the paper investigates how the different percentage of AVs affects the urban MFD. A detailed simulation study was carried out by using SUMO both with an artificial grid road network and a real-world network in Budapest. On the one hand, simulations clearly show the capacity improvement along with AVs penetration growth. On the other hand, the paper introduces an efficient modeling for MFDs with different AVs rates by using the generalized additive model (GAM).

A parodontális kezelések során a mechanikus terápia kiegészítésére alkalmazhatók olyan kémiai anyagok, melyekkel a szájban fellelhető patogén baktériumok szaporodása visszaszorítható, a gyógyulási folyamat elősegíthető. Ennek egyik eszköze lehet a PerioChip® is, mint egy klórhexidin-glükonát (CHX) leadására képes rendszer. Jelen munkánk célja ezen rendszer hatóanyag-leadó tulajdonságának vizsgálata különböző pH-jú puffer oldatok alkalmazása során. Munkánkat 4–12 pH tartományban végeztük el univerzális Britton-Robinson puffert, illetve 7,4-es pH-jú PBS puffer oldatot alkalmazva kioldódási közegként. A kioldódást 1 hét időintervallumon követtük figyelemmel, és a kioldódott CHX men- nyiségét HPLC módszer segítségével határoztuk meg. A savas pH kedvező hatással volt a kioldódásra, gyors ütemben szabadult fel a hatóanyag 86,9%-a, de még pH 6 esetében is közel 80%-os volt a hatóanyag-leadás. Mindezek bázikus pH-n jelentősen kisebb értékeket mutattak, pH 8 esetében közel 40%, míg pH 10, és pH 12-nél már csak 30%-os nagyságrendbe estek. Eredményeink szerint a pH-változásnak jelentős hatása van a kioldódott CHX mennyiségére, és a kioldódás dinamikájára is.

Though the antibacterial effect is advantageous, silver and silver nanoparticles can negatively affect the viability of human tissues. This study aims to check the viability of cells on surfaces with different particle size and to find the biologically optimal configuration. We investigated the effect of modified thickness of vaporized silver and applied heat and time on the physical characteristics of silver nanoparticle covered titanium surfaces. Samples were examined by scanning electron microscopy, mass spectrometry, and drop shape analyzer. To investigate how different physical surface characteristics influence cell viability, Alamar Blue assay for dental pulp stem cells was carried out. We found that different surface characteristics can be achieved by modifying procedures when creating silver nanoparticle covered titanium. The size of the nanoparticles varied between 60 to 368 nm, and hydrophilicity varied between 63 and 105 degrees of contact angle. Investigations also demonstrated that different physical characteristics are related to a different level of viability. Surfaces covered with 60 nm particle sizes proved to be the most hydrophilic, and the viability of the cells was comparable to the viability measured on the untreated control surface. Physical and biological characteristics of silver nanoparticle covered titanium, including cell viability, have an acceptable level to be used for antibacterial effects to prevent periimplantitis around implants.

A set-theoretical approach is presented for a multi-objective control design of the local ramp metering problem. Two control objectives are specified: first, the optimization of traffic performance, by the minimization of total time spent. Second, the emission factor of CO2 needs to be minimized. The optimal state for traffic emission, however, lies in the unstable domain of the dynamic system. To dissolve this inconsistency, the control problem is formalized for the multi-objective optimization problem by using set-theoretical methods. For this purpose, the non-linear model METANET is rewritten in a shifted coordinate frame with a parameter-varying, polytopic representation. Bounds on state-, input- and disturbance variables are expressed by convex polytopes. These sets are then used for the design of an interpolated H∞ controller that is capable of improving traffic conditions according to the prescribed multi-objective criteria.

The management of periodontal disease is frequently aided by the use of local antimicrobial adjuncts to therapeutically support mechanical debridement. Various antimicrobial agents have been shown to be effective against putative periopathogenic microorganisms, thereby promoting the healing processes. PerioChip®, as a locally delivered chlorhexidine gluconate (CHX) controlled releasing system, is such a local antimicrobial adjunct. The aim of this study was to determine the CHX release profile of the PerioChip® system in different pH buffer solutions. Phosphate-buffered saline (PBS) at pH 7,4 and universal Britton-Robinson buffer solutions in the range of pH 4–12 were used as releasing mediums. The total period of release was 1 week. The amounts of released CHX were measured by HPLC. Acidic pH showed a positive effect on the release rate and speed. The rate and speed of release were fastest at pH 4, when 86,9% of the embedded antimicrobial agent was released from the gel. In contrast, the observation was notably different in an alkaline pH environment. A 39% release was noted at pH 8 which decreased to 27% at pH 10. These findings suggest that the pH of a medium has a significant impact on the dynamics of the local release process of adjunctive chlorhexidine gluconate from the PerioChip® system, thereby playing an important role in the bioavailability of the antimicrobial therapeutic agent in the combat of periodontal disease.

hanem a közlekedésmérnökök számára is új kihívásokat támaszt

Traffic control of urban areas is a current research topic. Different pricing regimes such as cordon pricing, time-based average cost zone pricing, distance-based average cost zone pricing or marginal cost zone pricing have been investigated so far. The economical best solution, however, cannot be used due to the lack of information. In the study, the future of road pricing together with traffic control is analysed with the assumption of widespread information and communications technology (ICT) usage, i.e. access to real-time information. The study proposes a utility-based dynamic road pricing for optimal traffic flow management. The research largely focused on the model and regulator definition [fixed, dynamic, and non-linear model predictive control (MPC)]. The theoretical research was conducted on a real-world traffic test network by applying different control methods and taking into account the time-delay effect of traffic forecasting. The simulation results show that time delay in response to vehicle concentration can result in significant oscillation on the concurrent routes in case of fixed and dynamic control, but can be compensated by non-linear MPC. As a major result, it is shown that with the market penetration of ICT, a new era of road tolling regimes could be introduced.

Objectives: Using dental Ti implants has become a well-accepted and used method for replacing missing dentition. It has become evident that in many cases peri-implant inflammation develops. The objective was to create and evaluate the antibacterial effect of silver nanoparticle (Ag-NP) coated Ti surfaces that can help to prevent such processes if applied on the surface of dental implants. Methods: Annealing I, Ag ion implantation by the beam of an Electron Cyclotron Resonance Ion Source (ECRIS), Ag Physical Vapor Deposition (PVD), Annealing II procedures were used, respectively, to create a safely anchored Ag-NP layer on 1x1 cm2 Grade 2 titanium samples. The antibacterial effect was evaluated by culturing Staphylococcus aureus (ATCC 29213) on the surfaces of the samples for 8 hours, and comparing the results to that of glass as control and of pure titanium samples. Alamar Blue assay was carried out to check cytotoxicity. Results: It was proved that silver nanoparticles were present on the treated surfaces. The average diameter of the particles was 58 nm, with a 25 nm deviation and Gaussian distribution, the the filling factor was 25%. Antibacterial evaluation revealed that the nanoparticle covered samples had an antibacterial effect of 64.6% that was statistically significant. Tests also proved that the nanoparticles are safely anchored to the titanium surface and are not cytotoxic. Conclusion: Creating a silver nanoparticle layer can be an option to add antibacterial features to the implant surface and to help in the prevention of peri-implant inflammatory processes. Recent studies demonstrated that silver nanoparticles can induce pathology in mammal cells, thus safe fixation of the particles is essential to prevent them from getting into the circulation.