Modern urban highways are under the influence of increased traffic demand and cannot fulfill the desired level of service anymore. In most of the cases there is no space available for any infrastructure building. Solutions from the domain of intelligent transport systems are used, such as ramp metering. To cope with the significant daily changes of the traffic demand, various approaches with autonomic properties like self-learning are applied for ramp metering. One of these approaches is reinforced learning. In this paper the Q-Learning algorithm is applied to learn the local ramp metering control law in a simulation environment, implemented in a VISSIM microscopic simulator. The approach proposed is tested in simulations with emphasis on the mainstream speed and travel time, using a typical on-ramp configuration.

Efficient traffic systems control in large cities, and the complex traffic management of signalized intersections is a challenging task, particularly when dealing with high traffic volumes. The city of Zagreb faces this challenge, as all administrative and governmental institutions are in the historic part of the city, and routes for escorted vehicles have a significant impact on the traffic network. This paper addresses the issue of the impact of unconditional priority for escorted vehicles on the energy efficiency of the urban traffic network in the city of Zagreb. The traffic network model is developed using the PTV Vissim microsimulation software. The evaluation was conducted with nodes (delay, queue length, and number of stops) and network evaluation parameters (CO₂ emission, NO_x emission, PM₁₀ emission, and fuel consumption). The results show that unconditional priority has minimal impact on energy consumption and exhaust emission in the observed scenario. This is a significant result considering all actions that must be undertaken to manage the passage of the escorted vehicles through the traffic network.

Efficient traffic systems control in large cities with complex traffic management of signalized intersections is a challenging task, particularly when dealing with high traffic volumes. The city of Zagreb faces this challenge, as all administrative and governmental institutions are located in the old city centre, and routes for escorted vehicles have a significant impact on the traffic network. This paper addresses the issue of the impact of unconditional priority for escorted vehicles on the energy efficiency of the urban traffic network in the city of Zagreb. The traffic network model is developed by using the PTV Vissim microsimulation software. The evaluation was conducted with node (delay, queue length, number of stops) and network evaluation parameters (CO2 emission, NOx emission, PM10 emission, and fuel consumption). The results show that unconditional priority has minimal impact on energy consumption and exhaust emission in the observed scenario. This is a significant result considering all actions that have to be done to manage the passage of the escorted vehicles through the traffic network.

Effective teaching methods for the coming generations of pragmatic students and teachers are evolving towards much greater involvement on all sides, attempting to bridge real life and academia in innova-tive ways. Our theoretical foundation lays upon the Triple Helix, n-Tuple Helix theory and the innova-tion triangle, but in a problem-based multidisciplinary setting. After introducing and validating the Mul-tiCreation approach in teaching/learning for the business-academia collaboration, where multiple disci-plines, diverse profiles of students, professors, and managers have taken up various roles to address relevant business issues, we were encouraged to expand its applicability beyond the business world - toward societal problems. We retained the problem-based and participatory learning but shifted the positioning of the problem towards the safety of primary school children, incorporating economic, pro-ject-based, managerial, traffic engineering, logistical, regulatory, and governance issues. By including two primary schools, collaborating with their principals, advisory teams, and teachers, as well as chil-dren and parents, in two different cities, we aimed to provide complete research, engineering and educa-tion for the stakeholders so that the schools could just hand in documentation to the relevant municipal bodies to be acted upon effectuation. The involved students came from two faculties -of economics and traffic engineering, steered by three university professors on the subjects of project management and basic and advanced techniques for traffic management. The blended learning components took place as prescribed in the MultiCreation approach, during two semesters of two academic years. They combined countermeasures and solutions. The MultiCreation approach has been enhanced regarding its components and workflow and its effectiveness has been validated in a multi-stakeholder environ-ment of direct and indirect educational beneficiaries.