The main objective of truck parking systems is to assist drivers in efficiently transporting goods by reserving the best available parking space on their route while ensuring compliance with existing regulations. This goal is particularly challenging due to the constantly changing environment in terms of availability of parking spaces, as well as factors that influence in traffic and affects driving to the rest area.

The DATEX II standard, originally conceived for traffic information exchange among control centers and road operators, has undergone a transformative journey, emerging as a fundamental European standard for open traffic data. Propelled by the ITS Directive, which positions DATEX II as the preferred language for traffic information publication at National Access Points, it stands as a cornerstone in the realm of open traffic data. This article explores the transformation of DATEX II, with a specific focus on the exemplary LOD-RoadTran18 project.

This paper discusses a segment of the "Artificial Intelligence and Semantics of Earth Observation (EO) data for the establishment of the Valencia Anchor Station as a supersite of the CEOS LPV Program (ASOTVAS)." The ASOTVAS project aims to apply AI and data semantics algorithms to the Valencia Anchor Station’s control zone (10 km x 10 km). A data semantics analysis explores concepts such as vocabularies, ontologies, and knowledge maps, with an emphasis on the reuse of existing models. Crucially, an ontological model with clear data definitions is developed to correlate Copernicus Program data with station parameters (e.g., FAPAR, LST, soil moisture, etc.). Using the ontology, the actual data are aggregated to create a knowledge map, which includes both an assertion model (concepts and properties) and an instance model (specific instances for ontological relationships). The main task is to develop an ontology-based representation scheme for terms of the application domain, which facilitates knowledge capture, distribution, and maintenance. The scheme enables computer processing for tasks related to information handling and supporting information exchange. Widely accepted ontology specification methodologies are employed. To avoid unnecessary efforts, emphasis is put on the reuse of existing ontologies or vocabularies, expanded, and adapted to the described case study. The optimal granularity is chosen for efficient ontology operation. The conceptual and technological requirements of the representation scheme are discussed. The methodology is based on software quality standards.

One of the objectives of the Smart Cities is the efficient and sustainable use of transport infrastructures. Sustainability is understood as the application of new technologies to minimize the loss of time and energy, and at the same time, to improve the satisfaction of citizens. Achieving this objective calls for making use of the mobility data collected from the existing transport infrastructure and services, as well as from the citizens themselves. After the data collection process, information must be stored (use of open data bases) and made accessible (available) to specialized applications and users. This paper highlights the opportunity to take advantage of emerging technologies, like the open source data platform CKAN, or to use services for data linked queries (SPARQL endpoint). As an example of application of these technologies to the transport domain, two use cases are presented: the proposed implementation of an information access point and a national project called “CONECTA”.

Weather is an important factor that affects traffic flow and road safety. Adverse weather situations affect the driving conditions directly; hence, drivers must be informed about the weather conditions downstream to adapt their driving. In the framework of intelligent transport systems, several systems have been developed to know the weather situations and inform drivers. However, these systems do not forecast weather in advance, and they need the support of road operators to inform drivers. This paper presents a new autonomous system to forecast weather conditions in a short time and to give users the information obtained. The system uses a set of algorithms and rules to determine the weather and to forecast dangerous situations on the road network. It has been implemented using a multiagent approach and tested with real data. Results are very promising. The system is able to forecast adverse situations with a high degree of quality. This quality makes it possible to trust in the system and to avoid the supervision of operators.

Traffic and road transport conditions are strongly influenced by the decisions of drivers. The more information they receive, the better decisions may be taken about their behavior. This is especially important in the transport of goods, since drivers are subject to traffic laws about maximum driving time and minimum time rest. In this paper a multi-agent system for negotiated management of parking spaces in road rest areas is presented. This system dynamically adapts itself to the preferences and needs of the drivers of goods about parking requests. The system is shown to be robust to incidents regarding the closure of road rest areas and an increased volume of freight traffic. The results also show that the number of illegal parkings is reduced resulting in greater road safety.

In this work we demonstrate a particular use of ontologies based on the European specifications DATEXII. These specifications are designed and developed as a traffic and travel data exchange mechanism by a European task force to set up and standardise the interface between traffic control and information centres. It is the reference for applications that are developed and implemented in Europe.

Road accidents are well correlated with bad weather conditions. In traffic management, several strategies have been considered in order to reduce this kind of accidents. Weather problems can cause difficult situations for the traffic management decision-makers. They need to analyze and absorb a large quantity of information in order to solve some problems due to bad weather. An automated agent-based system is a good solution to help decision-makers in the management of weather information to road users in relation to traffic conditions.

Currently, freight transport carried through a country or through different countries undergoes many delays due to merchandise controls. Merchandise control is only carried out at some border posts or when the authorities demand it. Such control can be an important problem since there are different laws for the same merchandise, according to the legislation of the country and even within the same country.