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.

This work proposes a new route calculation algorithm to enhance traffic flows, based on traffic forecast. The forecasted traffic represents the speeds on itinerary segments during specific time periods, serving as the foundation for the algorithm that evaluates real-time travel time on each segment to define the best itinerary. The proposed algorithm involves the application of the A* algorithm taking use of traffic forecast for each covered segments in the route. By incorporating real-time traffic predictions, the algorithm becomes more adaptive, offering users dynamically adjusted routes that anticipate and navigate through changing traffic scenario. The algorithm has been implemented, tested and evaluated in a existing multi-agent framework. A extension of agents, concretely segment and vehicle agents, has been required to test the proposal. The results obtained show that the use of the algorithm have a positive impact on traffic flow: vehicles modifies their behaviour and use the existing alternative route with better travel times.

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.

Road transport plays a big role in the current society and in the transportation domain. Long distance journeys have restrictions to guarantee road safety. Drivers have restrictions regarding driving times and rest periods. So, they must stop in rest areas. Drivers need real-time information about the most convenient rest area and their parking availability. Furthermore, negotiation is required to coordinate where vehicles are allowed to park to comply with parking time directives. In this paper, a new negotiation protocol is presented to support drivers in the election of an adequate rest area. The negotiation protocol combines a reservation system with a voting-based negotiation. The voting protocol is based on Borda voting system but it includes some modifications to be adjusted to the particularities of the transportation domain. The negotiation protocol has been tested in a real test-bed environment. The results obtained have been positive with respect to a proper distribution among the vehicles involved and the rest areas.

Several resources must be devoted to deal with the management of a traffic accident. However, these resources are managed by several independent agencies. The current solutions to coordinate the resources of these agencies are being provided manually by using centralized systems, obviating the distributed nature of the problem. This paper presents a new distributed combinatorial auction PAUSE based protocol suitable to be used in these types of situations. The main innovation in this new protocol is that it allows to allocate efficiently resources grouped by types. In addition it can exploit the existing synergy between the resources provided by any single agency. A multiagent system, MAS, has been programmed to evaluate the performance of this protocol in the traffic accidents domain. The assignments of resources proposed by this MAS show that the protocol provides efficient solutions close to the optimal ones.

In the last decade, the use of new technologies in the transportation domain has made possible the development of the Intelligent Transport System (ITS). However, the ITS services were deployed isolated. The purpose of the EasyWay Project is to involve all the European countries to deploy harmonized ITS services taking into account the European citizen as final

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.

The present paper describes the main characteristics and components of the tool developed for integrating the definition of profiles for semantic web services. This tool is based on the languages DAML-S and OWL-S and it includes the ontology visualization and consistency verification that specify the concepts a web service interacts with. Starting from a service description interpreted by a computer and by the means used for accessing the service, it is possible to find out which software agents use the service. The tool can generate information in different formats, such as the SVG format proposed by the W3C, for representing graphic information based on XML. The tool was developed in Java language and is being used for the visualization of ontologies and for the semantic description of services in traffic information systems that the LISITT group (Laboratorio Integrado de Sistemas Inteligentes y Tecnologías de la información de Tráfico) developed at the Robotics Institute at the University of Valencia.

The Transportation and traffic domain is cross-disciplinary; Different areas must be covered to solve complex problems. It also involves the use of different systems for monitoring, visualization, information distribution, control, communication, etc. All of these systems are implemented using different levels of technology. In most cases the control of these systems is handled by [graphic] user interfaces. In the past years the number of systems has grown substantially and because of their "monolytic" design, they have different and in most cases not-compatible user-interfaces. A generic interface would be useful to improve not only the different processes but also the efficiency of the operator