José Fernando García

An autonomic system for intelligent truck parking

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.

A Framework to Evaluate Autonomic Behaviours for Intelligent Truck Parking

This paper presents a multi-agent platform to evaluate different strategies to manage the negotiated management of parking spaces in road rest areas. The 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 allows a conversational interaction of new parking requests through an Android based mobile application.