The transport of hazardous materials can have a negative impact on human health and the environment quality; therefore it represents a relevant concern for each national economy of Europe. In Italy, the Apulia Region funded a research project to face this problem. In this framework, the authors proposed a flexible intelligent transport system (ITS) designed to work in many complex situations on the road network. This ITS uses artificial intelligence methods to implement route planning. Essentially, the system specifies a route for each vehicle by optimising a multi-objective function. The objectives, which are optimised, depend on the specific application and in this work they are related to the hazardous material transport impact reduction. This goal is achieved by implementing a negotiation process among intelligent agents. The system monitors the route followed by each vehicle and verifies if it coincides with the specified route. A key element of the ITS is a flexible on-board unit mounted on vehicles. It has a modular structure that allows for a variety of sensors to be connected, depending on the application. In this case, a variety of parameters, such as the vehicle speed, position, load balance and accelerations are analysed. Using that data the system identifies some characteristics, for example, the driver behaviour and hazardous vehicle operating conditions. In order to represent this information, the authors propose a multi-level metaphor-based graphic user interface (GUI). The first level of the interface provides a quickly understood view of the situation being monitored and it is oriented towards on-site first response and route monitoring operators. The second level provides more detailed information for incident managers and other operators. This interface has been evaluated using a human panel. Each volunteer has compiled a questionnaire after that he/she has used the interface for a 30-min session. The focus of this work is to present the approaches adopted for route planning and the user interface.
Route planning and user interface for an advanced intelligent transport system
IET Intelligent Transport Systems ; 5 , 3 ; 149-158
2011-12-01
10 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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