A multilevel interface for an intelligent transport system
ABSTRACT Aim of this work is to present a metaphor based multilevel interface for an Intelligent Transport System (ITS) designed to handle the transport of hazardous materials. This ITS was developed by the authors in the framework of a research project funded by Apulia Region (Italy). Starting from monitoring some parameters of a vehicle in motion such as position, speed, load balancing, stress conditions, etc., this system identifies various situations such as driver's behavior, hazardous conditions, and so on. In order to represent this information, the authors propose a multi level metaphor based graphic user interface (GUI). The first level of the interface allows for a rapid system view at a glance and is oriented to unskilled users while the second level reports more detailed information for the expert users.
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ABSTRACT: 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 approach- - es adopted for route planning and the user interface.IET Intelligent Transport Systems 10/2011; 5(3-5):149 - 158. DOI:10.1049/iet-its.2009.0100 · 0.95 Impact Factor
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ABSTRACT: Vehicles are nowadays provided with a variety of new sensors capable of gathering information about themselves and from their surroundings. In a near future, these vehicles will also be capable of sharing all the harvested information, with the surrounding environment and among nearby vehicles over smart wireless links. They will also be able to connect with emergency services in case of accidents. Hence, distributed applications based on Vehicular Networks (VNs) will need to agree on a ‘common understanding’ of context for interoperability, and, therefore, it is necessary to create a standard structure which enables data interoperability among all the different entities involved in transportation systems. In this paper, we focus on traffic safety applications; specifically, we present the VEhicular ACcident ONtology (VEACON) designed to improve traffic safety. Our ontology combines the information collected when an accident occurs, and the data available in the General Estimates System (GES) accidents database. We assess the reliability of our proposal using both realistic crash tests, held in the facilities of Applus+ IDIADA in Tarragona, Spain, and Vehicular Network simulations, based on the ns-2 simulation tool. Experimental results highlight that both nearby vehicles and infrastructure elements (RSUs) are correctly notified about an accident in just a few seconds, increasing the emergency services notification effectiveness.Journal of Network and Computer Applications 11/2012; 35(6). DOI:10.1016/j.jnca.2012.07.013 · 1.77 Impact Factor
Conference Paper: CAOVA: A Car Accident Ontology for VANETs[Show abstract] [Hide abstract]
ABSTRACT: In a near future, vehicles will be provided with a variety of new sensors capable of gathering information from their surroundings. These vehicles will also be capable of sharing the harvested information via Vehicular Ad hoc NETworks (VANETs) with nearby vehicles, or with the emergency services in case of an accident. Hence, distributed applications based on VANETs will need to agree on a ‘common understanding’ of context for interoperability, and therefore, it is necessary to create a standard structure which enables data interoperability among all the different entities involved in transportation systems. In this paper, we focus on traffic safety; specifically, we present a Car Accident lightweight Ontology for VANETs (CAOVA). The instances of our ontology are filled with: (i) the information collected when an accident occurs, and (ii) the data available in the General Estimates System (GES) accidents database. We assess the reliability of our proposal in two different ways: one via realistic crash tests, and the other one using a network simulation framework.IEEE Wireless Communications and Networking Conference (WCNC); 04/2012