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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- "volume, capacity, speed, and efficiency) have evolved. Moving goods and people as quickly as possible all around the world requires advanced integrated transportation systems (Di Lecce and Amato, 2009). Information Technology (IT) and transport infrastructure help to manage transportation systems in an accurate and effective manner. "
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
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ABSTRACT: The aim of this work is to propose a semantic approach to driving behavior analysis. The analyzed vehicle motion parameters are accelerations and positions. Both are sampled using an embedded low-cost lightweight architecture. The authors start from a linguistic description of the problem ontology demonstrating that the selected parameters are sufficient to describe various aspects of the driving behavior. The system is modeled in terms of fuzzy rules and a Fuzzy Inference System is used to classify the driving behavior. The experiments carried out show that the proposed system is able to discriminate among various driving behavior.Journal of Circuits System and Computers 12/2009; 18(8):1581-1596. DOI:10.1142/S0218126609005873 · 0.33 Impact Factor
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ABSTRACT: Focus of this paper is to present an ITS used to certificate the correctness of vehicle activities. Due to the growing importance of transport system for the sustainability of the human society development, nowadays various intelligent transport systems (ITS) have been developed. In this work flexible ITS designed to handle various aspects of the hazardous material transport is presented. This system is able to monitor some vehicle's activities starting from the measurement of parameters such as accelerations, positions, etc. A fuzzy inference system (FIS) was implemented to test the possibility of using the proposed system as a certifier of the correctness of these activities. In particular, the loading and unloading activity of a vehicle fleet used for the rubbish collection was monitored. The proposed system was developed and tested in the framework of a research project funded by Apulia Region (Italy).Instrumentation and Measurement Technology Conference (I2MTC), 2010 IEEE; 06/2010