Abstract-A hybrid method of short-term traffic forecasting is introduced; the KARIMA method. The technique uses a Kohonen self-organizing map as an initial classifier; each class has an individually tuned ARIMA model associated with it. Using a Kohonen map which is hexagonal in layout eases the problem of defining the classes. The explicit separation of the tasks of classification and functional approximation greatly improves forecasting performance compared to either a single ARIMA model or a backpropagation neural network. The model is demonstrated by producing forecasts of traffic flow, at horizons of half an hour and an hour, for a French motorway. Performance is similar to that exhibited by other layered models, but the number of classes needed is much smaller (typically between two and four). Because the number of classes is small, it is concluded that the algorithm could be easily retrained in order to track long-term changes in traffic flow and should also prove to be readily transferrable.
Serious games are increasingly explored as collaborative tools to enhance social learning on sustainable management of land and natural resources. A systematic literature review was conducted to examine the current state of the art of the different methods and procedures used to assess social learning outcomes of collaborative serious games. Forty-two publications were identified and included in the review following study selection and quality assessment steps. Extracted data from the publications were categorized in relation to five research questions. Approaches that were used to assess cognitive, normative, and relational learning outcomes of collaborative serious games were subsequently identified based on the categorizations. As a result, these approaches distinguished between the nature of learning in the assessment of collaborative serious games. Combined, these approaches provide an overview of how to assess social learning outcomes of collaborative serious games, including the methods and procedures that can be used, and may serve as a reference for scholars designing and evaluating collaborative serious games.
Through the years, many methods and tools have been developed that support designers in creating good products. Current trends, for example, are to use virtual reality (VR) simulation, gaming principles, and scenario based techniques during product design processes. Each of these methods and tools contributes to the potential effectiveness and efficiency of product design processes. However, in current practice, they are often applied in an ad-hoc manner. This paper presents a new product design method that integrates elements of a number of important trends in contemporary product design processes. Using VR simulation, gaming principles and scenarios, the new product design method gives non-designers (e.g. users, production engineers, marketing managers, maintenance workers) a proactive role in the design process. Within a dedicated design environment, all stakeholders are allowed to create their own designs and immediately test these in a wide variety of use scenarios. By letting stakeholders realistically interact with their personal creations, designers can quickly and reliably pinpoint their needs and preferences. At the same time, good designs are generated. The new product design method was applied to the design of a lane change support system; a system that supports the driver of a vehicle in performing lane change maneuvers. Using the design environment that was established for this case, the designer was able to get a consistent
Abstract-Lateral driver support systems have the potential to reduce the number of accidents associated with -both intentional and unintentional -lane departures. Additionally, such systems may increase driving comfort and stimulate a more efficient traffic flow, thereby reducing traffic emissions and the costs associated with traffic delays. This paper provides a literature review to identify the current state of the art on lateral driver support systems. The emphasis is on sensor technology, detection algorithms and safety assessment algorithms.
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