In this paper, I describe research topics in my PhD-project Multimodal perceptually rich interfaces in transport. The project aims at exploring the use of multimodal interfaces, focusing on non-visual sense impressions in complex sociotechnical systems as the operation of high speed crafts. INTRODUCTION My PhD-project Multimodal perceptually rich interfaces in transport is part of an interdisci...

background many multimodal analgesia techniques have been tried to provide adequate analgesia for midline incisions extending above and below the umbilicus aiming at limiting the perioperative use of morphine thus limiting side effects. ultrasound (us) guidance made the anesthesiologist reconsider old techniques for wider clinical use. the rectus sheath block (rsb) is a useful technique under-u...

We present a system for multimodal, semantic analysis of person movements that incorporates data from surveillance cameras, weather sensors, and third-party information providers. The interactive demonstration will show the automated creation of a survey of passenger transfer behavior at a public transport hub. Such information is vital for public transportation planning and the presented appro...

Lean Production is one of the current issues in logistics (Womack, 2004). Clocked production and transport effect an adjustment of the individual process steps. Today only large companies are able to raise enough transport volume for an individual transport solution and so assure the resulting advantages of decreasing storage costs and capital lockup. An individually clocked transport in small ...

One of the challenges facing intermodal integration is that the planning framework needed for it lacks appropriate measures of level of service that cut across the modes involved and the connections between them. In this study we develop a framework and a set of metrics of level of service in a multimodal context. We propose a conceptual framework in which we identify the various attributes of ...

Traffic flow forecasting has been regarded as a key problem of intelligent transport systems. In this work, we propose a hybrid multimodal deep learning method for short-term traffic flow forecasting, which jointly learns the spatial-temporal correlation features and interdependence of multi-modality traffic data by multimodal deep learning architecture. According to the highly nonlinear charac...

This paper presents a discrete network design problem for optimally designing freight transport network in terms of the efficiency of supply chain. Modelling is undertaken within the framework of mathematical programmes with equilibrium constraints, which first incorporates both supply chain and transport networks explicitly. The upper level determines the best set of actions for transport netw...