An experimental multimodal system combining natural input modes such as speech, lip movement, and gaze is proposed in this paper. It benefits from novel human-computer interaction (HCI) modalities and from multimodal integration for tackling the problem of the HCI bottleneck. This system allows the user to select menu items on the screen by employing speech recognition, lip reading, and gaze tr...

Computers are extremely powerful for data processing, but less adept at handling problems that involve subjective reasoning. People, on the other hand, are very good at these kinds of problems. We present a framework for adding subjective human experience to in-car navigation systems. People often rely on their own experience when planning trips, choosing the route that seemed fastest in the pa...

Human-computer interaction for in-vehicle information and navigation systems is a challenging problem because of the diverse and changing acoustic environments. It is proposed that the integration of video and audio information can significantly improve dialog system performance, since the visual modality is not impacted by acoustic noise. In this paper, we propose a robust audio-visual integra...

The paper presents the NaviExpert’s Community Traffic (CT) technology, an interactive, community-based car navigation system. Using data collected from its users, CT offers services unattainable to earlier systems. On one hand, the current traffic data are used to recommend the best routes in the navigation phase, during which many potentially unpredictable traffic-delaying and traffic-jamming ...

An experimental examination of the readability of a car-navigation system by elderly, middle-aged and young people was conducted. Subjects (127 people: 19-76 years of age) evaluated ease of reading of displayed characters. The experiment evaluated characters displayed on a liquid crystal display (LCD) similar to those used in car-navigation systems, and evaluated subjective evaluation of readab...

This paper characterizes how well the modular neuro-fuzzy controller, MoNiF, can perform in robotic applications by testing it in a race-car simulator. The performance of this controller is compared with that of a neural network controller (NNC) and the best programmed car (the ideal car). During the phase of learning from the ideal car, MoNiF reaches its stable performance (when it demonstrate...

In recent years, a trend of using real-time traffic data for navigation has developed. Google Navigation and Waze, for instance, generate traffic data from movement profiles of smartphones. In this paper we tackle the question to which extent it is possible for Google and Waze to track the smartphone and its owner. Furthermore, we show how wireless access points and smartphones acting like wire...

One of the major issues in the development of mobile pedestrian navigation services concerns the poor understanding of pedestrian spatiotemporal behaviour. Findings reveal that human route choice behaviour relies on a huge variety of influence factors. Therefore, common concepts like those used in car navigation systems will not conform to the requirements of pedestrians, as people on foot do n...