Scenario understanding and motion prediction are essential components for completely
replacing human drivers and for enabling highly and fully automated driving (SAE-Level …

The uncertainty of ship trajectory prediction is addressed. In particular, a probabilistic
trajectory prediction model is proposed that describes the uncertainty in future positions …

The task of similarity search is widely used in various areas of computing, including
multimedia databases, data mining, bioinformatics, social networks, etc. In fact, retrieval of …

A spatial correlation analysis of near collision clusters with local traffic characteristics is
presented. The Moran's I and Getis-Ord Gi* spatial autocorrelation methods are used to …

Future driver assistance systems will have to cope with complex traffic situations, especially
in the road crossing scenario. To detect potentially hazardous situations as early as …

This paper presents a novel application of automated video analysis for a before-and-after
(BA) safety evaluation of a scramble phase treatment. Data availability has been a common …

In this paper we present a machine learning framework to analyze moving object trajectories
from maritime vessels. Within this framework we perform the tasks of clustering, classification …

Forecasting the future positions of mobile users is a valuable task allowing us to operate
efficiently a myriad of different applications which need this type of information. We propose …

This paper carries out research on the prototype of an autonomous vessel that is normally
used for passenger transportation. A path generation system is proposed using a dynamic …

The advent of powerful sensing technologies, especially video sensors and computer vision
techniques, has allowed for the collection of large quantities of detailed traffic data. These …