The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In order to improve traffic efficiency in urban road networks, the analysis and prediction of congestion is essential. In this paper a method is presented that first identifies frequently congested regions of a network by clustering affected links and then predicts travel time losses inside these clusters. Thereby, the reduction of the entire network to its mostly congested regions allows considering...
In order to make full use of the massive vehicle networking data and dig out the characteristics of the vehicle driving behaviors, the analysis of the massive vehicle networking data is indispensable. And clustering analysis is an effective way to extract the information which can guide and supervise the vehicles. In this paper, we propose a novel initial clustering center selection algorithm based...
Ride-sharing practice represents one of the possible answers to the traffic congestion problem in today's cities. In this scenario, recommenders aim to determine similarity among different paths with the aim of suggesting possible ride shares. In this paper, we propose a novel dissimilarity function between pairs of paths based on the construction of a shared path, which visits all points of the two...
Clustering of Vanets is a technique for grouping nodes in geographical vicinity together, making the network more robust and scalable. Clustering of vehicles that is based on virtual forces has been recently introduced for highways. We propose a new algorithm, called Virtual Forces Vehicular Clustering (VFVC), to create stable clusters in Urban environments where mobility patterns of vehicles is more...
The present paper introduces an agent-based approach for clustering geographical data. In this approach, a multi-agent architecture is proposed. It consists of three competence levels: specialized gatherers (G-Agents), breakers (B-Agents), mappers (M-Agents). Each of these agents have particular role in the process of segmentation. Using biclustering, the approach combines the different views of the...
The Light Detection and Ranging (LiDAR) system is one of the best ways to accurately and effectively gather 3-D terrain information. However, it is complicated to process the LiDAR cloud data due to its irregularity and large number of collected data points. This letter proposes a novel method to automatically extract urban road network from 3-D LiDAR data. This method uses height and reflectance...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.