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1
Content available remote Investigations on vehicles guided by updated road and maps
EN
The scope of this paper is to analyze performance of automatic vehicles during data dissemination with the realtime updated road information into the maps followed by the vehicle moments. Both modeling and development of the additional subsystems needed such as communications, reference/sensor systems and mobility are considered. The primary reason is that for solving both traffic congestion and safety problems to save time and fuel. The proposed location based algorithm analyses the features of complete automation of the driving function with suitably equipped road facilities.
PL
W artykule analizowano właściwości pojazdu automatycznego otrzymujące informacje o drodze w czasie rzeczywistym. Rozważano system przesyłu danych, system czujników oraz parametry ruchu przy kryterium oszczędności czasu i paliwa.
2
Content available Traffic Video and VANET data fusion algorithm
EN
Modern Intelligent Transport Systems incorporate the traffic control strategies that are based not only on long term traffic analysis and forecasts, but also on the real time events detection like accidents or high congestion. The flexibility of these systems depends on accurate and precise data set describing the current state of road network. To estimate it, the data from various sources like: video surveillance, induction loops or vehicles itself (Vehicle to Infrastructure communication -V2I) is gathered. Excluding detection errors, the video surveillance data is a reliable source of general information about the traffic flow. On the other hand, the vehicle communication can provide less reliable, but more detailed information about a particular vehicle like: its engine state or planned manoeuvre. Unreliable or forged C2I information can be used to disturb traffic or to gain a higher priority on the road. The paper reviews the fusion algorithms that are used to merge data from video tracking algorithms and vehicular networks. Based on the survey, a weighted fusion algorithm is proposed that estimates the acquired data reliability. The algorithm uses the video surveillance data as a filter for C2I communication. Finally, applications for microscopic traffic models and safety issues are taken into consideration.
EN
Many of the safety related applications that can be facilitated by Dedicated Short Range Communications (DSRC), such as vehicle proximity warnings, automated braking (e.g. at level crossings), speed advisories, pedestrian alerts etc., rely on a robust vehicle positioning capability such as that provided by a Global Navigation Satellite System (GNSS). Vehicles in remote areas, entering tunnels, high rise areas or any high multipath/ weak signal environment will challenge the integrity of GNSS position solutions, and ultimately the safety application it underpins. To address this challenge, this paper presents an innovative application of Cooperative Positioning techniques within vehicular networks. CP refers to any method of integrating measurements from different positioning systems and sensors in order to improve the overall quality (accuracy and reliability) of the final position solution. This paper investigates the potential of the DSRC infrastructure itself to provide an intervehicular ranging signal that can be used as a measurement within the CP algorithm. In this paper, time-based techniques of ranging are introduced and bandwidth requirements are investigated and presented. The robustness of the CP algorithm to inter-vehicle connection failure as well as GNSS dropouts is also demonstrated using simulation studies. Finally, the performance of the Constrained Kalman Filter used to integrate GNSS measurements with DSRC derived range estimates within a typical VANET is described and evaluated.
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