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This study is prepared to produce solutions for estimating vehicle traffic density which is one of the biggest problems of urban life today. Four different algorithms are proposed for density estimation problem with different perspectives. All these proposed algorithms have been tried to estimate next state of the road by looking at history of density data. Algorithms are inspired by the methods used...
With growing road traffic, it becomes essential to predict the travel time of road travelers well ahead of their travel to avoid traffic mismanagement. Vehicular Adhoc Network (VANET) infrastructure is an ideal solution for such requirements. VANET uses Road Side Units (RSU) that remain as the primary and critical source to predict the traffic in any road. This paper proposes an Optimized RSU based...
Present work analyses the continuous self-calibration of extrinsic parameters of a stereo vision system for safe visual odometry applications in vehicles at urban environments. The calibration method determines the extrinsic parameters of a stereo vision system based on knowing the geometry of the ground in front of the cameras. The slight changes of the road profile cause variations in the extrinsic...
An important cause of road accidents is the reduced visibility due to the presence of fog or haze. For this reason, there is a fundamental need for Advanced Driving Assistance Systems (ADAS) based on efficient real time algorithms able to detect the presence of fog, estimate the fog's density, determine the visibility distance and inform the driver about the maximum speed that the vehicle should be...
These days, robust autonomous navigation incorporates the information on the digital map including variety of road features such as position of lane markings, road boundaries and etc. In this study, a method of extracting road features are developed using two dimensional laser range finder (LRF). In particular, range measurements are employed to identify the road surface using split and merge method...
Accurately estimating node density in Vehicular Ad hoc Networks (VANETs) is a challenging and crucial task. Various approaches exist yet none are able to deliver an accurate estimation in all situations especially in presence of collision in highly saturated networks. This paper describes an adaptive framework that allows individual nodes to estimate the real-time node density of their surrounding...
This paper proposes a framework of segment-based free space estimation using plane normal vector with stereo vision. An image is divided into compact superpixels and each of them is viewed as a plane composed of the normal vector in disparity space. To deal with the variation of illumination and shading in real traffic scenes, we estimate depth information for the segmented stereo pair. The representative...
Estimating the localization of an autonomous robot is a key problem in robotics. Monocular cameras have been successfully used to solve this problem, but they suffer with the absence of depth information. It limits measurements made with only monocular cameras to be recoverable only up to a scale. This condition is known as scale ambiguity. In this paper we propose an approach to solve the scale ambiguity...
Future advanced driver assistant systems and automated driving put high demands on the environmental perception especially in urban environments. Major tasks are the perception of static and dynamic elements along with the drivable area and road structures. Although these tasks can be done without an explicit representation of the ground surface, evaluations with real-world sensor data have shown...
Information is critical in almost all decision making processes. Therefore, it is important to get the right information at the right time from the right sources. However, information sources may behave differently while providing information — i.e., they may provide unreliable, erroneous, noisy, or misleading information deliberately or unintentionally. Motivated by this observation, in this paper,...
In this paper, disparity map estimation algorithm targeting for advanced driver assistance systems (ADAS) is described. A disparity map estimation algorithm for ADAS needs to be both accurate and to be able to work in real time. These algorithms can be classified into two categories: global estimation and local estimation. While global estimation algorithms tend to output a less noisy disparity map,...
The missing trajectory problem is a difficulty in various transportation applications, e.g. the road which the truck usually travels and the driver's behavior. Most of previously developed missing data are not concerned about the spatial and continues space. Therefore, in this article, an algorithm is proposed to complete the missing trajectory in a vehicle's trace. The possible traces are found out...
In developing countries like India, limited Intelligent Transportation Systems (ITS) infrastructure is available and it is difficult to generate real time traffic information for city wide or larger regions. On the other hand, cellular network is widely deployed in India covering major part of the road network. However, cellular network based positioning data have large location error (250-500 meters)...
Cooperative Awareness Messages (CAMs) regularly distribute state information about vehicles in Vehicular Ad-hoc Networks (VANETs). Hardware modules in series vehicles have limited processing capabilities so that only a subset of received CAMs can be processed which may be chosen by a relevance estimation mechanism (REM). In this work, we review several REMs that differ in complexity. We compare them...
In this paper an automated vehicle detection and traffic density estimation algorithm has been developed and validated for very high resolution satellite video data. The algorithm is based on an adaptive background estimation procedure followed by a background subtraction at every video frame. The vehicle detection is performed through a further mathematical morphology and statistical analysis on...
Perimeter traffic flow control has recently been found to be a practical and efficient control scheme in mitigating traffic congestion in urban road networks. This control scheme aims at stabilising the accumulation of vehicles of the socalled network fundamental diagram near critical accumulation to achieve maximum network throughput. Nevertheless, the maximum throughput in urban road networks may...
This paper presents a novel integrated optimal dynamics control of 4WS4WD electric vehicles via hierarchical control methodology. In the higher-level design, an LQR controller is proposed to obtain the generalized longitudinal force, lateral force and yaw moment, according to their respective reference values. In the lower-level design, the control signals from the higher-level controller are allocated...
Accident prevention systems have recently been a part of many modern cars to reduce injuries and casualties on the road. However, the high cost of components and equipment have limited such safety systems to higher-end and luxury vehicles. This paper proposes an economical method of using a smartphone application for real-time lane detection and rearend collision warning system for drivers on the...
This paper shows how rerouting phenomena can be observed from the available data and how to derive valuable input to estimate the rerouting models. By rerouting we mean changing the currently chosen path in road network after either receiving some information or observing consequences of an unexpected traffic event. Recently we have proposed Information Comply Model (ICM) to address the rerouting...
Short-term traffic prediction provides tools for improved road management by allowing the reduction of delays, incidents and other unexpected events. Different real-time approaches provide traffic managers with varying but valuable information. This paper reviews the literature regarding model-driven and data-driven approaches focusing on short-term realtime traffic prediction. We start by analyzing...
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