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The vehicle's localization is classically achieved by Bayesian methods like Extended Kaiman Filtering. Such a method provides an estimated position with its associated uncertainty. Bounded-error approaches using interval analysis work in a different way as they provide a possible set of positions. An advantage of such approaches is that the results are guaranteed and are not probabilistically defined...
The ArosDyn project aims to develop embedded software for robust analysis of dynamic scenes in urban traffic environments, in order to estimate and predict collision risks during car driving. The on-board telemetric sensors (lidars) and visual sensors (stereo camera) are used to monitor the environment around the car. The algorithms make use of Bayesian fusion of heterogenous sensor data. The key...
This paper presents a method for pedestrian tracking in urban environments using in-vehicle multilayer laser lidar (MLLR). The MLLR that we developed irradiates the laser in six scanning planes by a polygon mirror mechanism, and thus objects with height are observed with the plural scanning planes. MLLR outputs are modified by GPS data and are mapped onto a grid map. Pedestrians are found based on...
This paper describes hybrid fusion module used in a strong localization context (POMA) for embedded vehicle applications. This work has been developed in order to give an answer to the POMA (Positioning, Maps and local referencing) sub project objectives. These objectives are to provide, for a set of high level applications, a positioning service included a service quality, a metric accuracy (lane)...
The use of multiple hypothesis tracking has proven to provide significant performance benefits over the single hypothesis GNN or the PDA algorithm. Automotive sensors like radars, laser-scanners or vision systems are being integrated into vehicles for commercial or scientific purposes, in increasing numbers over the last years. As a result, there is profound literature on this area and several approaches...
To address perception problems we must be able to track dynamic objects of the environment. An important issue of tracking is the association problem in which we have to associate each new observation with one existing object in the environment. This problem is complex: unfortunately, the number of observations generally does not correspond to the number of objects. Moreover, the number of objects...
Trustworthy sensors are the key points regarding road safety applications. The lack of reliable sensors able to fulfil the entire requirements for these situations makes fusion schemes mandatory. A fusion scheme that uses two sensors: far infrared camera vision and a laser scanner to perform pedestrian detection is presented. Both sensors have different field of view thus different detection zones...
This paper presents the problematic of outdoor vehicle localization under the IMM (interacting multiple model) approach. The IMM is now a well known modular approach, which is based on the discretization of the vehicle evolution space into simple maneuvers, represented each by a simple dynamic model such as constant velocity or constant turning etc. This allows the method to be optimized for highly...
Due to the requirement of huge computation and real-time communication for integrated navigation system, a new scheme of distributed multiprocessor is introduced. The Control and communication of integrated system is completed by PC104, while navigation algorithm and integrated algorithm is realized by DSP. According to the error models of inertial navigation system, a tightly coupled integrated navigation...
We propose the information fusion of visible and infrared images for a pedestrian-vehicle SVM-based classification. Different types of fusion methods are presented: data fusion, feature fusion, matching score fusion and decision fusion. Data - level fusion assumes that the raw information is combined at the pixel level. The fusion at the feature level produces a feature vector integrating both visual...
This paper describes a design of a data logger based system dedicated to vehicle trajectory monitoring. The system evaluation is based on prototyping an embedded application. The adopted architecture allows tests and applications and results are obtained with a set of constraints. In this multisensors architecture, a GPS receiver is used for the absolute localization. In order to integrate the GPS...
In this paper we evaluate k-nearest neighbor (KNN), linear and quadratic discriminant analysis (LDA and QDA, respectively) for embedded, online feature fusion which poses strong limitations on computing resources and timing. These algorithms are implemented on our multisensor data fusion (MSDF) architecture and are applied to traffic monitoring, i.e., classifying vehicles using distributed image,...
The fusion of multiple monitoring systems is essential to build an accurate recognised traffic picture in support to maritime surveillance. In this paper, a novel approach to perform autonomous data correlation is described, focussing on the alignment of tracks originated by different sensors and technologies into a common spatial and time reference system, and introducing the quality characterisation...
The paper presents a real-time vision system for automatic traffic monitoring based on a network of autonomous tracking units that capture and process images from one or more pre-calibrated cameras. The system, which has been developed within the framework of TRAVIS (TRAffic VISual monitoring) project, is flexible, scalable and can be useable for a broad field of applications, including traffic monitoring...
This article deals with the following issue: how to track a varying number of pedestrians through observations by means of a 4-plane laser sensor. In order to answer to the multiple target tracking problem and more specifically pedestrian tracking, we propose in this paper a statistical approach using a particle filter based on nonparametric data association methods. This approach allows to go beyond...
The integration of current traffic monitoring operational systems in the field of maritime surveillance is widely acknowledged as a key requirement for borders control and illegal trafficking prevention. In this paper, an overview of the satellite-extended-vessel traffic service (SEV) system for in-situ and earth observation (EO) data association is presented. The description of the cognitive data...
In the scope of the EU funded TRACKSS project on cooperative advanced sensors for road traffic applications, we investigate the potential of pre-existing road traffic sensors for pedestrian crossing detection. Two road traffic video-sensors provide spatial occupancy rates on areas along a crosswalk. We propose to correct pedestrian under-detection with a double fusion process composed of inter-sensor...
In this paper, we propose a passenger monitoring system with ubiquitous detection sensors for railway platform safety. Objectives of the system are to perceive dangerous situation in platform, such as fallen passenger on the track, and to inform central control room and local station employee and train driver about the situation. The proposed system consists of a series of sensors, such as infrared...
For the land vehicle positioning, we need an accuracy that the actual sensors can't provide singly. So, we classically integrate two or more complementary sensors. In this paper, we present an algorithm based on Kalman filter, which integrates data from an inertial navigation system and a global positioning system receiver
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