4 research outputs found

    A comprehensive survey on cooperative intersection management for heterogeneous connected vehicles

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    Nowadays, with the advancement of technology, world is trending toward high mobility and dynamics. In this context, intersection management (IM) as one of the most crucial elements of the transportation sector demands high attention. Today, road entities including infrastructures, vulnerable road users (VRUs) such as motorcycles, moped, scooters, pedestrians, bicycles, and other types of vehicles such as trucks, buses, cars, emergency vehicles, and railway vehicles like trains or trams are able to communicate cooperatively using vehicle-to-everything (V2X) communications and provide traffic safety, efficiency, infotainment and ecological improvements. In this paper, we take into account different types of intersections in terms of signalized, semi-autonomous (hybrid) and autonomous intersections and conduct a comprehensive survey on various intersection management methods for heterogeneous connected vehicles (CVs). We consider heterogeneous classes of vehicles such as road and rail vehicles as well as VRUs including bicycles, scooters and motorcycles. All kinds of intersection goals, modeling, coordination architectures, scheduling policies are thoroughly discussed. Signalized and semi-autonomous intersections are assessed with respect to these parameters. We especially focus on autonomous intersection management (AIM) and categorize this section based on four major goals involving safety, efficiency, infotainment and environment. Each intersection goal provides an in-depth investigation on the corresponding literature from the aforementioned perspectives. Moreover, robustness and resiliency of IM are explored from diverse points of view encompassing sensors, information management and sharing, planning universal scheme, heterogeneous collaboration, vehicle classification, quality measurement, external factors, intersection types, localization faults, communication anomalies and channel optimization, synchronization, vehicle dynamics and model mismatch, model uncertainties, recovery, security and privacy

    Holistic Temporal Situation Interpretation for Traffic Participant Prediction

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    For a profound understanding of traffic situations including a prediction of traf- fic participants’ future motion, behaviors and routes it is crucial to incorporate all available environmental observations. The presence of sensor noise and depen- dency uncertainties, the variety of available sensor data, the complexity of large traffic scenes and the large number of different estimation tasks with diverging requirements require a general method that gives a robust foundation for the de- velopment of estimation applications. In this work, a general description language, called Object-Oriented Factor Graph Modeling Language (OOFGML), is proposed, that unifies formulation of esti- mation tasks from the application-oriented problem description via the choice of variable and probability distribution representation through to the inference method definition in implementation. The different language properties are dis- cussed theoretically using abstract examples. The derivation of explicit application examples is shown for the automated driv- ing domain. A domain-specific ontology is defined which forms the basis for four exemplary applications covering the broad spectrum of estimation tasks in this domain: Basic temporal filtering, ego vehicle localization using advanced interpretations of perceived objects, road layout perception utilizing inter-object dependencies and finally highly integrated route, behavior and motion estima- tion to predict traffic participant’s future actions. All applications are evaluated as proof of concept and provide an example of how their class of estimation tasks can be represented using the proposed language. The language serves as a com- mon basis and opens a new field for further research towards holistic solutions for automated driving

    Analyse d'un système radar intervéhiculaire en onde millimétrique (77 GHZ)

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    RÉSUMÉ Le nombre de capteurs et des données générées par les véhicules augmentent graduellement et devraient possiblement doubler d’ici 2020. L’avancée assez remarquable des techniques de communications sans fil pousse les recherches au plus haut niveau de la sécurité routière. A cet e˙et, le concept de sécurité routière relevant d’un facteur assez important dans la vaste par-tie des systèmes de transport intelligent, nécessite le déploiement d’infrastructures robustes capables d’implémenter des dispositifs à évitement de collision en circulation routière. Au vu de ce constat, le concept de détection intervéhiculaire par RADAR en ondes millimétrique est celui-là qui répondrait aux exigences des techniques d’évitement de col-lision par le principe de détection d’obstacle et de positionnement. En effet, la détection d’obstacle par RADAR repose sur un élément crustial appelé SER(Surface Equivalente RADAR) 1 qui de par sa valeur peut améliorer ou pas le RSB (SNR) 2 ou du moins les performances du système. Par contre, cette valeur de la SER diffère d’une cible à l’autre ou d’un obstacle à l’autre et ceci dépendamment de sa surface radiante. Dans le cas spécifique de la circulation routière et des usagers de la route, la variation de la SER est fortement liée à la distance de la cible par rapport au RADAR et de l’angle d’incidence des signaux émis. Ceci dit, les faibles variations de distance ou d’angles d’incidence engendrent des grandes variations de la SER ce qui occasionne des pertes importantes de quelques décibels mètre carré des valeurs de la SER. Ces pertes aussi majeures qu’elles soient, dégradent significativement les performances du système.Suite à cette problématique énoncée dans le paragraphe précédent, et dans le but de compenser les variations de la SER, un module de SER a été conçu au laboratoire Poly-Grames de l’école Polytechnique de Montréal.---------- ABSTRACT The number of sensors and data generated by vehicles is gradually increasing and is expected to double by 2020. The remarkable advance of wireless communications techniques is driving research at the highest level of road safety. To this end, the concept of road safety is a fairly important factor in the vast range of intelligent transport systems, requiring the deployment of robusts infrastructures capable of implementing collision avoidance devices in traÿc. In view of this, the concept of inter-vehicular detection by RADAR in millimeter wave is the one that would meet the requirements of collision avoidance techniques by the principle of obstacle detection and positioning. Indeed, the obstacle detection by RADAR is based on a crustial element called RCS (RADAR Cross Section) which by its value can improve or not the SNR (Signal Noise Ratio) or at least the performance of the system. On the other hand, this RCS value differs from one target to another or from one obstacle to another and this depends on its radiant surface. In the specific case of road traÿc and road users, the variation of RCS is strongly related to the distance from the target to RADAR and the angle of incidence of the transmitted signals. The small variations in distance or angles of incidence generate large variations of the RCS, which causes significant losses of a few decibels square meter of the RCS values. These losses as major as they are, significantly degrade the performance of the system. Following this problem stated in the previous paragraph, and in order to compensate for variations in the RCS, a RCS module was designed at Poly-Grames Laboratory of electrical engineering department of Ecole Polytechnique de Montréal. To this end, from the high-lighted RCS designed, the project aims to design and analyze the performance of a RADAR detection system on the following aspects: probability of detection or false alarm in term of SNR and range, optimization of parameters of the RADAR equation, FMCW modulation, estimation of angular position measurements and MSE of angles in the case of ESPRIT algorithms.In response to this design and analysis of the radar system’s performance, the conceptual approach was made at four levels. As a first step, a theoretical analysis of radar binary detection systems was carried out in order to analyze the influence of the parameter attenuation factor (�) commonly represented by the ratio between the distance radar to target (R), the wave-length (�0) and the RCS (˙)
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