Intelligent Road Signs with V2X Interface for Adaptive Traffic Controlling - Project - Bridge of Knowledge

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Intelligent Road Signs with V2X Interface for Adaptive Traffic Controlling

Celem projektu jest opracowanie koncepcyjne, budowa i badania testowe nowego rodzaju inteligentnych znaków drogowych, które umożliwią zapobieganie najbardziej powszechnym kolizjom na drogach szybkiego ruchu, wynikającym z gwałtownego spiętrzania się pojazdów w przypadku wystąpienia potrzeby gwałtownego hamowania. W ramach projektu opracowany zostanie typoszereg produktów, obejmujących inteligentne znaki stojące, wiszące i mobilne, wyświetlające dynamicznie aktualizowaną zalecaną prędkość jazdy, określaną samoczynnie, dzięki wbudowaniu w znak drogowy modułowi elektronicznemu, umożliwiającemu wielomodalny pomiar warunków ruchu (wizyjny, akustyczny i analizę warunków meteorologicznych). W typowych warunkach użytkowania inteligentny znak będzie komunikował prędkość obliczaną w powiązaniu z informacjami otrzymywanymi z rzędu podobnych znaków rozmieszczonych wzdłuż odcinka drogi szybkiego ruchu, komunikujących się wzajemnie za pośrednictwem sieci bezprzewodowej lub opcjonalnie ustawianą w sposób zarządzany zdalnie. Jego opracowanie wymaga rozwiązania szeregu problemów badawczych i technologicznych, takich jak: skuteczna i niezależna od warunków atmosferycznych analiza ruchu drogowego dokonywana na podstawie jednoczesnej analizy kilku sposobów reprezentacji danych, metoda obliczania gradientu prędkości dla różnego typu sytuacji drogowych i topologii ruchu, stworzenie platformy samoorganizujących się i niezawodnych połączeń bezprzewodowych oraz przeprowadzenia zaplanowanych na odpowiednią skalę badań testowych prototypów, których realizacja doprowadzi do opracowania produktów zwiększających bezpieczeństwo ruchu drogowego, na które istnieje zapotrzebowanie rynkowe na całym świecie.

Details

Project's acronym:
INZNAK
Financial Program Name:
Program Operacyjny Inteligentny Rozwój
Organization:
Narodowe Centrum Badań i Rozwoju (NCBR) (The National Centre for Research and Development)
Agreement:
POIR.04.01.04-00-0089/16 z dnia 2017-02-13
Realisation period:
2017-07-01 - 2020-12-31
Project manager:
prof. dr hab. inż. Andrzej Czyżewski
Realised in:
Department of Multimedia Systems
External institutions
participating in project:
  • Siled Sp. z o.o. (Poland)
  • Akademia Górniczo Hutnicza (Poland)
  • Microsystem Sp. z o.o. (Poland)
Request type:
European Founds
Domestic:
Domestic project
Verified by:
Gdańsk University of Technology

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Catalog Projects

  • Estimating Traffic Intensity Employing Passive Acoustic Radar and Enhanced Microwave Doppler Radar Sensor
    Publication

    Innovative road signs that can autonomously display the speed limit in cases where the trac situation requires it are under development. The autonomous road sign contains many types of sensors, of which the subject of interest in this article is the Doppler sensor that we have improved and the constructed and calibrated acoustic probe. An algorithm for performing vehicle detection and tracking, as well as vehicle speed measurement,...

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  • Microscopic traffic simulation models for connected and automated vehicles (CAVs) – state-of-the-art
    Publication
    • P. Gora
    • C. Kartakazas
    • A. Drabicki
    • F. Islam
    • P. Ostaszewski

    - Procedia Computer Science - Year 2020

    Research on connected and automated vehicles (CAVs) has been gaining substantial momentum in recent years. However, thevast amount of literature sources results in a wide range of applied tools and datasets, assumed methodology to investigate thepotential impacts of future CAVs traffic, and, consequently, differences in the obtained findings. This limits the scope of theircomparability and applicability and calls for a proper standardization...

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  • System for monitoring road slippery based on CCTV cameras and convolutional neural networks
    Publication

    The slipperiness of the surface is essential for road safety. The growing number of CCTV cameras opens the possibility of using them to automatically detect the slippery surface and inform road users about it. This paper presents a system of developed intelligent road signs, including a detector based on convolutional neural networks (CNNs) and the transferlearning method employed to the processing of images acquired with video...

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  • Vehicle Detection with Self-Training for Adaptative Video Processing Embedded Platform
    Publication

    Traffic monitoring from closed-circuit television (CCTV) cameras on embedded systems is the subject of the performed experiments. Solving this problem encounters difficulties related to the hardware limitations, and possible camera placement in various positions which affects the system performance. To satisfy the hardware requirements, vehicle detection is performed using a lightweight Convolutional Neural Network (CNN), named...

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  • Development of Intelligent Road Signs with V2X Interface for Adaptive Traffic Controlling
    Publication

    - Year 2019

    The objective of this paper is to present a practical project of intelligent road signs, under which a series of new products for the regulation of traffic is being created. The engineering part of the project, described in this paper, was preceded by a series of experimental studies, the results of which were described in another paper accepted for publication at the MTS-ITS conference 2019, entitled "Comparative study on the effectiveness...

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  • Determination of the Vehicles Speed Using Acoustic Vector Sensor
    Publication

    - Year 2018

    The method for determining the speed of vehicles using acoustic vector sensor and sound intensity measurement technique was presented in the paper. First, the theoretical basis of the proposed method was explained. Next, the details of the developed algorithm of sound intensity processing both in time domain and in frequency domain were described. Optimization process of the method was also presented. Finally, the proposed measurement...

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  • Suppression of distortions in signals received from Doppler sensor for vehicle speed measurement
    Publication

    - Year 2018

    Doppler sensors are commonly used for movement detection and speed measurement. However, electromagnetic interference and imperfections in sensor construction result in degradation of the signal to noise ratio. As a result, detection of signals reflected from moving objects becomes problematic. The paper proposes an algorithm for reduction of distortions and noise in the signal received from a simple, dual-channel type of a Doppler...

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  • Examining Impact of Speed Recommendation Algorithm Operating in Autonomous Road Signs on Minimum Distance between Vehicles
    Publication

    - Remote Sensing - Year 2022

    An approach to a new kind of recommendation system design that suggests safe speed on the road is presented. Real data obtained on roads were used for the simulations. As part of a project related to autonomous road sign development, a number of measurements were carried out on both local roads and expressways. A speed recommendation model was created based on gathered traffic data employing the traffic simulator. Depending on...

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  • Localization of sound sources with dual acoustic vector sensor
    Publication

    - Year 2019

    The aim of the work is to estimate the position of sound sources. The proposed method uses a setup of two acoustic vector sensors (AVS). The intersection of azimuth rays from each AVS should indicate the position of a source. In practice, the result of position estimation using this method is an area rather than a point. This is a result of inaccuracy of the individual sensors, but more importantly, of the influence of a source...

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  • Evaluating calibration and robustness of pedestrian detectors
    Publication

    - Year 2020

    In this work robustness and calibration of modern pedestrian detectors are evaluated. Pedestrian detection is a crucial perception com- ponent in autonomous driving and here we study its performance under different image corruptions. Furthermore, we provide analysis of classifi- cation calibration of pedestrian detectors and we show a positive effect of using style-transfer augmentation technique. Our analysis is aimed as a step...

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  • Application of autoencoder to traffic noise analysis

    The aim of an autoencoder neural network is to transform the input data into a lower-dimensional code and then to reconstruct the output from this code representation. Applications of autoencoders to classifying sound events in the road traffic have not been found in the literature. The presented research aims to determine whether such an unsupervised learning method may be used for deploying classification algorithms applied to...

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  • Counting and tracking vehicles using acoustic vector sensors

    A method is presented for counting vehicles and for determining their movement direction by means of acoustic vector sensor application. The assumptions of the method employing spatial distribution of sound intensity determined with the help of an integrated 3D intensity probe are discussed. The intensity probe developed by the authors was used for the experiments. The mode of operation of the algorithm is presented in conjunction...

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  • Comparing traffic intensity estimates employing passive acoustic radar and microwave Doppler radar sensor

    The purpose of our applied research project is to develop an autonomous road sign with built-in radar devices of our design. In this paper, we show that it is possible to calibrate the acoustic vector sensor so that it can be used to measure traffic volume and count the vehicles involved in the traffic through the analysis of the noise emitted by them. Signals obtained from a Doppler radar are used as a reference source. Although...

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  • Style Transfer for Detecting Vehicles with Thermal Camera
    Publication

    - Year 2019

    In this work we focus on nighttime vehicle detection for intelligent traffic monitoring from the thermal camera. To train a Convolutional Neural Network (CNN) detector we create a stylized version of COCO (Common Objects in Context) dataset using Style Transfer technique that imitates images obtained from thermal cameras. This new dataset is further used for fine-tuning of the model and as a result detection accuracy on images...

  • Vehicle detector training with minimal supervision
    Publication

    - Year 2019

    Recently many efficient object detectors based on convolutional neural networks (CNN) have been developed and they achieved impressive performance on many computer vision tasks. However, in order to achieve practical results, CNNs require really large annotated datasets for training. While many such databases are available, many of them can only be used for research purposes. Also some problems exist where such datasets are not...

  • Akustyczna analiza natężenia ruchu drogowego dla systemów zarządzania ruchem
    Publication

    - Year 2019

    W pracy przybliżono wybrane zagadnienia z dziedziny zarządzania transportem drogowym w Polsce i na świecie. W tym kontekście pzredstawiono potrzeby rynkowe, wymagania jak i możliwości w zakresie pozyskiwania informacji o aktualnym stanie sieci drogowych. Zaproponowano akustyczną metodę nadzorowania ruchu drogowego i jej możliwości w kontekście systemów zarządzania ruchem. Przedstawiono schemat akwizycji sygnału wraz z danymi odniesienia....

  • An application of acoustic sensors for the monitoring of road traffic
    Publication

    Assessment of road traffic parameters for the developed intelligent speed limit setting decision system constitutes the subject addressed in the paper. Current traffic conditions providing vital data source for the calculation of the locally fitted speed limits are assessed employing an economical embedded platform placed at the roadside. The use of the developed platform employing a low-powered processing unit with a set of microphones,...

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  • Adaptive traffic optimization using Variable Speed Limits; Adaptacyjna optymalizacja ruchu drogowego przy pomocy zmiennych ograniczeń prędkości
    Publication

    - Year 2020

    Variable speed limits (VSL) is an intelligent transportation system (ITS) solution for traffic management. The speed limits can be changed dynamically in order to adapt to traffic, weather, or road surface conditions. This paper presents an approach for such an adaptive traffic control where the primary goal is to ensure traffic safety and efficiency of the traffic control system (fast response to dynamically changing traffic,...

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  • Projekt INZNAK - aktywne znaki drogowe
    Publication

    W Politechnice Gdańskiej na Wydziale Elektroniki, Telekomunikacji i Informatyki we współpracy z Akademią Górniczo-Hutniczą w Krakowie i dwiema firmami z województwa pomorskiego (Siled Sp. z o.o. i Microsystems Sp. z o.o.) od 2017 r. realizowany jest projekt badawczy pt. „INZNAK – inteligentne znaki drogowe do adaptacyjnego sterowania ruchem pojazdów, komunikujące się w technologii V2X”. Projekt jest dofinansowywany przez NCBR w...

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  • Analiza ruchu drogowego z wykorzystaniem analizy akustycznej

    Tematyka pracy porusza zagadnienia dotyczące pozyskiwania informacji o ruchu drogowym z wykorzystaniem monitoringu akustycznego. Przybliżono podstawowe techniki nadzoru nad ruchem drogowym. Przedstawiono założenia akustycznego detektora ruchu i zbadano jego skuteczność na trzech płaszczyznach działania – zliczania pojazdów, klasyfikacji rodzajowej i klasyfikacji warunków pogodowych panujących na nawierzchni

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  • 1D convolutional context-aware architectures for acoustic sensing and recognition of passing vehicle type
    Publication

    A network architecture that may be employed to sensing and recognition of a type of vehicle on the basis of audio recordings made in the proximity of a road is proposed in the paper. The analyzed road traffic consists of both passenger cars and heavier vehicles. Excerpts from recordings that do not contain vehicles passing sounds are also taken into account and marked as ones containing silence....

  • Automatic labeling of traffic sound recordings using autoencoder-derived features
    Publication

    An approach to detection of events occurring in road traffic using autoencoders is presented. Extensions of existing algorithms of acoustic road events detection employing Mel Frequency Cepstral Coefficients combined with classifiers based on k nearest neighbors, Support Vector Machines, and random forests are used. In our research, the acoustic signal gathered from the microphone placed near the road is split into frames and converted...

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