The development of an automatic method of safety monitoring at Pelican Crossings

This paper reports on the development of a method for automatic monitoring of safety at Pelican crossings. Historically, safety monitoring has typically been carried out using accident data, though given the rarity of such events it is difficult to quickly detect change in accident risk at a particular site. An alternative indicator sometimes used is traffic conflicts, though this data can be time consuming and expensive to collect. The method developed in this paper uses vehicle speeds and decelerations collected using standard in-situ loops and tubes, to determine conflicts using vehicle decelerations and to assess the possibility of automatic safety monitoring at Pelican crossings. Information on signal settings, driver crossing behaviour, pedestrian crossing behaviour and delays, and pedestrian-vehicle conflicts was collected synchronously through a combination of direct observation, video analysis, and analysis of output from tube and loop detectors. Models were developed to predict safety, i.e. pedestrian-vehicle conflicts using vehicle speeds and decelerations

Eine mikrosimulationsbasierte Methode zur Beurteilung der Leistungsfähigkeit von Shared Space

Shared space is a concept of urban street design which implies the creation of a level surface within the whole road reserve and is aimed at encouraging different road users to interact spontaneously and to negotiate priority with each other. To build successful shared spaces, traffic engineers can rely at present on specific guidelines as well as technical reports. Nevertheless, there is no method available to compute the performance of shared spaces in terms of Level Of Service (LOS). In order to address this gap, a new indicator of traffic quality for pedestrians is being developed. This measure of performance considers aspects of comfort related to the crossing, which pedestrians use to go from one side of the roadway to the other. During this movement, discomfort is generated by the necessity to solve the conflicts with vehicles. Therefore, factors which potentially influence comfort are mathematically formulated. Later, the performance indicator can be calibrated on the basis of the opinion of a group of respondents, who evaluated real-world crossing movements in video sequences. The effectiveness and usability of the developed indicator is demonstrated in an exemplary case study. A shared street in the district of Bergedorf, Hamburg (D) is selected and filmed. To reproduce the interaction of road users and the mechanism of space negotiation, an innovative modeling approach based on social force model (SFM) is proposed. The model is calibrated and implemented in a Java-based simulation tool. Alternative shared space scenarios, as well as conventional ones with space segregation, are simulated. The goal of this dissertation is to establish a method to evaluate the performances of shared spaces through traffic microsimulation. This method includes the data survey and acquisition, the definition of performance indicators, the development of a microsimulation approach, the calibration of the motion model on the basis of real-world data and finally the execution of simulations to collect the results. In addition, this work shows the necessity to employ a comfort-based indicator for pedestrian traffic quality in shared spaces. The benefits of this approach, with respect to conventional efficiency-based indicators as time delay, is properly shown in real-world situations and successively demonstrated by help of statistical methods.Shared Space ist ein Konzept der urbanen Straßengestaltung, das die Schaffung von niveaugleichen Zonen im gesamten Straßenquerschnitt beinhaltet, und darauf abzielt, die verschiedenen Verkehrsteilnehmer zu ermutigen, spontan zu interagieren und den Vorrang untereinander auszuhandeln. Um erfolgreiche Shared Spaces zu gestalten, können sich Ingenieure derzeit auf spezifische Richtlinien, sowie auf technische Berichte stützen. Dennoch gibt es keine Methode, um die Qualität des Shared Space im Hinblick auf den Level of Service (LOS) zu kalkulieren. Daher wird ein neuer Verkehrsqualitätsindikator für Fußgänger entwickelt. Diese Erfolgsmessgröße berücksichtigt Komfortaspekte hinsichtlich der von Fußgängern zur Querung der Straßen benutzten Übergänge. Während der Überquerung wird durch das Aushandeln des Vorrangs mit den Fahrzeugen ein Unbehagen erzeugt. Daher werden potentiell komfortbeeinflussende Faktoren mathematisch formuliert. Später kann der Leistungsindikator auf Basis der Ansicht einer Umfragegruppe, die reale Straßenüberquerungen in Videosequenzen auswertet, kalibriert werden. Die Effektivität und Tauglichkeit des entwickelten Indikators wird in einer exemplarischen Fallstudie im Hamburger Bezirk Bergedorf demonstriert. Hierzu wird der dortige Shared Space gefilmt. Um die Interaktion von Verkehrsteilnehmern und die Wirkungsweise der Verkehrsraumaushandlung nachzustellen, wird ein innovativer Modellierungsansatz, der auf dem sozialen Kräftemodell basiert, empfohlen. Das Modell wird in einem Java-basierten Simulationstool kalibriert und implementiert. Verschiedene Shared Space Arten und konventionelle Szenarien mit Raumtrennung werden simuliert. Das Ziel dieser Dissertation ist es, ein Verfahren zur Auswertung der Performances von Shared Spaces durch Verkehrsmikrosimulation zu entwickeln. Dieses Verfahren beinhaltet die Datenerhebung und –erfassung, die Definition der Leistungsindikatoren, die Entwicklung eines Mikrosimulationsansatzes und die Kalibrierung des Bewegungsmodells auf Basis realer Daten. Zudem werden Simulationen durchgeführt, um Ergebnisse zu sammeln. Des Weiteren zeigt diese Arbeit die Notwendigkeit, einen komfortbasierten Indikator für die Verkehrsqualität der Fußgänger in Shared Spaces zu verwenden. Die Vorteile dieses Ansatzes, gegenüber konventionellen, effizienzbasierten Indikatoren wie z.B. Zeitverzögerungen, werden entsprechend in praxistauglichen Situationen dargestellt und sukzessiv mittels statistischer Verfahren veranschaulicht

An Overview about Emerging Technologies of Autonomous Driving

Since DARPA started Grand Challenges in 2004 and Urban Challenges in 2007, autonomous driving has been the most active field of AI applications. This paper gives an overview about technical aspects of autonomous driving technologies and open problems. We investigate the major fields of self-driving systems, such as perception, mapping and localization, prediction, planning and control, simulation, V2X and safety etc. Especially we elaborate on all these issues in a framework of data closed loop, a popular platform to solve the long tailed autonomous driving problems

車載カメラを用いた障害物検出システムの研究

九州工業大学博士学位論文 学位記番号:工博甲第371号　学位授与年月日:平成26年9月26日1 Introduction||2 Obstacles Detection||3 2D and 3D Objects Classification||4 Final Experimental Results and Evaluation||5 Conclusion||ReferencesIn recent years, autonomous collision avoidance systems have been researched and developed for realizing safe driving using cameras and sensors. These systems are designed to warn the drivers the presence of obstacles on the road and help them take a necessary action in advance. In these systems, the ability to detect obstacles is essential. Although various methods of obstacles detection have already been reported, these existing obstacles detection methods have some inadequacies: Some of them can be only used to detect moving obstacles; Some of them cannot extract the shape of obstacles, and they only use a rectangular frame that surrounds an obstacle to represent a detected obstacle; Some of them can only be used to detect one kind of specific object, such as pedestrian detection or vehicle detection. In order to make up for the inadequacies of the existing obstacles detection method, in this thesis, a method is proposed for detecting obstacles on a road by the employment of the background modeling and the road region detection. In obstacles detection, true obstacles are defined as arbitrary objects which protrude from the ground plane in the road region, including static and moving objects. Road marks in the road region and objects outside the road region are considered as false obstacles. The output of this obstacles detection method is based on the obstacles’ shape. In this thesis, we also propose a method of classifying 2D objects and 3D objects. The results of 2D objects and 3D objects classification can be used in the resultant image of obstacles detection to delete 2D objects (such as road marks) and improve the accuracy of obstacles detection. The originalities of this thesis are as follows: In the first place, the proposed method can detect arbitrary objects including both static objects and moving objects. This is helpful because static objects such as boxes fallen on the road from a car are dangerous for drivers. In the second place, the output of the proposed method is the shape of obstacles. Extraction of the shape of an obstacle is important for obstacles recognition. If the detected obstacle is recognized as a pedestrian from its shape, we can foresee his/her next motion. In the third place, the proposed method can distinguish which objects are 3D objects, and which objects are 2D objects in a pile of objects using a monocular camera. It is useful in the obstacles detection and other applications, such as navigation of walking robots. In the performed experiments, it is shown that the proposed obstacles detection method is able to extract the shape of both static and moving obstacles in a frontal view from a car

Vision-based traffic monitoring system with hierarchical camera auto-calibration

Texto en inglés.En las últimas décadas, el tráfico, debido al aumento de su volumen y al consiguiente incremento en la demanda de infraestructuras de transporte, se ha convertido en un gran problema en ciudades de casi todo el mundo. Constituye un fenómeno social, económico y medioambiental en el que se encuentra inmersa toda la sociedad, por lo que resulta importante tomarlo como un aspecto clave a mejorar. En esta línea, y para garantizar una movilidad segura, fluida y sostenible, es importante analizar el comportamiento e interacción de los vehículos y peatones en diferentes escenarios. Hasta el momento, esta tarea se ha llevado a cabo de forma limitada por operarios en los centros de control de tráfico. Sin embargo, el avance de la tecnología, sugiere una evolución en la metodología hacia sistemas automáticos de monitorización y control. Este trabajo se inscribe en el marco de los Sistemas Inteligentes de Transporte (ITS), concretamente en el ámbito de la monitorización para la detección y predicción de incidencias (accidentes, maniobras peligrosas, colapsos, etc.) en zonas críticas de infraestructuras de tráfico, como rotondas o intersecciones. Para ello se propone el enfoque de la visión artificial, con el objetivo de diseñar un sistema sensor compuesto de una cámara, capaz de medir de forma robusta parámetros correspondientes a peatones y vehículos que proporcionen información a un futuro sistema de detección de incidencias, control de tráfico, etc.El problema general de la visión artificial en este tipo de aplicaciones, y que es donde se hace hincapié en la solución propuesta, es la adaptabilidad del algoritmo a cualquier condición externa. De esta forma, cambios en la iluminación o en la meteorología, inestabilidades debido a viento o vibraciones, oclusiones, etc. son compensadas. Además el funcionamiento es independiente de la posición de la cámara, con la posibilidad de utilizar modelos con pan-tilt-zoom variable para aumentar la versatilidad del sistema. Una de las aportaciones de esta tesis es la extracción y uso de puntos de fuga (a partir de elementos estructurados de la escena), para obtener una calibración de la cámara sin conocimiento previo. Esta calibración proporciona un tamaño aproximado de los objetos buscados, mejorando así el rendimiento de las siguientes etapas del algoritmo. Para segmentar la imagen se realiza una extracción de los objetos móviles a partir del modelado del fondo, basándose en mezcla de Gaussianas (GMM) y métodos de detección de sombras. En cuanto al seguimiento de los objetos segmentados, se desecha la idea tradicional de considerarlos un conjunto. Para ello se extraen características cuya evolución es analizada para conseguir finalmente una agrupación óptima que sea capaz de solventar oclusiones. El sistema ha sido probado en condiciones de tráfico real sin ningún conocimiento previo de la escena, con resultados bastante satisfactorios que muestran la viabilidad del método

Sensory Augmentation for Navigation in Difficult Urban Environments by People With Visual Impairment

Independent mobility in completing such tasks as walking through a town centre is taken for granted by well-bodied individuals. However, for those with a disability such as impairment of vision, mobility and navigation can become challenging tasks not easily undertaken. The barriers to access for blind and partially sighted individuals are increased when familiar navigational cues are removed in difficult urban environments such as Shared Space. The research consisted of investigating methods of navigation employed by people with visual impairment and designing a device to restore confidence to this group so as to lower the barriers of access to such environments. Investigation was carried out through the deployment of a questionnaire; discussions with groups representing blind and partially sighted people; and a site visit to Shared Space environments. Statistical analysis was carried out on the results of the questionnaire to ascertain the navigational habits of blind and partially sighted individuals in different environments. From the analysis and the results of the discussions and site visit it was established that it would be socially acceptable to design a secondary aid to navigation that would complement the primary aids of long cane or guide dog. A concept experiment was carried out to test the idea that knowledge about changes in surface colour could help with navigation. A prototype device that could be used by individuals with visual impairment to increase their confidence when navigating a difficult environment was designed, built and tested. Different programming methods were researched and trialled to effectively use machine vision to provide a solution to analyse video feed from a passive camera and return useful information to a blind or partially sighted user. The device was tested indoors and outdoors and found to be effective at detecting changes in surface colour. Further work is needed to run the software on a more compact platform such as a mobile phone, but initial results show that the concept is viable and that the barriers that present to blind and partially sighted people navigating difficult urban environments can be much reduced through the use of this technology

Sensor fusion methodology for vehicle detection

A novel sensor fusion methodology is presented, which provides intelligent vehicles with augmented environment information and knowledge, enabled by vision-based system, laser sensor and global positioning system. The presented approach achieves safer roads by data fusion techniques, especially in single-lane carriage-ways where casualties are higher than in other road classes, and focuses on the interplay between vehicle drivers and intelligent vehicles. The system is based on the reliability of laser scanner for obstacle detection, the use of camera based identification techniques and advanced tracking and data association algorithms i.e. Unscented Kalman Filter and Joint Probabilistic Data Association. The achieved results foster the implementation of the sensor fusion methodology in forthcoming Intelligent Transportation Systems