Road condition acquisition and assessment are the key to guarantee their permanent availability. In order to maintain a country's whole road network, millions of high-resolution images have to be analyzed annually. Currently, this requires cost and time excessive manual labor. We aim to automate this process to a high degree by applying deep neural networks. Such networks need a lot of data to be trained successfully, which are not publicly available at the moment. In this paper, we present the GAPs dataset, which is the first freely available pavement distress dataset of a size, large enough to train high-performing deep neural networks. It provides high quality images, recorded by a standardized process fulfilling German federal regulations, and detailed distress annotations. For the first time, this enables a fair comparison of research in this field. Furthermore, we present a first evaluation of the state of the art in pavement distress detection and an analysis of the effectiveness of state of the art regularization techniques on this dataset.
Millions of kilometers are driven and recorded by car manufacturers and researchers every year to gather information about realistic traffic situations. The focus of these studies is often the recording of critical situations to create test scenarios for the development of new systems before introducing them into the market. This paper shows a novel Analysis and Investigation Method for All Traffic Scenarios (AIMATS) based on real traffic scenes. It also shows how to get detailed information about speeds, trajectories and behavior of all participants without driving thousands of kilometers at the example of conflict situations with animals. Basis of the AIMATS is the identification of the most relevant locations as "Points of Interest" (POI), the recording of the critical situations and their "base lines" at these POI. This paper presents a new method to identify critical scenarios involving both vehicles and animals as well as preliminary results of a study done in Saxony using this new method.
Camera-monitor systems (CMS) can be used in motor vehicles to display the driver's rear view on a monitor mounted inside the vehicle. This also offers the possibility of replacing conventional exterior mirrors with suitable CMS and thereby implementing new design concepts with aerodynamic advantages. However, as exterior mirrors are safety-relevant vehicle parts for securing the driver's indirect rear view (requirements specified in UN Regulation No. 46), the question arises whether CMS can provide an equivalent substitute for mirrors. In the scope of this study, CMS and conventional exterior mirrors were compared and assessed in test drives and static tests under different external conditions. On the one hand, the examination of technical aspects, and on the other hand, issues pertaining to the design of the human-machine interaction, were the objects of the study. Two vehicles were available for the trials with passenger vehicles: A vehicle, manufactured in small series, which is already equipped with CMS as sole replacement for the exterior mirrors, as well as a compact class vehicle which had a CMS retrofitted by the car manufacturer in addition to conventionally used exterior mirrors. The latter could be covered exclusively for trips with CMS. A tractor unit with semitrailer was available for the truck trials. The driver's cabin was equipped with a CMS system developed by the vehicle manufacturer. In general, it was shown that it is possible to display the indirect rear view sufficiently for the driver, both for cars and trucks, using CMS which meet specific quality criteria. Depending on the design, it is even possible to receive more information about the rear space from a CMS than is possible with mirror systems. It was also shown that the change from mirrors to CMS requires a certain period of familiarisation. However, this period is relatively short and does not necessarily result in safety-critical situations.
Kamera-Monitor-Systeme (KMS) können bei Kraftfahrzeugen dazu verwendet werden, die Sicht nach hinten für den Fahrer auf einem im Fahrzeug montierten Monitor darzustellen. Dies bietet auch die Möglichkeit, herkömmliche Außenspiegel durch geeignete KMS zu ersetzen und damit neue Designvarianten mit aerodynamischen Vorteilen umsetzen zu können. Da es sich bei den Außenspiegeln jedoch um ein sicherheitsrelevantes Fahrzeugteil zur Gewährleistung der indirekten Sicht nach hinten handelt (Anforderungen sind in der UN-Regelung Nr. 46 festgelegt), stellt sich die Frage, ob KMS einen gleichwertigen Ersatz für Spiegel bieten können. In der vorliegenden Studie wurden das KMS und der herkömmliche Außenspiegel während der Durchführung von Versuchsfahrten und statischen Tests unter verschiedenen äußeren Bedingungen verglichen und bewertet. Untersuchungsgegenstand waren zum einen technische Aspekte, zum anderen Fragestellungen zur Gestaltung der Mensch-Maschine-Interaktion. Für die Versuche mit Pkw standen zwei Fahrzeuge zur Verfügung: Ein Fahrzeug, das in Kleinserie hergestellt wird und bereits nur mit KMS als Ersatz für Außenspiegel ausgerüstet ist, sowie ein Fahrzeug der Kompaktklasse, an dem sowohl ein KMS als Nachrüstsatz verbaut war als auch die herkömmlich vorhandenen Außenspiegel. Letztere konnten für Fahrten ausschließlich mit KMS abgedeckt werden. Für die Versuche am Lkw stand eine Sattelzugmaschine mit Auflieger zur Verfügung. Die Fahrerkabine war mit einem nachgerüsteten KMS ausgestattet. Grundsätzlich hat sich gezeigt, dass es möglich ist, die indirekte Sicht nach hinten sowohl bei Pkw als auch bei Lkw durch KMS, die gewisse Qualitätskriterien erfüllen, für den Fahrer ausreichend darstellen zu können. Je nach Ausgestaltung bietet ein KMS sogar die Möglichkeit, mehr Information über den rückwärtigen Raum zu präsentieren als es mit Spiegelsystemen möglich ist. Es hat sich auch gezeigt, dass der Umstieg von Spiegeln auf KMS immer einer gewissen Gewöhnungsphase bedarf, diese jedoch verhältnismäßig kurz ist und nicht notwendigerweise zu sicherheitskritischen Situationen führt.
The Traffic Accident Research Institute at University of Technology Dresden investigates about 1,000 accidents annually in the area around and in Dresden. These datasets have been summarized and evaluated in the GIDAS (German Accident In-Depth Study) project for 13 years. During the project it became apparent that the specific traffic situation of a covert exit of a passenger car and an intersecting two-wheeler involves a high risk potential. This critical situation develops in a large part due to the lack of visibility between the driver and the intersecting bike. In this paper the accident avoidance potential of front camera systems with lateral field of view, which allows the driver to have an indirect sight into the crossing street area will be presented.
The changed focus in vehicle safety technology from secondary to primary safety systems need to evolve new methods to investigate accidents, high critical, critical and normal driving situations. Current Naturalistic Driving Studies mostly use vehicles that are highly equipped with additional measuring devices, video cameras, recording technology, and sensors. These equipped fleets are very expensive regarding the setup and administration of the study. Due to the great rarity of crashes it is additionally necessary to have a high distribution and a homogeneous distribution of subject groups. At the end all these facts are leading to a very expensive study with a manageable number of data. Smartphones are becoming more and more popular not only for younger people. Contrary to traditional mobile phones they are mostly equipped with sensors for acceleration and yaw rates, GPS modules as well as cameras in high definition resolution. Additionally they have high-performance processors that enable the execution of CPU-intensive tools directly on the phone. The wide distribution of these smartphones enables researchers to get high numbers of users for such studies. The paper shows and demonstrates a software app for smartphones that is able to record different driving situations up to crashes. Therefore all relevant parameter from the sensors, camera and GPS device are saved for a given duration if the event was triggered. The complete configuration is independently adjustable to the relevant driver and all events were sent automatically to the research institute for a further process. Direct after the event, interviews with the driver can be done and important data regarding the event itself are documented. The presentation shows the methodology and gives a demonstration of the working progress as well as first results and examples of the current study. In the discussion the advantages of this method will be discussed and compared with the disadvantages. The paper shows an alternative method to investigate real accident and incident data. This method is thereby highly cost efficient and comparable with existing methods for benefit estimation.