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Motorcycling is a fascinating kind of transportation. While the riders' direct exposure to the environment and the unique driving dynamics are essential to this fascination, they both cause a risk potential which is several times higher than when driving a car. This chapter gives a detailed introduction to the fundamentals of motorcycle dynamics and shows how its peculiarities and limitations place high demands on the layout of dynamics control systems, especially when cornering. The basic principles of dynamic stabilization and directional control are addressed along with four characteristic modes of instability (capsize, wobble, weave, and kickback). Special attention is given to the challenges of braking (brake force distribution, dynamic over-braking, kinematic instability, and brake steer torque induced righting behavior). It is explained how these challenges are addressed by state-of-the-art brake, traction, and suspension control systems in terms of system layout and principles of function. It is illustrated how the integration of additional sensors " essentially roll angle assessment " enhances the cornering performance in all three categories, fostering a trend to higher system integration levels. An outlook on potential future control systems shows exemplarily how the undesired righting behavior when braking in curves can be controlled, e.g., by means of a so-called brake steer torque avoidance mechanism (BSTAM), forming the basis for predictive brake assist (PBA) or even autonomous emergency braking (AEB). Finally, the very limited potential of brake and chassis control to stabilize yaw and roll motion during unbraked cornering accidents is regarded, closing with a promising glance at roll stabilization through a pair of gimbaled gyroscopes.
The project UR:BAN "Cognitive assistance (KA)" aims at developing future assistance systems providing improved performance in complex city traffic. New state-of-the-art panoramic sensor technologies now allow comprehensive monitoring and evaluation of the vehicle environment. In order to improve protection of vulnerable road users such as pedestrians and cyclists, a particular objective of UR:BAN is the evaluation and prediction of their behaviour and actions. The objective of subproject "WER" is development support by providing quantitative estimates of traffic collisions at the very start and predict potential in terms of optimized accident avoidance and reduction of injury severity. For this purpose an integrated computer simulation toolkit is being devised based on real world accidents (GIDAS as well as video documented accidents), allowing the prediction of potential effectiveness and future benefit of assistance systems in this accident scenario. Subsequently, this toolkit may be used for optimizing the design of implemented assistance systems for improved effectiveness.
Auf Grundlage von gebräuchlichen und anerkannten Modellen im Kontext der Fahrzeugführung werden zentrale Konzepte identifiziert, die mögliche Ansatzpunkte von langfristigen Wirkungen von Systemen zur Erkennung des Fahrerzustands bilden. Dabei werden nicht nur klassische Mehr-Ebenen-Modelle der Fahraufgabe mit beteiligten Kontrollprozessen berücksichtigt, sondern auch weitere Blickwinkel eingenommen, die in individuellen Persönlichkeitsmerkmalen, Einstellungen oder dem Fahrstil wichtige moderierende Einflussfaktoren identifizieren. Im Rahmen eines allgemeinen Evaluationsansatzes können grundlegende Taxonomien von Bewertungsverfahren, diverse Charakterisierungen von Bewertungsdimensionen sowie wichtige und zu dokumentierende Attribute und Fragestellungen von Evaluationsuntersuchungen beschrieben werden. In diesem Rahmen werden aus den betrachteten Modellen und Konzepten Kriterien abgeleitet, Aspekte der Operationalisierung erörtert sowie methodische Erhebungsansätze vorgeschlagen und diskutiert. Die Bandbreite der betrachteten Methoden ist vielfältig und reicht von unstrukturierten Befragungen über den Einsatz standardisierter Fragebögen bis hin zur maschinellen Erfassung von fahrrelevanten Kenngrößen über fahrzeugeigene Sensorsysteme. Besondere Bedeutung für die Realisierung einer Evaluationsstudie wird möglichst realitätsnahen Erhebungsumständen beigemessen. Daher wird als Rahmenansatz ein Field Operational Test zur Integration der diversen Erhebungsverfahren vorgeschlagen.
The evaluation of the expected benefit of active safety systems or even ideas of future systems is challenging because this has to be done prospectively. Beside acceptance, the predicted real-world benefit of active safety systems is one of the most important and interesting measures. Therefore, appropriate methods should be used that meet the requirements concerning representativeness, robustness and accuracy. The paper presents the development of a methodology for the assessment of current and future vehicle safety systems. The variety of systems requires several tools and methods and thus, a common tool box was created. This toolbox consists of different levels, regarding different aspects like data sources, scenarios, representativeness, measures like pre-crash-simulations, automated crash computation, single-case-analyses or driving simulator studies. Finally, the benefit of the system(s) is calculated, e.g. by using injury risk functions; giving the number of avoided/mitigated accidents, the reduction of injured or killed persons or the decrease of economic costs.
Since its creation in 2011 the Pre-Crash-Matrix (PCM) offers the possibility to observe the pre-crash phase until five seconds before crash for a wide range of accidents. Currently the PCM contains more than 8.000 reconstructed accidents out of the GIDAS (German In-Depth Accident Study) database and is enlarged continuously by more than 1.000 cases per year. Hence, a detailed investigation of active safety systems in real accident situations has been made feasible. The PCM contains all relevant data in database format to simulate the pre-crash phase until the first collision of the accident for a maximum of two participants. This includes the definition of the participants and their characteristics, the dynamic behavior of the participants as time-dependent course for five seconds before crash as well as the geometry of the traffic infrastructure. The digital sketch of the accident and information from GIDAS as well as from supplementary databases represent the main input for the simulation of the pre-crash phase of an accident with the VUFO simulation model VAST (Vufo Accident Simulation Tool). This simulation in turn embodies the foundation of the PCM. The PCM underlies continual improvements and enhancements in consultation with its users. In addition to collisions of cars with other cars, pedestrians, bicycles and motorcycles the PCM now also covers car to object and car to truck collisions. The paper illustrates car to truck collisions as a showcase and explains perspectives for further developments. In 2016 a more detailed definition of the contour of the vehicle was added. Furthermore, the geometrical surroundings of the accident site will be provided in a new structure with a higher level of detail. Thus, a precise classification of road marks and objects is possible to further improve the support of developing and evaluating ADAS. This paper gives an overview about the latest developments of the PCM with its innovations and provides an outlook to upcoming enhancements. Besides potential areas of application for the development of ADAS are shown.
Rear-end collisions are the most frequent same and opposite-direction crashes. Common causes include momentary inattention, inadequate speed or inadequate distance. While most rear-end collisions in urban traffic only result in vehicle damage or slight injuries, rear-end collisions outside built-up areas or on motorways usually cause fatal or serious injuries. Driver assistance systems that detect dangerous situations in the longitudinal vehicle direction are therefore an essential safety plus. In view of this, for ADAC, systems that alert drivers to dangerous situations and initiate autonomous braking complement ESC as one of the most important active safety features in modern vehicles. The aim of ADAC is to provide consumers with technical advice and competent information about the systems available on the market. Reliable comparative tests that are based on standardised test criteria may provide motorists with important information and help them make a buying decision. In addition, they raise consumer awareness of the systems and speed up their market penetration. The assessment must focus on as many aspects of effectiveness as possible and include not only autonomous braking but also collision warning and autonomous brake assist. The work of the ADAC accident research is the development of the testing scenarios with direct link to accident situations and the identification of useful test criteria for testing.
Unfälle im Straßenverkehr sind in aller Regel Konsequenzen normalen Fahrverhaltens, das an eine bestimmte Situation nicht angepasst war und daher zum Unfall beigetragen hat. Zur Klassifikation dieses mutmaßlich fehlerbehafteten Verhaltens wurde im hier berichteten Projekt eine Taxonomie entwickelt. Sie dient der Klassifizierung von Fahrerfehlverhalten und integriert Aspekte des menschlichen Informationsverarbeitungsprozesses sowie die drei Fehlertypen von RASMUSSEN (1983). Als Bestimmungsstücke beinhaltet die Taxonomie Fehlertypen (regel-/wissens-/fertigkeitsbasiert) und Entscheidungsknoten mit Fragen, deren Beantwortung den Analysten zum jeweiligen Fehler führt. Zusammengefasst bietet die erarbeitete Taxonomie eine breite Anwendbarkeit für die Klassifikation von Fahrfehlern und fehlerfreiem Verhalten bei Manövern, kritischen Situationen bis hin zu Beinaheunfällen oder Unfällen, z. B. zur Harmonisierung der (Video-)Auswertung von FOT- und NDS-Datensätzen oder für In-Depth-Unfallerhebungen. Die Taxonomie wird komplementiert durch eine Übersicht über Fehlervorläuferbedingungen, die im Sinne von Genotypen (HOLLNAGEL 1998) in ihrer jeweiligen Ausprägung auslösende und begünstigende Bedingungen für Fehler, Beinaheunfälle und Unfälle darstellen. Die Übersicht ist als erweiterbares strukturierendes Dokument zu sehen, welches je nach wissenschaftlichen Erkenntnissen verändert werden kann. Gemeinsam mit der Taxonomie bildet sie die Basis für die Ableitung von Fahrerassistenzbedarf und andere Maßnahmen, zur Generierung von Hypothesen und zur strukturierten Sammlung von Studienergebnissen. Der vorliegende Bericht adressiert die FOT- und NDS-Community sowie allgemein verkehrspsychologisch-wissenschaftlich Interessierte. In acht Kapiteln widmet er sich den Arbeitsschritten und Ergebnissen der Taxonomieentwicklung.
The main focus of the benefit estimation of advanced safety systems with a warning interface by simulation is on the driver. The driver is the only link between the algorithm of the safety system and the vehicle, which makes the setup of a driver model for such simulations very important. This paper describes an approach for the use of a statistical driver model in simulation. It also gives an outlook on further work on this topic. The build-up process of the model suffices with a distribution of reaction times and a distribution of reaction intensities. Both were combined in different scenarios for every driver. Each scenario has then a specific probability to occur. To use the statistical driver model, every accident scene has to be simulated with each driver scenario (combinations of reaction times and intensities). The results of the simulations are then combined regarding the probabilities to occur, which leads to an overall estimated benefit of the specific system. The model works with one or more equipped participants and delivers a range for the benefit of advanced safety systems with warning interfaces.
The Swedish National Road Administration (SNRA), the Japanese Automobile Research Institute (JARI) and the Federal Highway Research Institute (BASt) are co-operating in the International Harmonized Research Activities on Intelligent Transportation Systems (IHRA-ITS). Under this umbrella a joint study was conducted. The overall objective of this study was to contribute to the definition and validation of a "battery of tools" which enables a prediction and an assessment of changes in driver workload due to the use of in-vehicle information systems (IVIS) while driving. In this sense \"validation\" means to produce empirical evidence from which it can be concluded that these methods reliably discriminate between IVIS which differ in terms of relevant features of the HMI-design. Additionally these methods should also be sensitive to the task demands imposed on the driver by the traffic situation and their interactions with HMI-design. To achieve these goals experimental validation studies (on-road and in the simulator) were performed in Sweden, Germany and Japan. As a common element these studies focused on the secondary task methodology as an approach to the study of driver workload. In a joint German-Swedish on-road study the Peripheral Detection Task (PDT) was assessed with respect to its sensitivity to the complexity of traffic situations and effects of different types of navigation systems. Results show that the PDT performance of both the German and the Swedish subjects reflects the task demands of the traffic situations better than those of the IVIS. However, alternative explanations are possible which will be examined by further analyses. Results of this study are supplemented by the Japanese study where informational demands induced by various traffic situations were analysed by using a simple arithmetic task as a secondary task. Results of this study show that relatively large task demands can be expected even from simple traffic situations.
The sequence of accident events can be classified by three essential phases, the pre-crash-sequence, the crash-sequence and the post-crash-sequence. The level of reliability of the information in the GIDAS-database (German In Depth Accident Study) is provided predominantly on the passive side. The period to evaluate active safety systems begins already in the pre-crash-sequence. The assessment of the potential of sensor- or communication-based active safety systems can only be accomplished by a detailed analysis of the pre-crash-phase. Hence the necessity to analyze the early period of the accident event in detail arises. This is possible with the help of the digital sketches of the accident site and the simulation of the accident by a simulation method of the VUFO GmbH. After simulating the pre-crash scenario it is possible to generate additional and standardized data to describe the pre-crash-sequences of an accident in a very high detail. These data are documented in a second database called the GIDAS Pre-Crash-Matrix (PCM). The PCM contains various tables with all relevant data to reproduce the pre-crash-sequence of traffic accidents from the GIDAS database until 5 seconds before the first collision. This includes parameters to describe the environment data, participant data and motion or dynamic data. This paper explains the creation of the PCM, the simulation itself and the contents and structure of the PCM. With this information of the pre-crash-sequence for various accident scenarios an improved benefit estimation and development of active safety systems can be made possible.