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Autonomous Vehicles (AVs) will soon be a reality on our roads. Up to now, their standard behaviour is predetermined since it is the result of programmed algorithms. Under risky traffic situations, however, they will face dilemmas such as, deciding between affecting the passenger or affecting others. Thus, in this experiment, we investigate how people solve a reframed version of the well-known Trolley-problem [Foot, P. 1967. “The problem of abortion and the doctrine of double effect,” Oxford Review 5: 5–15] under two conditions: when subjects actually drive a vehicle simulator, versus when they solve the same dilemma by programming a hypothetical AV. In both settings, the participants’ decisions have real monetary consequences, which affect others and themselves. Our Probit models indicate that subjects who program an AV and who are more cautious in terms of speed are less (more) likely to sacrifice a pedestrian (themselves) compared to those who actually drive and prefer a higher driving speed. Moreover, we find that the subjects’ choices are associated with risk aversion but not with moral beliefs or loss aversion. Implications of the driving vs programming discrepancies for the design of AVs algorithms are discussed.
The focus of this publication is on the development of lane-precise “Ground Truth” (GT) maps for the objective quality evaluation of automated driving functions. Therefore, attention is paid to the proper measurement of road geometry. The road geometry forms the basic layer of the HD maps.
A new map format Curved Regular Objects (CRO) is developed, which is based on the idea of OpenCRG®. For the evaluation of current Advanced Driver Assistance Systems (ADAS) an accurate High Definition (HD) maps as GT are necessary. This makes it possible to locate the high precision vehicle position and motion with centimeter accuracy. The aim is to achieve maximum accuracy of the absolute 3D positions when measuring lanes. This method for the generation of highly accurate GT maps promises an absolute accuracy of < ± 0.05 m. Various research activities benefit from the exact street reference at the Kempten University of Applied Sciences (UAS Kempten) in the Adrive Living Lab. First of all, the publication deals with the current Lane Keeping Assistant Systems (LKAS). The accuracy of the vehicle’s localization on the GT map and an objective evaluation of the LKAS is shown. In addition, the CRO data is used as a virtual sensor for the steering assistant in real time. Another application is the Visual Range Finder (VRF), which requires less computation power by using the CRO data. In addition, a current LKAS camera sensor performance is evaluated using CRO maps.
Fahrerassistenzsysteme und automatisiertes Fahren sind ein Megatrend in der Fahrzeugindustrie. Dabei stellen sich folgende Fragen: Können sich die Fahrzeughersteller auch noch in Zukunft markenspezifisch differenzieren, oder fahren alle Fahrzeuge gleich? Wie lässt sich eine Marken-DNA implementieren, und wie erzielt man den Übergang von Fahrspaß zum Spaß am Gefahrenwerden? Um Antworten zu generieren, sind klare Fahreigenschaftsziele "vor Kunde" und daraus die Anforderungen an die Fahrzeugsysteme und -komponenten abzuleiten. Aber was sind Fahreigenschaften im Kontext des assistierten und automatisierten Fahrens, und wie können diese in einer Entwicklung gezielt erreicht werden? Dieser Herausforderung hat sich Porsche gemeinsam mit der Hochschule für angewandte Wissenschaften Kempten und MdynamiX angenommen. Um die Eigenschaftsziele in allen Phasen der Entwicklung auf Gesamtfahrzeugebene validieren zu können, wurde eine modulare Simulationsumgebung, bestehend aus der Umfeldsimulation Vires VTD, Porsche-Fahrdynamikmodell und einem Reglersystemverbund inklusive Spurhalteregler aufgebaut. Die Co-Simulationsplattform AVL Model.Connect stellt dabei die Vernetzung der einzelnen Simulationen/Modelle dar und bietet entsprechende Funktionen, um diese durchgängig in den Verfahren Model in the Loop (MiL), Software in the Loop (SiL) und Hardware in the Loop (HiL) einzusetzen. Um die Spurführungsgüte, Fahrzeugreaktion und Fahrer-Fahrzeug-Interaktion realistisch abbilden zu können, ist ein gutes Lenkmodell mit Effekten im On-Center-Bereich notwendig.
Claim and Reality? Lane Keeping Assistant: the Conflict Between Expectation and Customer Experience
(2018)
In a current customer study with over 50 subjects, the customer wishes/acceptance of the Lane Keeping Assistance System were tested, evaluated and compared over 4000 km in a real road test. As a result, a considerable amount of potential can be seen for improvement in terms of customer acceptance for all three Lane Keeping Assistance Systems tested. The feeling of safety is the most important criterion, followed by the HMI and the edge guide. Furthermore, specific properties can be derived from the study, which must be fulfilled from the customer's point of view in order to fulfil the customer's wishes. There was a clear "GAP" between the degree to which the criteria were met and their importance. Only 27 % of customers would finally buy the LKAS on the basis of the product quality they have experienced. The results show that, in addition to differentiated expectations, there are primarily knowledge and experience-based deficits. Although a large part of the ADAS is known, only a few of the drivers surveyed have system expertise. Furthermore, it becomes clear from the questions according to Kano that, in addition to the pure transfer of knowledge, above all the subjective experience of the systems contributes to the enthusiasm of the users and to the increase in acceptance, provided that the first contact with the Lane Keeping Assistance represents a successful experience. Therefore, more attention should be paid to the capabilities and needs of end-users when designing vehicles. ADAS have the potential to counteract people's performance limitations, to support you where people reach their limits. However, only under the condition that they find acceptance in the target group and are used safely. The system is only used if it has the system behavior expected by the driver and he can therefore trust the system. Arndt also points out that too little confidence in ADAS means that it is not used. However, in the same context, she stresses that too much confidence can tempt the driver into relying too much on the ADAS, leading to system abuse. In addition to technical feasibility, knowledge of the requirements, needs and wishes of drivers is indispensable for their acceptance and use. Therefore, the recommendation to automotive manufacturers and suppliers is to involve various user groups in the product development process as early as possible, for example using the QFD method. In this way, ADAS are developed that meet the expectations of the customers. Especially the emotional comfort experience of the users, like lack of system trust, fear of negligence, distraction, paternalism and loss of control, will gain importance with increasing degree of automation. In order to lay the foundation for the acceptance of current developments in the field of highly automated and autonomous driving, drivers must develop a comprehensive system understanding and trust in comparison with today's ADAS of level 2 functions. Acceptance and trust in ADAS depends largely on a suitable and transparent human-machine interface. This theory has been also proven in this study. The customer wants to be informed about the current status of the system at any time during the journey via an understandable display concept and to be clear. He wants a predictable system that gives him enough time to intervene in the event of a system crash due to system limitations. In current systems, the warning comes - if at all - at the time of the drop. The driver has often already crossed the lane limit. Taking human situational awareness into account, such a short-term warning is critical. In addition, users' expectations for a Lane Keeping Assistance System do not always match the system's functionalities. According to the participants, the current system design does not offer any added value, as the driver must be ready to intervene at all times. This means that the driver not only has the task of checking himself for his primary task of driving, but must also monitor the availability of the system and prepare himself for unforeseen, in some cases also unforeseen drops off of the system. Since human hands over control to the vehicle, trust and the associated acceptance plays a central role. Ultimately the break-out of automated driving will decide on customer acceptance. "If only the engineer realizes the differences and understands the system, the customer has no benefit". The findings of the study show that in ADAS/AD development, the human being, or rather the customer should be placed much more at the center of development. Furthermore, it is necessary to focus on driving attributes and the driving experience in the sense of an attribute-based development.
Advanced Driver Assistance Systems (ADAS) warn, inform and perform monotonous tasks so that the strain on the driver's side is greatly reduced. They should lead to a further increase in customer mobility through greater comfort, efficiency and safety. As far as the theory goes - in practice, the comfort benefits addressed by the customer are not evident with all driver assistance systems. A previous study of the Lane Keeping Assistance System (LKAS) at Kempten University has shown that the physiological stress and perceived stress of the subjects using the LKAS during a test drive are significantly higher than if the same person refrains from using it. This finding clearly shows that the product "still" misses the purpose of comfort gain through relief. As a result, customer acceptance is very moderate. The motivation of this study was to identify requirements for the LKAS from the customer's point of view, to measure the degree of fulfilment in a competitive comparison and to learn from the customer assessments overall. By implementing these features, customer satisfaction with the LKAS is to be increased. The feeling of strain should lead to relief and consequently to an increase in the customer's acceptance of the product. Switching off or deactivating the system and the resulting increased safety risk should no longer occur in the future. The customer's wishes should be recognizable in the product specifications.
Validation of X-in-the-Loop Approaches for Virtual Homologation of Automated Driving Functions
(2018)
Securing and homologating automated driving functions presents a huge challenge for their market introduction due to an enormous number of scenarios and environment parameter combinations. Confronting conventional real world tests with the new challenges of automated driving is not feasible anymore and yields to a virtualization of the testing methods by means of X-in-the-Loop approaches. Since their validity is a key enabler for virtual homologation, this paper focuses on the validation of X-in-the-Loop approaches. A generic validation methodology is introduced and demonstrated for the specific use case of an automated longitudinal driving function. As a proof of concept equal scenarios are performed in real driving tests as reference and in two X-in-the-Loop approaches based on a test bed resp. a purely virtual co-simulation environment. The paper describes how a consistent implementation can be ensured to evaluate the collected data. First results show a promising correlation regarding multiple repetitions on the test bed and regarding the validation of both X-in-the-Loop approaches for a future virtual homologation of automated driving functions.
Advanced driver assistance systems (ADAS) of longitudinal control are widely used. In contrast to longitudinal controls, lateral controls are a growing market since this technique plays a major role in a successful introduction of automated driving. Customer and benchmark studies conducted by theUniversity of Applied Sciences Kempten and Consline AG have clearly shown that the vehicle behavior and customer experience such as tracking performance, driver-vehicle interaction, availability, degree of stress and the sense of security of today's lane keeping assistance systems are consistently rated as extremely unsatisfactory. As a consequence, there is a moderate level of trust and low customer acceptance. A new measuring method based on high-precision and accurate digital maps (ground truth) was developed. With this method, analysis of the entire chain of action, from sensor to tracking is possible. Position, direction and motion of the vehicle and its reference distance to road markings can be precisely measured in the digital map using a high-precision inertial measurement system (IMU) with RTK-DGPS and SAPOS correction service. The measuring method can be used in particular on public routes, since test areas are still insufficient due to the very small tracks and driving maneuver variations for lane keeping assistance systems. For a precise assessment of the sensor, planning and control performance as well as the overall driving characteristics, a very precise knowledge of the routes and the route excitation is required. For this purpose, high precision and accurate digital maps (ground truth) of real tracks were generated. A roof mounted stereo camera system combined with an RTK-DGPS IMU was used to provide offline-generated digital maps with high precision in the OpenDRIVE or OpenStreetMap format, as well as other common simulation formats like IPG CarMaker. In order to be able to carry out the dynamic driving evaluation as well as the simultaneous evaluation of the sensor, planning and control performance in the digital maps in real time, a route format with a regular grid, based on OpenCRG (Curved Regular Grid), was further developed. An IMU with RTK-DGPS and correction service (e.g. SAPOS) provides in real time the highly accurate position, direction and movement of the ego vehicle of up to two centimeters in the lateral and longitudinal direction. In addition, a special measuring steering wheel was built to objectify the driver-vehicle interaction, in particular the steering torque curve and the tracking. Particular attention was paid to the reuse of the original steering wheel with all functions, such as airbag, operation and hands-off detection. The novelty is the ability to measure the recognition, planning and control performance of environmental sensors, algorithms and controllers compared to the reference "Ground Truth". In addition, the driving characteristics of the entire vehicle can be assessed in terms of its tracking performance, driver-vehicle interaction, availability, degree of relieving and a sense of security. Another novelty is the consistent use of digital maps in driving tests as well as in the MIL / SIL / HIL simulation as a digital twin.
In a recent study with N = 50 subjects, the lane keeping assistant was tested on more than 3,500 km on public roads in the Allgäu. To test the various settings of the lane keeping assistant, different conditions were tested: 120km/h versus 160km/h as well as with versus without lane keeping assistant. The evaluation of the criteria for lane keeping assistant, such as edge management and degree of relief show a significant relationship with the experienced workload. The increased workload as well as stress when using the lane keeping assistant system could be detected and proved subjectively as well as with physiological measuring devices. The significantly higher stress experienced with the use of the lane keeping assistant system shows the immense importance that the further research on this system has.
Simulation methods supporting homologation of Electronic Stability Control in vehicle variants
(2017)
Vehicle simulation has a long tradition in the automotive industry as a powerful supplement to physical vehicle testing. In the field of Electronic Stability Control (ESC) system, the simulation process has been well established to support the ESC development and application by suppliers and Original Equipment Manufacturers (OEMs). The latest regulation of the United Nations Economic Commission for Europe UN/ECE-R 13 allows also for simulation-based homologation. This extends the usage of simulation from ESC development to homologation. This paper gives an overview of simulation methods, as well as processes and tools used for the homologation of ESC in vehicle variants. The paper first describes the generic homologation process according to the European Regulation (UN/ECE-R 13H, UN/ECE-R 13/11) and U.S. Federal Motor Vehicle Safety Standard (FMVSS 126). Subsequently the ESC system is explained as well as the generic application and release process at the supplier and OEM side. Coming up with the simulation methods, the ESC development and application process needs to be adapted for the virtual vehicles. The simulation environment, consisting of vehicle model, ESC model and simulation platform, is explained in detail with some exemplary use-cases. In the final section, examples of simulation-based ESC homologation in vehicle variants are shown for passenger cars, light trucks, heavy trucks and trailers. This paper is targeted to give a state-of-the-art account of the simulation methods supporting the homologation of ESC systems in vehicle variants. However, the described approach and the lessons learned can be used as reference in future for an extended usage of simulation-supported releases of the ESC system up to the development and release of driver assistance systems.