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Comfort evaluation on a dynamic driving simulator with advanced tire, road and vehicle models
(2024)
The topics of automated driving and digitization are becoming increasingly im-portant and will shape the future of mobility. The potential of this technology is enormous. Concurrently, manufacturers want to continue to differentiate them-selves in driving characteristics typical of their brands. Rapid developments re-garding technological changes as well as legal regulations combined with short development times present new challenges for the entire automotive industry. In this context, virtualization and front-loading methods play a major role within the vehicle development. There has been a clear trend of pushing virtual devel-opment via simulation to reduce the number of necessary prototypes. Since however, both engineers and management still rely heavily on the crucial in-sights gained by real road tests, subjective closed-loop assessment must remain a part of this virtual process. Driving simulators have the potential to bridge these gaps, allowing engineers and test drivers to subjectively experience and assess new systems in an early virtual phase of development.
Kempten University of Applied Sciences is working with research and technol-ogy partners to research and further develop their dynamic driving simulator. With the goal to develop use-case specific methods for virtual vehicle develop-ment, the simulator’s novel motion platform is used specifically for research projects in areas requiring high dynamic performance such as vehicle dynamics and ride. This paper describes the methods and solutions developed in an R&D project investigating the simulator’s capabilities for ride comfort evaluation, such as primary & secondary ride. With the goal to enable experienced test drivers to perform a subjective ride evaluation in a very early development phase, the simulator’s real-time environment was extended with the highly so-phisticated tire model FTire. This paper provides an overview of the system’s performance regarding subjective ride assessment. It presents a brief insight into the detailed road modelling and describes the measures taken to ensure real-time capability of the individual model interfaces. Objective performance evaluation shows the benefit of this work for comfort evaluation in early phases of virtual development.
Motion sickness research has always been shaped by current events. With the advent of highly automated vehicles (HAVs), the topic is currently being revisited as 60% of users of HAV functions are expected to suffer from motion sickness. Failure to address this condition will jeopardize user acceptance of HAV functions. We investigated the vestibular mechanisms of motion misinterpretation and hypothesized that cross-coupled stimuli induce more sensory conflict and lead to higher motion sickness incidence compared to the non-coupled control condition. We conducted an experiment on a dynamic driving simulator with realistic motion profiles and analyzed the influence of cross-coupled motion on motion sickness incidence. Results show no significant difference in motion sickness incidence between cross-coupled and non-coupled motion profiles. Further research is needed to investigate the thresholds of the Coriolis effect and should include the measurement of compensatory or inertial head motion of participants.
Advanced Driver Assistance Systems and Automated Driving are a megatrend in the automotive industry. The following questions arise: Will vehicle manufacturers still be able to differentiate themselves “brand-specifically” in the future or will all vehicles be perceived the same when being driven? How can a brand DNA be implemented and how can the transfer of “fun to drive” to “fun to be driven” be achieved? In order to reach this, clear driving characteristic goals – in front of the customer – should be defined and the requirements for vehicle systems and components shall be derived from this. However, what are driving characteristics in the context of assisted and automated driving, Figure 1, and how can those specifically be achieved in the development? Porsche has addressed this question together with the University of Applied Sciences Kempten and MdynamiX. How can an attribute-based development look like and how can Porsche effectively design a brand-typical characteristic in this area?
Advanced Driver Assistance Systems (ADAS) and Highly Automated Driving Systems (HAD) are among the most important megatrends in the automotive development. Accompanying this one big question arises: do all assisted and automated driving cars drive the same or will vehicle manufacturers be able to differentiate themselves with DNA of their own? And - especially for a sportscar-manufacturer like Porsche – how can ADAS and HAD impart typical attributes like driving fun and sportiness, Figure 1? In order to achieve this, clear driving characteristic goals (from a customer’s point of view) must be defined and the system requirements for ADAS and HAD (including all components like sensors, ECU’s and actors) shall be derived from this. However, what are driving and brand characteristics in the context of assisted and automated driving? And how can those be realized in the development? Porsche has addressed this question together with the University of Applied Sciences Kempten and MdynamiX.
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.
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.
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.
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) 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.
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.
Kamerabasierte Rückspiegel bieten das Potenzial, ein größeres Sichtfeld zu schaffen und rückwärtige Verkehrsinformationen besser anzuzeigen. Das Adrive Living Lab, eine Forschungseinrichtung der Hochschule Kempten, hat in Kooperation mit MdynamiX, einem An-Institut der Hochschule München, und Gentex eine Kundenakzeptanzuntersuchung sowie eine Feldstudie zu einem kamerabasierten Hybridspiegel durchgeführt. Dabei wurden die Nutzererfahrungen, die Nutzerakzeptanz und die Kundenwünsche im Bezug auf einen digitalen Rückspiegel im realen Straßenverkehr analysiert und ausgewertet.
The disruptive change of the future vehicle fleet, new technologies and short development times challenge the entire automotive industry. Every test drive and every test kilometer is cost-intensive and, on top of that, in some cases hardly feasible for safety reasons. The goal is crystal clear: to shift development more and more to simulation and reduce the number of prototypes. However, the real driving experience in a road test still offers essential insights for engineers and management. Driving simulators have the potential to bridge these gaps. They can create the possibility for engineers and test subjects to experience the subjective driving impressions of new functions, systems and driving attributes already in the virtual phase. In order to achieve a comparable driving experience on a driving simulator and thus a comparable evaluation result with the driving test, the methods as well the driving simulator environment must be aligned with the targeted applications and use cases. Kempten University of Applied Sciences has set up a novel dynamic driving simulator from AB Dynamics (ABD). Together with research and technology partners, technologies and methods are being further developed on this basis in order to achieve the above-mentioned goal. The paper presents potential, methods as well as use cases relevant for chassis development. The paper also gives a first-hand account of the experience.
This paper presents a detailed analysis and characterization of Subjective Assessment Indicators for evaluating manual as well as fully automatic parking maneuvers. Parking is a huge challenge for many drivers. With the introduction of autonomous driving, parking maneuver assistants are essential functional components. For the development of automatic parking assistants, a detailed characterization of a subjective evaluation is essential. The characterization analysis presented here is based on general Subjective Assessment Indicators, which cover the subjective overall performance of a parking maneuver on a customer-oriented level in as many facets as necessary. This paper shows meaningful characteristics of the individual Subjective Assessment Indicators validated in a driving study with 497 performed parking maneuvers. The study results reveal different degrees of intensity of the characterizations for the different driving maneuvers. Here, it is shown that the characterization of the Final Parking Position has different reference points for longitudinal and lateral parking maneuvers. Furthermore, it was shown that an additional characteristic ‘‘Driving-Off Behavior’’ is required for the evaluation of the Safety Feeling, but for Parking Comfort the ‘‘Lateral Acceleration’’ and for Dynamic Performance the ‘‘Distance Traveled’’ can be neglected. The characteristics described in this paper can be used for all parking maneuvers and vehicle types. It forms the basis for a complete evaluation and enables OEMs to apply their individual requirements in the development of parking assistants.
During the development of state-of-the-art driver assistance systems and highly autonomous driving functions, there is a demand for reliable research vehicle platforms that can be used in a variety of applications. Especially for data-driven machine learning approaches, a large amount of measurement data obtained from multimodal sensors is needed. This paper presents a Robot Operating System (ROS) based prototype vehicle that is built on a Porsche Cayenne, which provides a dedicated test environment for autonomous research. To bridge the gap between pure research and actual production vehicles, the platform features near-series placement of sensors and the use of the built-in camera and actuators. Open-source packages and a containerized software architecture make the system reusable and easy to extend in terms of hardware and algorithms. Furthermore, we describe our approach for data recording and long-term persistence.
One of the most commonly used advanced driver assistance system is adaptive cruise control. Although many cars are equipped with such a driver assistance system, the development is still based on subjective evaluation indices. The design of adaptive cruise control could be more powerful and reach more customer acceptance when a design process with specific values to ensure good driving characteristics is used. Such an objective based process is still state of the art of classic chassis development, but typically not used for advanced driver assistance systems.
To achieve this, use case-based scenarios are deduced from properties. A scenario simulation is used to generate information about important KPIs and collect data to develop an automated data analysis tool. To correlate subjective KPIs with objective measurement values an inertial navigation system in each car with differential GPS (RTK) and a wireless connection between both cars is installed. With the aid of this measurement system differential speed, acceleration and distances are calculated in a precise way. It also contains a fully controllable target vehicle in longitudinal and lateral direction to generate manoeuvres with high reproducibility. An analysis algorithm automatically calculates KPIs and displays important diagrams after each test run. This leads to a complete system analysis test in two days for each car. The comparison of target KPIs and subjective evaluation criteria shows whether the system reached its goals or if improvements are necessary. For this purpose the project partners Porsche, University of Applied Sciences Kempten and MdynamiX have joined their forces.
Today’s validation of driver assistance systems and automated driving functions in state-of-the-art vehicles, still takes place mostly on the proving ground or on the real road. But driving tests can only be performed with the finished vehicle and fully implemented function, which might be difficult in early stages of the development process. Those purely physical tests are also time consuming and lack reproducibility. Hence, the validation process is guided more and more by simulation tools to reduce the number of tests that have to be driven. The pure simulation offers benefits, such as the functions can be tested in early stages of the development without the need for a physical carrier vehicle. Also, the flexibility of the simulation is high, since all variations of driving scenarios, also safety critical, can be driven easily and much faster than real time. On the other side, compared to the physical test, the parameterization of supplemental models is sometimes difficult and the risk of errors due to model abstraction is high.
Automated and autonomous vehicles will fundamentally change the way we humans experience individual mobility. Customers would like to use the time gained for secondary tasks such as private or professional work, for consuming entertainment media or simply for relaxing. Vehicle motion and vibration imposed on the human body in this environment also lead to fatigue and discomfort. A threshold for comfortable task performance is currently not known, however this could be important knowledge for designing future active chassis systems. This exploratory study with 12 subjects examined motion comfort during two secondary tasks on a digital road with the help of a dynamic driving simulator. Subjective data from questionnaires as well as objective data from inertial sensors were analyzed. Evaluations indicate a threshold for comfortable environments that should be further examined in future studies.
A major concern about advanced motion-based simulators is their level of fidelity i.e., how close the motion sensation in a simulator is to the one perceived in a real vehicle. In this study, we collect the assessment from an exceptional sample composed by n = 33 automotive industry experts who were asked to evaluate the fidelity in terms of steering, braking and speed. Given the subjective nature of our measure, we propose a censored-data Tobit regression model that accounts for this issue, thus providing more accurate estimations. Our results show that, on average, experts evaluated the steering actions close to the maximum level of fidelity. However, braking and speed were evaluated lower in realism, and in fact both diminished the overall fidelity judgement by up to 50%. Moreover, coefficients indicate that steering contributes more to the judgement of fidelity than braking and speed actions. Heterogeneity in the experts' responses and general implications are discussed.
As the development of advanced driver assistance systems (ADAS) continues, more and more software functions and sensors are being introduced to the market. This is accompanied by an increase in the amount of data that has to be transmitted to multiple receivers in the vehicle under hard real-time requirements. The use of deterministic and non-deterministic Fieldbus protocols enables communication between sensor and actuator or ECUs. For the purpose of verifying and validating the developed software modules, but also for type approval, an objective and thus data-driven toolchain is mandatory. By using suitable middleware such as Robotic Operating System (ROS), the complexity of integrating multiple (reference) sensors as well as prototypical software functions can be broken down into subtasks and thus distributed to the hardware in a computationally efficient manner. Recording and manipulating sensor ECU communication while driving is also possible under certain circumstances. However, at least to our knowledge, there is no public ROS driver available to integrate automotive-specific fieldbus protocols except for CAN. In the following paper, we introduce a generic and open-source framework for integrating on-board communication of various Fieldbus protocols and demonstrate the integration in ROS as a real-world use case. To validate the presented methodology, we perform a time analysis of the presented ROS node and compare it to a ROS-independent reference measurement system while performing a standardized vehicle dynamic driving test. In addition, we objectively compare two different on-board sensors from a series vehicle with two distinct reference sensors in a real-world scenario.
Safeguarding and type approval of automated vehicles is a key enabler for their market launch in our complex traffic environment. Scenario-based testing by means of computer simulation is becoming increasingly important to cope with the enormous complexity and effort. However, there is a huge gap when assessing the safety of the virtual vehicle while the real vehicle will drive on the road. Simulation must be accompanied by model validation to ensure its credibility since errors and uncertainties are inherent in every model. Unfortunately, this is rarely addressed in the current literature. In this paper, a modular process is presented covering both model validation and safeguarding. It is characterized by the fact that it quantifies a large number of errors and uncertainties, represents them in the form of an error model, and ultimately integrates them into the safeguarding results. It is applied to a type-approval regulation for the lane-keeping behavior of a vehicle under various scenario conditions. The paper contains a thorough validation of the methodology itself by comparing its results with actual ground truth values. For this comparison, a binary classifier and confusion matrices are used that relate the binary type-approval decisions. The classifier demonstrates that the methodology of this paper identifies a systematic error of the simulation model across several safeguarding scenarios. Finally, the paper provides recommendations for alternative configurations of the modular methodology depending on different requirements.
Due to the rapid progress in the development of automated vehicles over the last decade, their market entry is getting closer. One of the remaining challenges is the safety assessment and type approval of automated vehicles, as conventional testing in the real world would involve an unmanageable mileage. Scenario-based testing using simulation is a promising candidate for overcoming this approval trap. Although the research community has recognized the importance of safeguarding in recent years, the quality of simulation models is rarely taken into account. Without investigating the errors and uncertainties of models, virtual statements about vehicle safety are meaningless. This paper describes a whole process combining model validation and safety assessment. It is demonstrated by means of an actual type-approval regulation that deals with the safety assessment of lane-keeping systems. Based on a thorough analysis of the current state-of-the-art, this paper introduces two approaches for selecting test scenarios. While the model validation scenarios are planned from scratch and focus on scenario coverage, the type-approval scenarios are extracted from measurement data based on a data-driven pipeline. The deviations between lane-keeping behavior in the real and virtual world are quantified using a statistical validation metric. They are then modeled using a regression technique and inferred from the validation experiments to the unseen virtual type-approval scenarios. Finally, this paper examines safety-critical lane crossings, taking into account the modeling errors. It demonstrates the potential of the virtual-based safeguarding process using exemplary simulations and real driving tests.
Unified Framework and Survey for Model Verification, Validation and Uncertainty Quantification
(2020)
Simulation is becoming increasingly important in the development, testing and approval process in many areas of engineering, ranging from finite element models to highly complex cyber-physical systems such as autonomous cars. Simulation must be accompanied by model verification, validation and uncertainty quantification (VV&UQ) activities to assess the inherent errors and uncertainties of each simulation model. However, the VV&UQ methods differ greatly between the application areas. In general, a major challenge is the aggregation of uncertainties from calibration and validation experiments to the actual model predictions under new, untested conditions. This is especially relevant due to high extrapolation uncertainties, if the experimental conditions differ strongly from the prediction conditions, or if the output quantities required for prediction cannot be measured during the experiments. In this paper, both the heterogeneous VV&UQ landscape and the challenge of aggregation will be addressed with a novel modular and unified framework to enable credible decision making based on simulation models. This paper contains a comprehensive survey of over 200 literature sources from many application areas and embeds them into the unified framework. In addition, this paper analyzes and compares the VV&UQ methods and the application areas in order to identify strengths and weaknesses and to derive further research directions. The framework thus combines a variety of VV&UQ methods, so that different engineering areas can benefit from new methods and combinations. Finally, this paper presents a procedure to select a suitable method from the framework for the desired application.
When will automated vehicles come onto the market? This question has puzzled the automotive industry and society for years. The technology and its implementation have made rapid progress over the last decade, but the challenge of how to prove the safety of these systems has not yet been solved. Since a market launch without proof of safety would neither be accepted by society nor by legislators, much time and many resources have been invested into safety assessment in recent years in order to develop new approaches for an efficient assessment. This paper therefore provides an overview of various approaches, and gives a comprehensive survey of the so-called scenario-based approach. The scenario-based approach is a promising method, in which individual traffic situations are typically tested by means of virtual
simulation. Since an infinite number of different scenarios can theoretically occur in real-world traffic, even the scenario-based approach leaves the question unanswered as to how to break these down into a finite set of scenarios, and find those which are representative in order to render testing more manageable. This
paper provides a comprehensive literature reviewof related safety-assessment publications that deal precisely with this question. Therefore, this paper develops a novel taxonomy for the scenario-based approach, and classifies all literature sources. Based on this, the existing methods will be compared with each other and,
as one conclusion, the alternative concept of formal verification will be combined with the scenario-based approach. Finally, future research priorities are derived.
Deep learning for lateral vehicle control – an end-to-end trained multi-fusion steering model
(2019)
Deep Learning based behavior reflex methods found their way into modern vehicles. To model the human driving behavior it is not sufficient to rely solely on individual, noncontiguous camera frames without taking vehicle signals or road specific features into account. In this work four temporal fusion methods are evaluated based on three different Deep Learning models. The proposed spatio-temporal Mixed Fusion model extends the present end-to-end models and consist of multiple levels of fusions. The raw image data from a single front facing camera is mixed with recorded vehicle data and a map based predicted road bank angle gradient vector. The model accesses multiple time axes: temporal features of multiple image frames are extracted through a combination of Convolution and LSTM layers while it can also make assumptions about the future road condition with the use of upcoming Ground Truth road bank angle changes. Experiments are performed on a recorded data set of real world drivings. Results show, that this approach leads to an accurate imitation of the human driver with an inference capability of more than 60 FPS.
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.
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.
Die geplante Real-Driving-Emissions-Gesetzgebung erfordert neue Antriebskonzepte, die der Dynamik bei realen Straßenfahrten gerecht werden. Bei der Entwicklung dieser Technologien stoßen die traditionellen Methoden und Werkzeuge an ihre Grenzen. Das Institut für Verbrennungskraftmaschinen und Fahrzeugantriebe der TU Darmstadt (VKM) und AVL forschen daher gemeinsam an neuen Lösungen, die bereits bestehende Entwicklungsumgebungen weiterentwickeln können.
Driving simulators are used to test under reproducible conditions, however, they must be validated for each application. This guarantees that the gathered data on the simulator is representative of real vehicle data. This paper examines and compares objective data from 20 drivers that are recorded on a six degrees of freedom (DOF) high dynamic driving simulator and a passenger vehicle in the compact class on a proving ground. The purpose of this study is to investigate the comparability of the behavior of the subjects in their driving task on the driving simulator compared to the real driving test. The driving maneuvers include the 18 m slalom and an ISO double lane change (ISO 3888-2). The real car’s measurement setup is composed of an inertial measurement unit and access to the chassis CAN messages. The driving simulator is equipped with the same real electrical power steering as the test vehicle. Furthermore, a fully validated vehicle model is used in the simulation. Objective key performance indicators such as maximum steering wheel angle, steering wheel torque, lateral acceleration, yaw rate, and yaw gain deviate from around -18% to 10% in the slalom, with the majority of parameters not showing significant differences. Bigger differences are found for the double lane change. Overall, the results demonstrate a satisfactory degree of correlation between the driver behavior on the driving simulator and the real vehicle, even up to achieving absolute validity.
In the early phase of new vehicle system developments, it is crucial to fully define and optimize working system and functional architectures. Architecture definition and validation in turn requires a quick and accurate evaluation of a system‟s overall performance. Modeling and simulating a complete vehicle system, however, is complex and in many cases was either technically not achievable or simply has been omitted within the development process. It is the utmost challenge in system modeling and simulation to realistically reflect interaction of various electrical, mechanical, thermal, and software elements as attributed to individual system modules and their relations. State-of-the-art tools meanwhile bear this capability. In this paper we present an approach how they may effectively and efficiently be incorporated into a car system development process. To accomplish this target, we „virtualize‟ all system entities while defining and reflecting all relevant system aspects. Our proposed development flow allows simulating, evaluating, and validating complete vehicle systems and their behavior. The proposed flow will sustainably change car system development processes.
The present study investigated the mental workload associated with driving a vehicle equipped with Lane Keeping Assistance System (LKAS). Specifically, an experiment was carried out with16participants driving with LKAS in four real-world scenarios. Effects on mental workload were evaluated with psychophysiological measures such as heart rate and skin conductance response (SCR). The driving performance, which is also a measure of evaluating mental workload, was assessed by measure such as steering reversal rate, variation of lateral position and steering effort. The result suggested that LKAS has reduced physical workload in the steering task. However, the lane keeping performance was not improved. Moreover, the NASA-TLX showed that participants perceived higher mental workload while driving with LKAS. This effect was mirrored in the SCR. The objective data showed that LKAS was associated with higher steering reversal rate, which might explain the reason of participants perceiving higher mental workload. Overall, it was suggested that the mental workload was higher with the tested LKAS.
Parking – Evaluation of Manual and Automated Parking Maneuvers with Subjective Assessment Indicators
(2021)
In this paper, an analysis of a subjective evaluation of manually and automatically executed longitudinal and lateral parking maneuvers using Subjective Assessment Indicators is presented. With the introduction of autonomous driving, parking maneuver assistants are essential functional components. Driver assistance systems will only be accepted if they perform decisively better than the human driver. Whether the performance of such a system meets expectations is ultimately a subjective impression. For this reason, an analysis of the parking performance of humans and parking assistant systems is carried out based on a new innovative subjective evaluation method. This new subjective evaluation method is based on the so-called Subjective Assessment Indicators which cover the relevant areas of a parking maneuver but still do not reach a level of detail that makes evaluation unsuitable for customer. Using the new subjective evaluation method, a driving study was conducted with 21 participants and two different test vehicles. The participants evaluated both manual and fully automated longitudinal and lateral parking maneuvers purely digitally using an evaluation app. As the results of the study show, parking assistants still have notable deficits compared to human performance in some evaluation areas and show considerable potential for improvement. As the subjective evaluation method used is suitable for all parking maneuvers and vehicle types, the results of this and potentially further studies form the basis for determining Key Performance Indicators for parking maneuvers. This enables virtual development of automated parking systems, as a link can be established to subjective customer evaluations.
Die assistierte Querführung wie das Spurhalteassistenzsystem ist ein Schlüssel zur erfolgreichen Einführung des hochautomatisierten Fahrens. Was empfindet der Kunde beim Einsatz von Spurhalteassistenzsystemen, und welche psychischen und physischen Belastungen lösen die verschiedenen Fahrsituationen aus? Welche Erwartungen hat er an das Fahrerlebnis? Was wird als angenehm und unangenehm empfunden, was wird akzeptiert, und welche Attribute sind inakzeptabel? Die Hochschule Kempten und MdynamiX sind diesen Fragen in breit angelegten Studien mit insgesamt 120 Probanden im Realeinsatz nachgegangen.
Advanced driver assistance systems (ADAS) support the driver in certain traffic situations and can increase road safety. For this appropriate interaction, concepts between the driver and the assistance systems are required, which focuses on driver’s needs. In a user-centered study with N = 48 subjects, interviews and questionnaires were conducted during a test drive in real road traffic in order to test and evaluate the lane keeping assistant system (LKAS) with head-up display (HUD). In addition, two current premium vehicles from various manufacturers were used to investigate the influence of the HUD on the user experience and to derive optimization potential for current and future automatic driving functions. In comparison to the test rides with LKAS in combination without HUD (with head-down display), it can be determined that there is a positive influence of HUD on the experience with LKAS.
Study to assess the controllability after chassis component damages on the dynamic driving simulator
(2022)
The demands for shorter development times, reduced costs and prototypes make a greater use of virtual methods in the development process necessary. However, the real driving experience in a road test still offers essential insights for engineers and management. In particular, controllability tests through structurally damaged chassis components are extremely time-consuming in road tests and can therefore only be conducted to a limited extent. Moreover, they are often not reproducible or not representative, since the occurrence of damage is difficult to control over time and the tests can also be dangerous. On the other hand, purely virtual methods cannot adequately represent the driver's reaction and driver assessment of controllability.
In a feasibility and potential study, solutions and methods based on a dynamic driving simulator were developed. The Driver-in-the-Loop method using a driving simulator enables the precise control of a wide range of damage patterns and a broad spectrum of driving situations, while always offering a high level of safety in the test conduction. In addition, it records the human reaction and makes the controllability subjectively experienceable and assessable. Certain variants can also be presented to the management with this method and made experienceable for the decision-makers. In this way, important decisions and setting the course in the development can be supported. Overall, the method could save a lot of time and money.
The University of Applied Sciences Kempten together with the affiliated institute MdynamiX has build-up a dynamic driving simulator with a novel rail and movement concept, which was designed for vehicle dynamics and enables further applications such as ADAS/AD, HMI, functional safety. The concept was developed by Williams F1 and industrialized by AB Dynamics. The high dynamic visualization and environment simulation with low latency time and high level of details was developed by rFpro. The overall simulator system is characterized by exceptionally high lateral and vertical dynamics and a very realistic vehicle dynamics behavior and related driving experience.
The question now arises whether the controllability in case of vehicle damage can be reliably perform in such a driving simulator. The simulator thus offers good conditions for the study. Therefore a method for model design and simulation of the failure of selected chassis components using the MSC ADAMS Multi-Body Simulation (MBS) environment was developed. Furthermore, a transfer of the vehicle behavior into the simulation environment IPG CarMaker was worked out and the application of the methodology in real-time simulations was verified. Thereby replacement models of the different damages in IPG CarMaker were created, e.g. for the transient and dynamic wheel behavior. These were transferred to the dynamic driving simulator, where they were tested for controllability in the context of "driver-in-the-loop". In order to be able to compare and validate the controllability between simulator and real test. The controllability tests with several subjects were examined subjectively and objectively and compared with the behavior in the simulator. The paper will present the method and the given results of the study and further potentials for damage and failure possibilities.
Modern electric power steering (EPS) systems allow a flexible adaptation of the same steering hardware to different vehicle types by calibration of the corresponding control unit (ECU). As the steering behavior is one of the major factors influencing the end customers` buying decision and driving experience, the steering ECU calibration has to fit very well to the customer requirements. A growing number of functions in the steering ECU offer increasing possibilities to influence comfort, safety and steering feel and must be validated in different driving maneuvers (figure 1). However, several trade-offs of these characteristics have to be solved such as the driver’s steering effort vs. the steering feedback while cornering.
Model-based Development Methods – What can Chassis and Powertrain Development Learn from Each Other?
(2015)
The biggest challenge for today’s vehicle development is the increasing number of vehicle variants for different markets, which have to be developed in ever shorter cycles. In addition, customers and governments have high demands when it comes to comfort, driving pleasure, consumption, security and CO2 emissions. The powertrain and the chassis domain have developed their own methods to solve these difficulties. Although there are some important differences, the question arises how one domain can profit from the methods of the other domain. For example, the strict emission legislation in the powertrain sector lead to advanced model-based calibration and testing methods, which could be useful also for other domains.
How Can We Improve the Driving Experience with Human-Machine-Interface for Automated Driving?
(2020)
The head-up-display (HUD), which reflects driving information into the windshield has the goal to lower driving effort from the information uptake and thereby, increase our safety by reducing risks associated to e.g., fatigue and stress. This motivated us to test the HUD in combination with the lane keeping assistant system (LKAS) from n = 48 subjects who drove in real traffic conditions two premium vehicles in a highway in Germany. Subjects then rated the Human-Machine Interaction (HMI) from an assessment about the perceived feelings of safety, degree of relief, information displayed, displays design, and monitoring procedures. Results from CMP regressions show that the HUD has a significant effect on the driving effort and safety feelings, and on the overall subjects’ driving experience. Moreover, we find that this effect is stronger among elderly drivers, students, and females who feel significantly less driving effort. In particular, women felt significantly safer while the HUD was activated.
The variety of products on the market that are offered with advanced driver assistance systems is huge. Besides systems like the lane keeping assistant also camera based systems are more and more in the foreground. The Full Display Mirror (FDM), a camera-based hybrid mirror, is also being installed in vehicles. User experience in the sense of acceptance and peace of mind as well as benefit of the product are essential not only to know the systems are installed, but also to know how to use them. In a customer study with N = 60 persons, interviews and questionnaires were conducted during a test drive in real road traffic with various scenarios in order to test and evaluate the FDM. In comparison to the normal mirror, the FDM scored very well - especially in the field of view, the feedback was extremely positive. The increased safety with the use of the system, among other things due to the considerably larger field of view, is an absolute plus point of this camera-based mirror version. The fast familiarization with the system as well as the high user friendliness make the FDM a meaningful invention.
Im vorliegenden Beitrag wird eine Methode zur subjektiven und objektiven Charakterisierung von aktiven Fahrstreifenwechselfunktionen sowie eine Korrelationsanalyse zur Ermittlung optimaler Funktionseigenschaften vorgestellt. Zur Quantifizierung maßgeblicher subjektiver Eigenschaften wurden Bewertungskategorien und -kriterien aus den Bereichen Fahrerkooperation, Funktionsperformance, Entlastungsgrad und Sicherheitsgefühl erarbeitet, deren Beurteilung im Rahmen einer umfassenden Fahrstudie erfolgte. Die beurteilten Fahrzeuge wurden hinsichtlich ihrer unterschiedlichen Funktionsausprägungen anschließend in einem neuartigen fahrmanöverbasierten Prüfverfahren vermessen. Das Verfahren umfasst hierbei drei Typen von Fahrstreifenwechselszenarien in welchen unter anderem die Eigen- und Relativbewegung von Ego- und Target-Fahrzeug sowie die Funktionsrückmeldung am Lenkrad und im Kombi-Instrument des Egofahrzeugs messtechnisch erfasst wurden. Die Auswertung des hiermit aufgezeichneten objektiven Funktionsverhaltens geschieht durch eine automatisierte KPI-basierte Softwareumgebung. Ausgehend von der korrelativen Gegenüberstellung aller Subjektivkriterien mit den ermittelten KPI-Kennwerten können wichtige Trends und Zusammenhänge geprüft, erkannt und nutzbringend in die Festlegung optimaler Wertbereiche eingearbeitet werden. Die vorgestellte Methodik ermöglicht somit eine zielgerichtete Auslegung und Abstimmung der Eigenschaften einer aktiven Fahrstreifenwechselfunktion.
The proposed contribution addresses the growing need for systematic and efficient development methods for assisted and automated driving features. Active Lane Departure Warning (ALDW) systems with correcting steering interventions are the specific object of this research. Due to NCAP requirements ALDW systems are widespread in modern cars, but often lack drivers’ approval, as several related studies have shown. Causes are assumed to lie in unspecified attribute requirement metrics and missing target values. Based on typical ALDW usage scenarios on different road types, such as freeway, highway and country road, an advanced catalogue of subjective evaluation criteria was developed
and deployed in a comprehensive proband study with experts involving four distinct ALDW equipped passenger cars. Characteristic driving maneuvers with the intention to provoke controlled ALDW interventions complemented the subjective assessment with objective data. Statistically correlating derived objective key performance indicators with the respective subjective ratings established a link between drivers’ impressions and measurable system behavior. These dependencies allowed the conclusion of target values for a certain range of desired subjective ALDW characteristics fulfilling the initial requisites.
Recently the trend of driving simulators with driver in the loop (DiL) integration in the development process has become more and more visible. BMW opened a completely new simulation center, Daimler and Toyota have already had theirs in operation for some years. The reasons are well known and are presented in conferences and written down in papers: Reducing development time, reducing prototypes, reducing costs and increasing overall performance and efficiency. The same benefits are promised in papers about pure simulation, but what is the actual benefit from a dynamic driving simulator? The investment and operating costs are very high and yet it is crucial to bring the driver in to the loop. Obviously, the maturity level or knowledge about pure simulation and understanding for human drivers are still insufficient for a major breakthrough of simulation in many fields of application. A driving simulator connects the real and virtual world, by which humans experience functions and characteristics subjectively. Crucial decisions are made on reliable subjective feedback and humans especially become part of the left arm of the V-model development process. The current approach is using the same models and simulation environments combined with a driving simulator transferring simple signals from visible into feelable. The disadvantage of closing open control loops with a driver is that the objective data and maneuver quality largely depends on the driver. Assuming the driver is well qualified, the interface must reflect the real driving experience. Otherwise, every system/component under test will be assessed with an offset, filter or error. Besides the visualization, the steering feel is the most important channel for the driver to properly control any lateral movement. The common approach is using a force feedback system. A look on a steering system illustrates the complexity to ensure good steering feel.
Reducing time, costs and prototypes in vehicle development is a central objective. Previously, simulation and experimental testing are separate blocks in the development process chain that exchange information with each other. Theoretical preliminary considerations are realised by simulations, which are then tested by prototypes in real road trials. The use of driving simulators enables a synergetic solution to combine simulation and experimental testing. A process chain is presented in order to make it possible to experience the MBS model with damaged axle components on the driving simulator and thus also to evaluate them subjectively. Various deformation states of the components of the four-link rear axle are subjectively evaluated by several test drivers on the driving simulator in various driving manoeuvres. In the process, the components are ranked in terms of their damage criticality and the customer acceptance threshold is determined based on the component deformation. Furthermore, correlations between objective overall vehicle quantities and subjective driver evaluations are identified via linear regression models and artificial neural networks.
This paper provides an approach for controlling the level of risk when operating highly automated transportation systems like cars, trains and similar. Such systems replace human perception and decision-making by employing highly sophisticated solutions based on electronics, IT, and AI. Such systems have demonstrated the potential for building highly automated vehicles, but, as of today, encounter challenges in correctly understanding the extremely complex open contexts, into which such vehicles could be deployed. Its key focus is on bounding the risks stemming from uncertainty in the perception of the environment.
Automatisierte Fahrfunktionen haben sich fest in der Automobilindustrie etabliert. Insbesondere Einparkvorgänge lassen sich aufgrund der geringen Geschwindigkeiten und des vergleichsweise kleinen Betriebsraums sehr gut automatisieren. Um von den Insassen akzeptiert zu werden, muss eine Pkw-Parkfunktion jedoch souverän und mindestens so schnell agieren wie der Mensch. IPG Automotive, die Hochschule Kempten und MdynamiX zeigen, wie die eigenentwickelte Vehicle-in-the-Loop-Methode die durchgängige Bewertung automatisierter Fahrfunktionen unterstützen kann.