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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.