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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.
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.
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.
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.
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.