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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.