Für viele Autofahrer ist das Einparken eine tägliche Herausforderung, für die einen mehr, für die anderen weniger. Ebenso gibt es in modernen Fahrzeugen Einparkassistenzsysteme, die diese Aufgabe sehr gut erledigen, und solche, die sie viel schlechter erledigen. Um sowohl manuelle Einparkmanöver als auch Parkmanöverassistenten objektiv bewerten zu können, hat die Hochschule Kempten in Zusammenarbeit mit MdynamiX eine Kundenstudie mit 21 Teilnehmern und verschiedenen Einparkassistenten durchgeführt.
For many drivers, parking is a daily challenge, for some more for others less. Likewise, there are parking assistance systems in modern vehicles that do this task very well and those that do it much worse. In order to be able to objectively evaluate both manual parking maneuvers and parking assistants, Kempten University of Applied Sciences, in cooperation with MdynamiX, conducted a customer study with 21 participants and various parking assistants.
For many drivers, parking is a necessary challenge. There are even drivers who avoid certain parking spaces because their parking skills seem to be insufficient. Without doubt, there are drivers who are very good at parking and also drivers who are less good at it. Similarly, in modern vehicles you will find parking ma-neuver assistance systems (PMAs) which do this task very well and those which do it much worse. In attribute-based development, the pursuit of goals based on objective key performance indicators (KPI's) are essential. To be able to evaluate manual parking maneuvers as well as PMAs, the University of Ap-plied Sciences Kempten (UAS Kempten) in cooperation with MdynamiX has conducted a customer study with 21 participants and different PMAs. The data-base was used to develop a method for the objective evaluation of parking per-formance in general and to correlate this with the subjective evaluation. The goal of this new evaluation method was to analyze the parking maneuver in its different phases, from the selection of the parking space to the final standstill of the vehicle and parking out. Different steering, braking and acceleration strate-gies were examined in their characteristics and the customer experience, too. For example, the question arises as to which speeds are favored and whether it is better to steer when stationary or while driving, which could have a major ef-fect on e.g. comfort experience, tire wear etc. In addition, the question arises which approaching and related braking and acceleration strategy is perceived as more pleasant. The objective evaluation method is based on KPIs, which show the parking maneuver performance in its basic characteristics in detail. In the large-scale study at UAS Kempten, this new evaluation method was applied to manual and fully automated parking maneuvers. For the analysis of the KPIs, extensive physical measurement data was collected and evaluated. Based on this evaluation, automatically and manually driven parking scenarios can be funda-mentally analyzed. The manually driven parking maneuvers define the reference and will be compared to the performance of the PMAs with the developed KPIs.
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.