Die Entwickler von selbstfahrenden Fahrzeugen sind sich einig, dass es nach heutigem Stand der Technik über eine Milliarde Testkilometer bedarf, um ein autonom fahrendes Fahrzeug zu entwickeln. Daher überrascht es nicht, dass der "autonome" Shuttlebus in Bad Birnbach lediglich als teilautomatisiert einzustufen ist. Dennoch ist das Projekt wertvoll, um Erkenntnisse für die Entwicklung von autonomen Fahrzeugen zu erlangen und deren Einsatz im öffentlichen Personennahverkehr (ÖPNV) beurteilen zu können. Im vorliegenden Teilprojekt wurden innerhalb von vier Monaten über dreihundert Situationen dokumentiert, in denen die Fahrt unplanmäßig unterbrochen wurde. Diese wurden anschließend ausgewertet und teilweise in Versuchen nachgestellt. Es hat sich gezeigt, dass der Shuttlebus im aktuellen Betriebsmodell unfallfrei fahren kann. Allerdings ist für das unfall-und unterbrechungsfreie Fahren der durch die Zulassungsauflagen vorgeschriebene Operator an Bord zwingend erforderlich. Dieser muss an verschiedenen Stellen der Strecke-inklusive der Haltestellen-die Weiterfahrt bestätigen, den Bus um Hindernisse lenken und bei einem drohenden Unfall eingreifen. Ohne Operator käme es zur Kollision, da die Technik des Busses nicht alle kritischen Situationen erkennt. Der Bus kann im aktuellen Entwicklungsstand weder fahrerlos betrieben noch als zuverlässige Ergänzung im ÖPNV eingesetzt werden. Der Bus stellt dennoch einen wichtigen Schritt in Richtung autonomen Fahrens dar, welches weiterhin im Rahmen zukünftiger Forschungs-und Entwicklungsprojekte vorangetrieben werden muss.
The relevance of scientific investigations, whether simulative or empirical, is strongly related to the environment used and the scenarios associated with it. Within the field of cooperative intelligent transport systems, use-cases are defined to describe the benefits of applications. This has already been conducted in the available safety-relevant Day 1 applications longitudinal and intersection collision risk warning through the respective technical specifications. However, the relevance of traffic scenarios is always a function of accident severity and frequency of a retrospective consideration of accident databases. In this study, vehicle-to-vehicle scenarios with high frequency and/or severe personal injuries are therefore determined with the help of the CISS database and linked to the use-cases of the safety-relevant Day 1 applications. The relevance of the scenarios thus results on the one hand from the classical parameters of retrospective accident analysis and on the other hand from the coverage by the named vehicle-to-x applications. As a result, accident scenarios with oncoming vehicles are the most relevant scenarios for investigations with cooperative intelligent transport systems. In addition, high coverage of the most critical scenarios within the use-cases of longitudinal and intersection collision risk warning is already apparent.
The derivation of real accident scenarios from accident databases represents an important task within vehicle safety research. Simulations are increasingly used for this purpose. Depending on the research interest, a wide range of accident databases exists worldwide, which differ mainly in the number of recorded data per accident and availability. This work aims to identify critical vehicle-to-vehicle accidents based on freely available accident databases to derive concrete scenarios for a subsequent simulation. For this purpose, the method of the pre-crash matrix is applied using the example of the freely available Crash Investigation Sampling System database of the National Highway Traffic Safety Administration. An analysis of existing databases worldwide shows that this is the most detailed, freely available database. The derivation of scenarios succeeds here by a new method, whereby a center of gravity calculation is carried out based on the damages of the vehicles according to Collision Deformation Classification nomenclature. In addition, the determination of other necessary parameters, as well as the limits of the database, is shown in order to derive a scenario that can be simulated. As a result, the constellations of the five most frequent vehicle-to-vehicle accident scenarios according to the Crash Investigation Sampling System database are presented. In particular, other institutions should follow National Highway Traffic Safety Administration’s example and make data freely available for accident research.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.