Zofka M.R.,Research Center for Information Technology |
Kohlhaas R.,Research Center for Information Technology |
Bar T.,Research Center for Information Technology |
Schwab S.,IPG Automotive GmbH |
And 2 more authors.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2014
One of the great challenges for the release of automated vehicles is the verification and evaluation of their cognitive skills. Therefore, Vehicle-in-the-loop testing provides an adequate tool, combining real test drives with simulations. In this paper we present our innovative Vehiclein- the-loop framework: First, a marker-based head tracking is presented, which is able to track the driver’s head in presence of vehicle’s movement and illumination influences. Second, we present our realization based on the Open-Source framework ROS with an exemplary coupling to the professional simulation tool CarMaker. Finally, we evaluate our approach in different driving scenarios. © Springer International Publishing Switzerland 2014.
Shen D.,TU Berlin |
Bensch V.,IPG Automotive GmbH |
Muller S.,TU Berlin
IFAC Proceedings Volumes (IFAC-PapersOnline) | Year: 2015
This paper introduces a model predictive control (MPC) strategy for the purpose of fuel-optimal operation of a range-extender hybrid vehicle. The modern navigation system nowadays can provide abundant road information. Using this information, the proposed controller solves a global optimization problem offline in order to determine a preset trajectory of the state of charge (SoC). The online MPC uses the resulting SoC trajectory as set-points for the terminal state in every moving horizon. Repeating this process, the optimal energy management along the trip to be traveled can thus be calculated. This proposed control strategy is implemented in the commercial vehicle simulation environment IPG CarMaker. From the first simulation results, the proposed strategy shows a promising fuel saving potential with real-time capability. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved..
Geyer S.,TU Darmstadt |
Baltzer M.,RWTH Aachen |
Franz B.,TU Darmstadt |
Hakuli S.,IPG Automotive GmbH |
And 8 more authors.
IET Intelligent Transport Systems | Year: 2014
Activities in the field of automated driving have produced a variety of development tools and methodologies over the past decades. The requirements the systems have to fulfil and thus also the development guidelines are often documented in different kinds of catalogues (use-case catalogues, situation catalogues, scenario catalogues etc.). These catalogues cannot be directly applied for the development of partially and highly automated vehicle guidance concepts like conduct-by-wire (CbW) or H-mode. One reason is that up to now, no consistent terminology known to the authors yet exists for vehicle automation within the community. Moreover, as the aim of the two project groups CbW and H-mode is to make a comprehensive feasibility assessment of cooperative vehicle guidance, all interacting components of the overall system as well as all potential driving conditions a cooperative vehicle guidance system might have to cope with have to be analysed. This article focuses on two aspects. The first is a metaphor-based terminology discussion leading to a proposal for a fundamental ontology. The second aspect is an outlook on the different catalogues that use the new terminology and that have been developed. The methodology introduced here is a fundamental contribution towards simplifying communication and the exchange of findings. © The Institution of Engineering and Technology 2014.
Witter H.-J.,IPG Automotive GmbH |
Lange S.,AVL Deutschland GmbH |
Talwar K.,OEM Technology Instruments
SAE Technical Papers | Year: 2013
The evaluation of vehicle characteristics at an early phase of functional development is a key task in the definition of a viable system architecture. Today this is complicated by the fact that full vehicle characteristics, in particular those of modern hybrid vehicles, are dependent on a broad range of electrical, mechanical, thermal and control-related partial aspects. In addition to the current driving status and information on the environment, modern energy management systems (e.g. control systems, range, charging and thermal management) also require predictive information on the driving route to be expected. This includes, for example, uphill road grades, curve radii, speed limits, number of lanes, urban and residential areas, intersections and traffic lights. All together, the intelligent fusion of this information provides for increased safety and energy efficiency. Copyright © 2013 SAE International and Copyright © 2013 SIAT, India.
Kobayashi M.,IPG Automotive K.K. |
Donn C.,IPG Automotive GmbH
2015 54th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2015 | Year: 2015
In this paper, an open integration and test platform is used for the multi-objective optimization of the powertrain concept of a hybrid vehicle. This was done for different driving scenarios and driver types and taking into account longitudinal and lateral vehicle dynamics. A comparative study of fuel efficiency and performance for a hybrid-electric powertrain with different battery sizes and operating strategies was made, using the Functional Mockup Interface (FMI) approach to integrate a detailed vehicle powertrain model into a comprehensive full-vehicle model driven by a virtual driver on a virtual road. © 2015 The Society of Instrument and Control Engineers-SICE.