TU BRAUNSCHWEIG

DI-2 Working Group Vehicle Dynamics and Active Systems

The working group "Vehicle Dynamics and Active Systems" primarily focuses on the research field "Intelligent Vehicle and Connected Driving", aiming to strengthen and expand the interdisciplinary cooperation with partners in the Automotive Research Centre Niedersachsen (NFF) - and beyond. This includes interfaces between mechanical engineering, electrical engineering, road construction, information technology and life sciences with applications such as vehicle functions, actuators and sensors, recording of road attributes and information, C2X-based functions as well as human-technology interaction in terms of comfort / safety perception, usage behaviour and functional safety with regard to the transition from assisted to automated driving. The research infrastructure is tightly connected due to the activities, with a sustainable further development of the interdisciplinary topic "Efficient Development and Testing" (vehicle level, functional level, source code level) as one of the basic research objectives. Expanding the NFF's expertise and developing new thematic fields are the strategic structural objectives the working group focuses on.

The future of the automobile will be characterised by the topic of automated and connected driving. After today's driver assistance systems, such as active cruise control, lane keeping assistant or automatic emergency brake, have become established on the market and their effectiveness has been proven, it is only a question of time before highly automated vehicles (HAF) can be found operating in public road traffic - motorways at first, then urban roads. In order to achieve the latter, the current research in vehicle automation does not only focus on the structured motorway environment, but also on urban scenarios. From a safety perspective, the lower speeds in cities seem to offer advantages for the function development; however, the real-life situations are much more complex due to the multitude of interactions (some of them with vulnerable road users like pedestrians and cyclists), more dynamic traffic routing and traffic flow regulations, e.g. traffic lights.
MThe demanding driving environment results in several fascinating challenges. One important field is the "Car2X" communication, which ensures the exchange of information between vehicle and actors, e.g. infrastructure or other vehicles. City centres in particularly offer new possibilities of cooperation and interaction between vehicles, for instance at intersections, as well as the incorporation of transmitted light signal phases or remaining times for behavioural planning.


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Figure 1: "TEASY III" car - Testing and Engineering of Automated Driving Systems © IAE / Pictures: Sonka


The recognition of situations and interpretation of scenarios are further important research fields. Particularly the requirements on environmental sensors increase since, in contrast to conventional longitudinal control and track guidance, an area in front of the ego vehicle is not sufficient for monitoring, but - with increasing complexity during lane changes and automated driving in the city - high-precision surround view and object classification are required. For the redundant and reliable detection of passengers and cyclists, a sensor fusion is necessary, which relies on more than one detection technology. Combinations of camera and radar or camera and laser scanners are promising here.
For the interpretation of the acquired environmental data and action planning, algorithms from the field of artificial intelligence will be used in the future, which have achieved high performance in the past years. Similar to humans, they learn from available knowledge and can improve their efficiency and accuracy when used. This includes the challenging task of predicting the movements of e.g. cyclists and pedestrians, which are subject to individual dynamics. Their behaviour is therefore hard to predict.
With the advancing development of degrees of automation, the modern man more and more takes the role of a "co-driver". It is therefore essential that the systems run without errors and that a comprehensible and credible system behaviour is presented to the customers. This includes the dynamics during acceleration, braking, lane changes or turning, which are perceived differently as a driver. The perceived criticality heavily depends on the situation awareness and is influenced by whether the road users take the task of monitoring permanently in semi-automated mode or whether they can dedicate themselves to auxiliary tasks in fully automated mode. A trust-increasing design of the human-machine interaction through user-adaptive support and provision of information (e.g. based on the current driving mode, reaching the system limits or the request to take over) is also essential. According to driver type and degree of automation, different forms of interaction and information can be preferred.


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Figure 2: TEASY III during cooperative automated driving in complex city traffic © IAE / Pictures: Krauns, Sonka


With the omission of the human as fallback solution for the system to be fail safe / fail operational, the named functions require many redundancies in hardware and software, which in turn are connected to questions of functional and usage safety. Shifting the enormous test effort to the early virtual development phase and the definition of representative, internationally standardised test procedures will play an important role for the official approval and homologation for road service of highly automated vehicles.
The working group "Vehicle Dynamics & Active Systems" deals with many of these complex questions in line with their research activities. At the same time, the group takes a responsible role for the research field "Intelligent Vehicle and Connected Driving" at the Automotive Research Centre Niedersachsen (NFF) in close cooperation with other institutes and research institutions as well as international partners in the automotive and supplier industry.
The latest activities of the working group have for instance focused on the development of efficient tool chains for the development, testing and evaluation of automated driving functions. In this regard, several of their own automated research vehicles are used, e.g. "TEASY III" (Testing and Engineering of Automated Driving Systems), see Figures 1 and 2 in city use. TEASY III is equipped with laser scanner sensors and high-precision global positioning systems to record driving situations in real road use and to integrate them into the virtual validation process. The "Dynamic Vehicle Road Simulator" (DVRS, Figure 3) offers the possibility to optimise functions with higher degrees of automation based on real issues without any risks. In this context, research and development particularly focus on the design of control and display concepts, which ensure a clear handover / takeover of responsibility between "human" and automated driving mode in each situation.


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Figure 3: Dynamic Vehicle Road Simulator "DVRS" © NFF / Picture: Bierwagen


Reference projects:

  • KoHAF: Kooperatives Hochautomatisiertes Fahren auf Autobahnen (funded by the BMWi)
  • iFUSE: Intelligente Fusion von Radar- und Videosensoren für anspruchsvolle, hochautomatisierte Fahrsituationen (funded by the BMWi)
  • Digitaler Knoten 4.0: Gestaltung und Regelung städtischer Knotenpunkte für sicheres und effizientes automatisiertes Fahren im gemischten Verkehr. (funded by the BMVI)
  • RoCCl: Road Condition Cloud (DFG research project)
  • Priv. Doz. Dr.-Ing. Roman Henze (head),
  • Adrian Sonka, M.Sc. (research field coordinator),
  • Tim Ahrenhold, M.Sc.,
  • Maximilian Flormann, M.Sc.,
  • Alexander Hafner, M.Sc.,
  • Waldemar Jarisa, M.Sc.,
  • Marcel Kascha, M.Sc.,
  • Florian Krauns, M.Sc.,
  • Dipl.-Ing. Thorsten Meister,
  • Björn Reuber, M.Sc.,
  • Jan Sterthoff, M.Sc.,
  • Felix Tigges, M.Sc.,
  • Christian Wagner, M.Sc.
  • Holger Znamiec, M.Sc.
    1. LI, M.; FENG, Z.; KUNERT, M.; HENZE, R.; KÜÇÜKAY, F.: High Resolution Radar-based Occupancy Grid Mapping and Free Space Detection. In Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-293-6
    2. FLORMANN, M.; SONKA, A.; HENZE, R.: Automated and Connected Driving in Urban Scenarios. ADAPTIVE 2018. The Tenth International Conference on Adaptive and Self-Adaptive Systems and Applications. IARIA, 2018. ISBN: 978-1-61208-610-1
    3. REUBER, B.; ZNAMIEC, H.; HENZE, R.; KÜÇÜKAY, F.: Highly Accurate Map-based Path and Behavior Planning for Automated Urban Driving. ADAPTIVE 2018. The Tenth International Conference on Adaptive and Self-Adaptive Systems and Applications. IARIA, 2018. ISBN: 978-1-61208-610-1
    4. LI, M.; KUNERT, M.; HENZE, R.: Herausforderungen, Anwendungsfälle und Zukunftstechnologien für einen besseren Radfahrerschutz mit hochauflösenden Automobilradaren. 17. VDI-Tagung Fahrzeugsicherheit, 28.-29. November 2017
    5. HENZE, R.; JARISA, W.: Potentials of Fiction Adaptive AEB Systems. Future Active Safety Technology forward zero-traffic-accidents, FASTzero`17, September 19-22, Nara, Japan, 2017
    6. SONKA, A.; HAFNER, A.; WAGNER, C.; BUCHMUELLER, S.; BATH, C.: Analysis of Driver-System-Interaction in Highly Automated Driving. Future Active Safety Technology forward zero-traffic-accidents, FASTzero`17, September 19-22, Nara, Japan, 2017
    7. ZNAMIEC, H.; REUBER, B.; HENZE, R. KÜÇÜKAY, F.: A Method for the Efficent Testing of New Automated Driving Functions. Future Active Safety Technology forward zero-traffic-accidents, FASTzero`17, September 19-22, Nara, Japan, 2017
    8. HAFNER, A.; KRAUNS, F.; HENZE, R.; KÜÇÜKAY, F.: Holistically Simulation by Integration of Real Measurement Data. Future Active Safety Technology forward zero-traffic-accidents, FASTzero`17, September 19-22, Nara, Japan, 2017
    9. RAKSINCHAROENSAK, P.; LERTSILPACHALERN, V.; LIDBERG, M.; HENZE, R.: Robust Vehicle Handling Dynamics of Light-Weight Vehicles Against Variation in Loading Conditions. IEEE International Conference on Vehicular Electronics and Safety (ICVES), 27-28 June, Vienna Austria, 2017
    10. SONKA, A.; KRAUNS, F.; HENZE, R.; KÜÇÜKAY, F.; KATZ, R.; LAGES, U.: Dual Approach for Maneuver Classification in Vehicle Environment Data. IEEE Intelligent Vehicles Symposium – June 11-14, 2017.
    11. BÜYÜKYILDIZ, G.; PION, O.; HENZE, R.; KÜÇÜKAY, F.; HILDEBRANDT, C.; SEDLMAYER, M.: Identification of the Driving Style for the Adaptation of Assistance System. Journal of Intelligent Transportation System, Vol. 13 No. 3, 2017
    12. KRAUNS, F.; SONKA, A.; HENZE, R.; KÜÇÜKAY, F.: Objektivierung kombinierter Längs- und Querführung. AAET, 18. Symposium AAET 2017 - Automatisierungssysteme, Assistenzsysteme und eingebettete Systeme für Transportmittel, 08.-09.02.2017, Braunschweig.
    13. NIPPOLD, C.; HENZE, R.; KÜÇÜKAY, F.: Prüfstandsbasierte Vorbedatung von Lenksystemen. In: Automobiltechnische Zeitschrift Jahrgang 119 (1/2017), S. 72ff.
    DI-2 Henze


    Priv. Doz. Dr.-Ing. Roman Henze

    Head of Vehicle Dynamics & Active Systems,Institute of Automotive Engineering
    Head of research field "Intelligent Vehicle and Connected Driving" at the Automotive Research Centre Niedersachsen

    Technische Universität Braunschweig

    phone: +49 531 391-2608 und -66602
    e-mail: r.henze@tu-braunschweig.de

      last changed 12.11.2018
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