Georg Nestlinger

ORCID: 0000-0002-8919-5312
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About
Contact & Profiles
Research Areas
  • Autonomous Vehicle Technology and Safety
  • Vehicle Dynamics and Control Systems
  • Robotic Path Planning Algorithms
  • Traffic control and management
  • Vehicular Ad Hoc Networks (VANETs)
  • Real-time simulation and control systems
  • Vehicle emissions and performance
  • GNSS positioning and interference
  • Network Traffic and Congestion Control
  • Robotic Mechanisms and Dynamics
  • Guidance and Control Systems
  • IPv6, Mobility, Handover, Networks, Security
  • Mobile Agent-Based Network Management
  • Bluetooth and Wireless Communication Technologies
  • Indoor and Outdoor Localization Technologies
  • Teleoperation and Haptic Systems

Virtual Vehicle (Austria)
2016-2024

Automated driving is one of the big trends in automotive industry nowadays. Over past decade car manufacturers have increased step by number and features their assistance systems. Besides technical aspects realizing a highly automated vehicle, validation approval poses challenge to industry. Reasons for this are grounded complexity interaction with environment, difficulties proving that an vehicle shows at least same performance as human driver, respect safety. There common agreement within...

10.1007/s00502-018-0629-0 article EN cc-by e+i Elektrotechnik und Informationstechnik 2018-07-16

Besides longitudinal control, advanced driver assistance functions additionally require lateral control. Up to now, many different control approaches have been proposed and documented in literature dealing with In contrast this, there are only very few publications describing the handling of comfortable handover from manual assisted driving controlling car dynamics. The presented work aims enhance at activation by significantly reducing acceleration jerk, resulting smooth handover. First a...

10.1016/j.ifacol.2016.07.721 article EN IFAC-PapersOnLine 2016-01-01

Automated vehicles we have on public roads today are capable of up to SAE Level-3 conditional autonomy according the J3016 Standard taxonomy, where driver is main responsible for driving safety. All decision-making processes system depend computations performed ego vehicle and utilizing only on-board sensor information, mimicking perception a human driver. It can be conjectured that higher levels autonomy, information will not sufficient alone. Infrastructure assistance will, therefore,...

10.3390/electronics10172161 article EN Electronics 2021-09-04

In this paper, the problem of vehicle guidance by means an external leader is described. The objective to navigate a four-wheeled through unstructured environments, characterized lack availability typical infrastructure like lane markings or HD maps. trajectory-following approach based on estimate leader’s path. For that, position measurements are stored over time with respect inertial frame. A new strategy proposed rate significance and ensure that certain threshold samples not exceeded....

10.3390/electronics11121866 article EN Electronics 2022-06-13

Automated vehicles are expected to cause a paradigm shift in mobility and the way we travel. Particularly, increasing penetration rates of with automated driving functions will introduce new challenges such as excessive rutting. Lack wheel wander keeping lane center perfectly is lead road surface depression induced by vehicle platoons. Inspired this, EU project ESRIUM investigates infrastructure assisted routing recommendations. In this respect, specially designed ADAS being developed...

10.1109/iccve52871.2022.9742783 article EN 2022-03-07

We present a comparative analysis of EGNSS-based path tracking with and without open service navigation message authentication (OSNMA), which was recently made available in mass market EGNSS (Galileo) receivers. The receivers provide dual-band GPS L1/L2 Galileo E1/E5a RTK positioning for cm-level GNSS localization. following task utilizes mainly the accurate RTK-assisted position heading information to track reference path. lateral error from is used as correction signal controller. compare...

10.1109/iavvc57316.2023.10328133 article EN 2023-10-16

In designing and implementing control systems, converting simulation based results to real life systems is often not straightforward may need adaptation of the approach achieve similar performance levels results. Such adaptations are usually required due fact that sensors actuators have a number imperfections such as delays, offsets inherent noise processes. Here, problem in relation development lane keeping algorithm presented. An in-house developed controller on high-fidelity environment...

10.1109/iccve45908.2019.8964916 article EN 2019-11-01
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