Bumpless Transfer for Convenient Lateral Car Control Handover**This work was supported in part by COMET K2 - Competence Centres for Excellent Technologies Programme.

Nestlinger, Georg; Stolz, Michael

doi:10.1016/j.ifacol.2016.07.721

Cited by 12 publications

(3 citation statements)

References 13 publications

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“…For tracking the lateral and longitudinal references from the trajectory planner, two proven controller implementations were reused. The lateral controller implements a state-feedback control law based on [23], modified according to [24] as motivated from a demonstrator vehicle application. It makes use of the reference path from the trajectory planner up to the second geometric continuity, i.e., lateral error, heading error, and path curvature.…”

Section: Actuation: Lateral and Longitudinal Controlmentioning

confidence: 99%

Development and Verification of Infrastructure-Assisted Automated Driving Functions

et al. 2021

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Automated vehicles we have on public roads today are capable of up to SAE Level-3 conditional autonomy according to the SAE J3016 Standard taxonomy, where the driver is the main responsible for the driving safety. All the decision-making processes of the system depend on computations performed on the ego vehicle and utilizing only on-board sensor information, mimicking the perception of a human driver. It can be conjectured that for higher levels of autonomy, on-board sensor information will not be sufficient alone. Infrastructure assistance will, therefore, be necessary to ensure the partial or full responsibility of the driving safety. With higher penetration rates of automated vehicles however, new problems will arise. It is expected that automated driving and particularly automated vehicle platoons will lead to more road damage in the form of rutting. Inspired by this, the EU project ESRIUM investigates infrastructure assisted routing recommendations utilizing C-ITS communications. In this respect, specially designed ADAS functions are being developed with capabilities to adapt their behavior according to specific routing recommendations. Automated vehicles equipped with such ADAS functions will be able to reduce road damage. The current paper presents the specific use cases, as well as the developed C-ITS assisted ADAS functions together with their verification results utilizing a simulation framework.

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Section: Actuation: Lateral and Longitudinal Controlmentioning

confidence: 99%

Development and Verification of Infrastructure-Assisted Automated Driving Functions

et al. 2021

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“…The introduction of a look-ahead enables preventive reaction to sudden direction changes of the reference path, which stabilizes the vehicle motion. As this becomes more crucial for higher vehicle speeds several tracking controllers (see, for example, [19][20][21][22]) use an adaptive, velocity dependent look-ahead distance, instead of a fixed distance. This is advantageous also if the tracking controller is applied in combination with simple motion planning systems, which do not provide a smooth path (cf.…”

Section: Look-aheadmentioning

confidence: 99%

“…Table 2 lists the classification according to the specified classifiers. Hoffmann (Stanley) [25], Kolb [26] front no path Sun [27,28], Kritayakirane [17], CG no path Chen [29], Hu [30] Bruschetta [31] Chatzikomis [14], Xu [19], Zhang [32] CG no heading Hiraoka [33] CP no path Tieber [34], Samson [35], rear no path Dominguez [36], Solea [37] Nestlinger [20], Ackermann [38], CG heading heading ARGO [21], Guldner [23], Yuan [22] Elkaim [39] CG heading path Solea [37] rear motion path Sentouh [40] CG motion motion Coulter (Pure-pursuit) [41] rear path heading…”

Section: Application To State-of-the-art Tracking Controllermentioning

confidence: 99%

A Generic Interface Enabling Combinations of State-of-the-Art Path Planning and Tracking Algorithms

2021

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In the development of Level 4 automated driving functions, very specific, but diverse, requirements with respect to the operational design domain have to be considered. In order to accelerate this development, it is advantageous to combine dedicated state-of-the-art software components, as building blocks in modular automated driving function architectures, instead of developing special solutions from scratch. However, e.g., in local motion planning and control, the combination of components is still limited in practice, due to necessary interface alignments, which might yield sub-optimal solutions and additional development overhead. The application of generic interfaces, which manage the data transfer between the software components, has the potential to avoid these drawbacks and hence, to further boost this development approach. This publication contributes such a generic interface concept between the local path planning and path tracking systems. The crucial point is a generalization of the lateral tracking error computation, based on an introduced error classification. It substantiates the integration of an internal reference path representation into the interface, to resolve the component interdependencies. The resulting, proposed interface enables arbitrary combinations of components from a comprehensive set of state-of-the-art path planning and tracking algorithms. Two interface implementations are finally applied in an exemplary automated driving function assembly task.

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Novel Hybrid-Testing Paradigms for Automated Vehicle and ADAS Function Development

Solmaz

Holzinger

Mischinger

et al. 2020

Towards Connected and Autonomous Vehicle Highways

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Bumpless Transfer for Convenient Lateral Car Control Handover**This work was supported in part by COMET K2 - Competence Centres for Excellent Technologies Programme.

Cited by 12 publications

References 13 publications

Development and Verification of Infrastructure-Assisted Automated Driving Functions

Development and Verification of Infrastructure-Assisted Automated Driving Functions

A Generic Interface Enabling Combinations of State-of-the-Art Path Planning and Tracking Algorithms

Novel Hybrid-Testing Paradigms for Automated Vehicle and ADAS Function Development

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