A real-time capable model predictive approach to lateral vehicle guidance

Götte, Christian; Keller, Martin; Rösmann, Christoph; Nattermann, T.; Hass, Carsten; Glander, Karl-Heinz; Seewald, Alois; Bertram, Torsten

doi:10.1109/itsc.2016.7795865

Cited by 15 publications

(4 citation statements)

References 16 publications

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“…Optimization approaches can also be used, the main advantage being the smoothness of the solutions and a straightforward encoding of the vehicle model [10]. A combined trajectory planning and control approach, formulated as a nonlinear model predictive control method is presented in [11]. Simulation results show its effectiveness even in challenging emergency maneuvers.…”

Section: Related Workmentioning

confidence: 99%

Path Planning for Autonomous Bus Driving in Highly Constrained Environments

Oliveira

Lima

Pereira

et al. 2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

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Driving in urban environments often presents difficult situations that require expert maneuvering of a vehicle. These situations become even more challenging when considering large vehicles, such as buses. We present a path planning framework that addresses the demanding driving task of buses in urban areas. The approach is formulated as an optimization problem using the road-aligned vehicle model. The road-aligned frame introduces a distortion on the vehicle body and obstacles, motivating the development of novel approximations that capture this distortion. These approximations allow for the formulation of safe and nonconservative collision avoidance constraints. Unlike other path planning approaches, our method exploits curbs and other sweepable regions, which a bus must often sweep over in order to manage certain maneuvers. Furthermore, it takes full advantage of the particular characteristics of buses, namely the overhangs, an elevated part of the vehicle chassis, that can sweep over curbs. Simulations are presented, showing the applicability and benefits of the proposed method.

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Section: Related Workmentioning

confidence: 99%

Path Planning for Autonomous Bus Driving in Highly Constrained Environments

Oliveira

Lima

Pereira

et al. 2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

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“…With regard to MPC, several contributions have recently been made for trajectory generation and control in the field of automated driving. An approach for lateral vehicle guidance, using MPC for trajectory planning and control is presented and evaluated in simulation by Götte et al [16]. A similar approach utilizing more advanced collision avoidance constraints is described by Gutjahr and Werling [17].…”

Section: Focus Of Examplementioning

confidence: 99%

Model predictive control based trajectory generation for autonomous vehicles — An architectural approach

Nolte

Rose

Stolte

et al. 2017

2017 IEEE Intelligent Vehicles Symposium (IV)

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Abstract-Research in the field of automated driving has created promising results in the last years. Some research groups have shown perception systems which are able to capture even complicated urban scenarios in great detail. Yet, what is often missing are general-purpose path-or trajectory planners which are not designed for a specific purpose. In this paper we look at path-and trajectory planning from an architectural point of view and show how model predictive frameworks can contribute to generalized pathand trajectory generation approaches for generating safe trajectories even in cases of system failures.c 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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“…Die Approximation hängt stärker mit einer Stellgrößenänderung zusammen, welche in erster Linie durch diesen Gütemaßanteil minimiert werden sollen. Das im Gütemaß enthaltene Umfeldmodell (siehe [Thi15] und [Göt+16a]) besteht aus zwei Teilen:…”

Section: Aufbau Des Gütemaßesunclassified

Trajektorienplanung zur Kollisionsvermeidung im Straßenverkehr

Keller¹

2017

Self Cite

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Um die Unfallzahlen im öffentlichen Straßenverkehr zu senken, werden zusätzlich zu den klassischen Fahrstabilisierungssystemen neuartige Fahrerassistenzsysteme benötigt, die neben fahrdynamischen Größen auch Informationen über das Fahrzeugumfeld in die Funktionalität miteinbeziehen. Automatische Bremseingriffe waren der erste Schritt in diese Richtung, jedoch wird die Fahrzeugquerführung bisher nicht eingesetzt, um das gesamte Kollisionsvermeidungspotential von Fahrzeugen zu nutzen. In der vorliegenden Arbeit werden vier verschiedene Verfahren zur Fahrzeugführung im Sinne der Kollisionsvermeidung in Notsituationen entwickelt. Die Komplexität der Verfahren reicht von einfachen Bahnplanern, über massenpunktbasierte Optimierungen bis hin zu modellprädiktiven Verfahren, welche fahrdynamische Effekte explizit berücksichtigen. Die Arbeit zeigt die unterschiedlichen Eigenschaften, Möglichkeiten, Herausforderungen und Grenzen der Verfahren auf, bewertet und vergleicht diese mite...

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A real-time capable model predictive approach to lateral vehicle guidance

Cited by 15 publications

References 16 publications

Path Planning for Autonomous Bus Driving in Highly Constrained Environments

Path Planning for Autonomous Bus Driving in Highly Constrained Environments

Model predictive control based trajectory generation for autonomous vehicles — An architectural approach

Trajektorienplanung zur Kollisionsvermeidung im Straßenverkehr

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