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Models and Methodology for Optimal Vehicle Maneuvers Applied to a Hairpin Turn
Department of Automatic Control, Lund University, Lund, Sweden.
Department of Automatic Control, Lund University, Lund, Sweden.
Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska högskolan.
Department of Automatic Control, Lund University, Lund, Sweden.
Visa övriga samt affilieringar
2013 (Engelska)Konferensbidrag, Publicerat paper (Övrigt vetenskapligt)
Abstract [en]

There is currently a strongly growing interest in obtaining optimal control solutions for vehicle maneuvers, both in order to understand optimal vehicle behavior and to devise improved safety systems, either by direct deployment of the solutions or by including mimicked driving techniques of professional drivers. However, it is nontrivial to find the right mix of models, formulations, and optimization tools to get useful results for the above purposes. Here, a platform is developed based on a stateof-the-art optimization tool together with adoption of existing vehicle models, where especially the tire models are in focus. A minimum-time formulation is chosen to the purpose of gaining insight in at-the-limit maneuvers, with the overall aim of possibly finding improved principles for future active safety systems. We present optimal maneuvers for different tire models with a common vehicle motion model, and the results are analyzed and discussed. Our main result is that a few-state singletrack model combined with different tire models is able to replicate the behavior of experienced drivers. Further, we show that the different tire models give quantitatively different behavior in the optimal control of the vehicle in the maneuver.

Ort, förlag, år, upplaga, sidor
2013.
Nationell ämneskategori
Teknik och teknologier
Identifikatorer
URN: urn:nbn:se:liu:diva-94204OAI: oai:DiVA.org:liu-94204DiVA, id: diva2:630274
Konferens
The 2013 American Control Conference, June 17-19, Washington, DC, USA
Tillgänglig från: 2013-06-18 Skapad: 2013-06-18 Senast uppdaterad: 2013-06-18Bibliografiskt granskad
Ingår i avhandling
1. Modeling and Optimization for Critical Vehicle Maneuvers
Öppna denna publikation i ny flik eller fönster >>Modeling and Optimization for Critical Vehicle Maneuvers
2013 (Engelska)Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

As development in sensor technology, situation awareness systems, and computational hardware for vehicle systems progress, an opportunity for more advanced and sophisticated vehicle safety-systems arises. With the increased level of available information---such as position on the road, road curvature and knowledge about surrounding obstacles---future systems could be seen utilizing more advanced controls, exploiting at-the-limit behavior of the vehicle. Having this in mind, optimization methods have emerged as a powerful tool for offline vehicle-performance evaluation, providing inspiration to new control strategies, and by direct implementation in on-board systems. This will, however, require a careful choice of modeling and objectives, since the solution to the optimization problem will rely on this.

With emphasis on vehicle modeling for optimization-based maneuvering applications, a vehicle-dynamics testbed has been developed. Using this vehicle in a series of experiments, most extensively in a double lane-change maneuver, verified the functionality and capability of the equipment. Further, a comparative study was performed, considering vehicle models based on the single-track model, extended with, e.g., tire-force saturation, tire-force lag and roll dynamics. The ability to predict vehicle behavior was evaluated against measurement data from the vehicle testbed.

A platform for solving vehicle-maneuvering optimization-problems has been developed, with state-of-the-art optimization tools, such as JModelica.org and Ipopt. This platform is utilized for studies concerning the influence different vehicle-model configurations have on the solution to critical maneuvering problems. In particular, different tire modeling approaches, as well as vehicle-chassis models of various complexity, are investigated. Also, the influence different road-surface conditions-e.g., asphalt, snow and ice-have on the solution to time-optimal maneuvers is studied.

The results show that even for less complex models-such as a single-track model with a Magic Formula based tire-model-accurate predictions can be obtained when compared to measurement data. The general observation regarding vehicle modeling for the time-critical maneuvers is similar; even the least complex models can be seen to capture certain characteristics analogous to those of higher complexity.

Analyzing the results from the optimization problems, it is seen that the overall dynamics, such as resultant forces and yaw moment, obtained for different model configurations, correlates very well. For different road surfaces, the solutions will of course differ due to the various levels of tire-forces being possible to realize. However, remarkably similar vehicle paths are obtained, regardless of surface. These are valuable observations, since they imply that models of less complexity could be utilized in future on-board optimization-algorithms, to generate, e.g., yaw moment and vehicle paths. In combination with additional information from enhanced situation-awareness systems, this enables more advanced safety-systems to be considered for future vehicles.

Ort, förlag, år, upplaga, sidor
Linköping: Linköping University Electronic Press, 2013. s. 108
Serie
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1608
Nationell ämneskategori
Reglerteknik
Identifikatorer
urn:nbn:se:liu:diva-94010 (URN)LIU-TEK-LIC-2013:42 (Lokalt ID)978-91-7519-561-2 (ISBN)LIU-TEK-LIC-2013:42 (Arkivnummer)LIU-TEK-LIC-2013:42 (OAI)
Presentation
2013-08-16, Visionen, B-huset, Campus Valla, Linköpings universitet, Linköping, 10:15 (Svenska)
Opponent
Handledare
Tillgänglig från: 2013-06-14 Skapad: 2013-06-14 Senast uppdaterad: 2013-06-25Bibliografiskt granskad

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