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  • 1.
    Anistratov, Pavel
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Burdakov, Oleg
    Linköpings universitet, Matematiska institutionen, Optimeringslära. Linköpings universitet, Tekniska fakulteten.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Autonomous-Vehicle Maneuver Planning Using Segmentation and the Alternating Augmented Lagrangian Method2020Ingår i: 21th IFAC World Congress Proceedings / [ed] Rolf Findeisen, Sandra Hirche, Klaus Janschek, Martin Mönnigmann, Elsevier, 2020, Vol. 53, s. 15558-15565Konferensbidrag (Refereegranskat)
    Abstract [en]

    Segmenting a motion-planning problem into smaller subproblems could be beneficial in terms of computational complexity. This observation is used as a basis for a new sub-maneuver decomposition approach investigated in this paper in the context of optimal evasive maneuvers for autonomous ground vehicles. The recently published alternating augmented Lagrangianmethod is adopted and leveraged on, which turns out to fit the problem formulation with several attractive properties of the solution procedure. The decomposition is based on moving the coupling constraints between the sub-maneuvers into a separate coordination problem, which is possible to solve analytically. The remaining constraints and the objective function are decomposed into subproblems, one for each segment, which means that parallel computation is possible and benecial. The method is implemented and evaluated in a safety-critical double lane-change scenario. By using the solution of a low-complexity initialization problem and applying warm-start techniques in the optimization, a solution is possible to obtain after just a few alternating iterations using the developed approach. The resulting computational time is lower than solving one optimization problem for the full maneuver.

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  • 2.
    Anistratov, Pavel
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Lund Univ, Sweden.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Analysis and design of recovery behaviour of autonomous-vehicle avoidance manoeuvres2022Ingår i: Vehicle System Dynamics, ISSN 0042-3114, E-ISSN 1744-5159, Vol. 60, nr 7, s. 2231-2254Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Autonomous vehicles allow utilisation of new optimal driving approaches that increase vehicle safety by combining optimal all-wheel braking and steering even at the limit of tyre-road friction. One important case is an avoidance manoeuvre that, in previous research, for example, has been approached by different optimisation formulations. An avoidance manoeuvre is typically composed of an evasive phase avoiding an obstacle followed by a recovery phase where the vehicle returns to normal driving. Here, an analysis of the different aspects of the recovery phase is presented, and a subsequent formulation is developed in several steps based on theory and simulation of a double lane-change scenario. Each step leads to an extension of the optimisation criterion. Two key results are a theoretical redundancy analysis of wheel-torque distribution and the subsequent handling of it. The overall contribution is a general treatment of the recovery phase in an optimisation framework, and the method is successfully demonstrated for three different formulations: lane-deviation penalty, minimum time, and squared lateral-error norm.

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  • 3.
    Anistratov, Pavel
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Chalmers Univ Technol, Sweden.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Lund Univ, Sweden.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Dynamics-Based Optimal Motion Planning of Multiple Lane Changes using Segmentation2022Ingår i: IFAC PAPERSONLINE, ELSEVIER , 2022, Vol. 55, nr 24, s. 233-240Konferensbidrag (Refereegranskat)
    Abstract [en]

    Avoidance maneuvers at normal driving speed or higher are demanding driving situations that force the vehicle to the limit of tire-road friction in critical situations. To study and develop control for these situations, dynamic optimization has been in growing use in research. One idea to handle such optimization computations effectively is to divide the total maneuver into a sequence of sub-maneuvers and to associate a segmented optimization problem to each sub-maneuver. Here, the alternating augmented Lagrangian method is adopted, which like many other optimization methods benefits strongly from a good initialization, and to that purpose a method with motion candidates is proposed to get an initially feasible motion. The two main contributions are, firstly, the method for computing an initially feasible motion that is found to use obstacle positions and progress of vehicle variables to its advantage, and secondly, the integration with a subsequent step with segmented optimization showing clear improvements in paths and trajectories. Overall, the combined method is able to handle driving scenarios at demanding speeds.

  • 4.
    Anistratov, Pavel
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Lund Univ, Sweden.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Efficient Motion Planning for Autonomous Vehicle Maneuvers Using Duality-Based Decomposition2019Ingår i: IFAC PAPERSONLINE, ELSEVIER , 2019, Vol. 52, nr 5, s. 78-84Konferensbidrag (Refereegranskat)
    Abstract [en]

    A method to decompose a motion-planning problem into several segments is presented. It is based on a modification of the original problem, such that certain variables at the splitting points are considered to be precomputed and thus fixed and the remaining variables are obtained by performing Lagrange relaxation. The resulting dual problem is split into several subproblems, allowing parallel computation. The method is formalized as a computational algorithm and evaluated in a safety critical double lane-change situation. The resulting maneuver has close-to-optimal behavior and, for certain initialization strategies, it is obtained in shorter computational time compared to computing the full maneuver in one step. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

  • 5.
    Anistratov, Pavel
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Lane-Deviation Penalty for Autonomous Avoidance Maneuvers2018Ingår i: Proceedings of the 14th International Symposium on Advanced Vehicle Control, Beijing, July 16-20, 2018, 2018Konferensbidrag (Refereegranskat)
    Abstract [en]

    A formulation of an offline motion-planning method for avoidance maneuvers based on a lane-deviation penalty function is proposed,which aims to decrease the risk of a collision by minimizing the time when a vehicle is outside of its own driving lane in the case ofavoidance maneuvers. The penalty function is based on a logistic function. The method is illustrated by computing optimal maneuversfor a double lane-change scenario. The results are compared with minimum-time maneuvers and squared-error norm maneuvers. Thecomparison shows that the use of the considered penalty function requires fewer constraints and that the vehicle stays less time in theopposing lane. The similarity between the obtained trajectories for different problem configurations was noticed. This property couldbe used in the future for predicting an intermediate trajectory online from a sparse data set of maneuvers.

  • 6.
    Anistratov, Pavel
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Lund Univ, Sweden.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Lane-deviation penalty formulation and analysis for autonomous vehicle avoidance maneuvers2021Ingår i: Proceedings of the Institution of mechanical engineers. Part D, journal of automobile engineering, ISSN 0954-4070, E-ISSN 2041-2991, Vol. 235, nr 12, s. 3036-3050, artikel-id 09544070211007979Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Autonomous vehicles hold promise for increased vehicle and traffic safety, and there are several developments in the field where one example is an avoidance maneuver. There it is dangerous for the vehicle to be in the opposing lane, but it is safe to drive in the original lane again after the obstacle. To capture this basic observation, a lane-deviation penalty (LDP) objective function is devised. Based on this objective function, a formulation is developed utilizing optimal all-wheel braking and steering at the limit of road-tire friction. This method is evaluated for a double lane-change scenario by computing the resulting behavior for several interesting cases, where parameters of the emergency situation such as the initial speed of the vehicle and the size and placement of the obstacle are varied, and it performs well. A comparison with maneuvers obtained by minimum-time and other lateral-penalty objective functions shows that the use of the considered penalty function decreases the time that the vehicle spends in the opposing lane.

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  • 7.
    Anistratov, Pavel
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Segmentation and Merging of Autonomous At-the-Limit Maneuvers for Ground Vehicles2018Ingår i: Proceedings of the 14th International Symposium on Advanced Vehicle Control, Beijing, July 16-20, 2018, 2018, s. 1-6Konferensbidrag (Refereegranskat)
    Abstract [en]

    To decrease the complexity of motion-planning optimizations, a segmentation and merging strategy for maneuvers is proposed. Maneuvers that are at-the-limit of friction are of special interest since they appear in many critical situations. The segmentation pointsare used to set constraints for several smaller optimizations for parts of the full maneuver, which later are merged and compared withoptimizations of the full maneuver. The technique is illustrated for a double lane-change maneuver.

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    Segmentation and Merging of Autonomous At-the-Limit Maneuvers for Ground Vehicles
  • 8.
    Fors, Victor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Anistratov, Pavel
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Predictive Force-Centric Emergency Collision Avoidance2021Ingår i: Journal of Dynamic Systems Measurement, and Control, ISSN 0022-0434, E-ISSN 1528-9028, Vol. 143, nr 8, artikel-id 081005Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A controller for critical vehicle maneuvering is proposed that avoids obstacles and keeps the vehicle on the road while achieving heavy braking. It operates at the limit of friction and is structured in two main steps: a motion-planning step based on receding-horizon planning to obtain acceleration-vector references, and a low-level controller for following these acceleration references and transforming them into actuator commands. The controller is evaluated in a number of challenging scenarios and results in a well behaved vehicle with respect to, e.g., the steering angle, the body slip, and the path. It is also demonstrated that the controller successfully balances braking and avoidance such that it really takes advantage of the braking possibilities. Specifically, for a moving obstacle, it makes use of a widening gap to perform more braking, which is a clear advantage of the online replanning capability if the obstacle should be a moving human or animal. Finally, real-time capabilities are demonstrated. In conclusion, the controller performs well, both from a functional perspective and from a real-time perspective.

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  • 9.
    Fors, Victor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Gao, Yangyan
    Univ Lincoln, Lincoln LN6 7TS, England.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Gordon, Timothy
    Univ Lincoln, Lincoln LN6 7TS, England.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Real-Time Minimum-Time Lane Change Using the Modified Hamiltonian Algorithm2020Ingår i: Advances in Dynamics of Vehicles on Roads and Tracks / [ed] Matthijs Klomp, Fredrik Bruzelius, Jens Nielsen, Angela Hillemyr, SPRINGER INTERNATIONAL PUBLISHING AG , 2020, s. 1457-1465Konferensbidrag (Refereegranskat)
    Abstract [en]

    A minimum-time lane change maneuver is executed under friction-limited conditions using (1) the Modified Hamiltonian Algorithm (MHA) suitable for real-time control and (2) numerical optimization for comparison. A key variable is the switching time of the acceleration reference in MHA. Considering that MHA is based on an approximate vehicle model to target real-time control, it cannot exactly match the ideal reference as obtained from offline optimization; this paper shows that incorporation of a limited-jerk condition successfully predicts the switching time and that the desired lane position is reached in near minimum time.

  • 10.
    Fors, Victor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Lund Univ, Sweden.
    Frisk, Erik
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Resilient Branching MPC for Multi-Vehicle Traffic Scenarios Using Adversarial Disturbance Sequences2022Ingår i: IEEE Transactions on Intelligent Vehicles, ISSN 2379-8858, E-ISSN 2379-8904, Vol. 7, nr 4, s. 838-848Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    An approach to resilient planning and control of autonomous vehicles in multi-vehicle traffic scenarios is proposed. The proposed method is based on model predictive control (MPC), where alternative predictions of the surrounding traffic are determined automatically such that they are intentionally adversarial to the ego vehicle. This provides robustness against the inherent uncertainty in traffic predictions. To reduce conservatism, an assumption that other agents are of no ill intent is formalized. Simulation results from highway driving scenarios show that the proposed method in real-time negotiates traffic situations out of scope for a nominal MPC approach and performs favorably to state-of-the-art reinforcement-learning approaches without requiring prior training. The results also show that the proposed method performs effectively, with the ability to prune disturbance sequences with a lower risk for the ego vehicle.

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  • 11.
    Fors, Victor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Attainable force volumes of optimal autonomous at-the-limit vehicle manoeuvres2020Ingår i: Vehicle System Dynamics, ISSN 0042-3114, E-ISSN 1744-5159, Vol. 58, nr 7, s. 1101-1122Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    With new developments in sensor technology, a new generation of vehicle dynamics controllers is developing, where the braking and steering strategies use more information, e.g. knowledge of road borders. The basis for vehicle-safety systems is how the forces from tyre–road interaction is vectored to achieve optimal total force and moment on the vehicle. To study this, the concept of attainable forces previously proposed in literature is adopted, and here a new visualisation technique is devised. It combines the novel concept of attainable force volumes with an interpretation of how the optimal solution develops within this volume. A specific finding is that for lane-keeping it is important to maximise the force in a certain direction, rather than to control the direction of the force vector, even though these two strategies are equivalent for the friction-limited particle model previously used in some literature for lane-keeping control design. More specifically, it is shown that the optimal behaviour develops on the boundary surface of the attainable force volume. Applied to lane-keeping control, this observation indicates a set of control principles similar to those analytically obtained for friction-limited particle models in earlier research, but result in vehicle behaviour close to the globally optimal solution also for more complex models and scenarios.

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    Attainable force volumes of optimal autonomous at-the-limit vehicle manoeuvres
  • 12.
    Fors, Victor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Department of Automatic Control, Lund University, Lund, Sweden.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Autonomous Wary Collision Avoidance2021Ingår i: IEEE Transactions on Intelligent Vehicles, ISSN 2379-8858, E-ISSN 2379-8904, Vol. 6, nr 2, s. 353-365Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Handling of critical situations is an important part in the architecture of an autonomous vehicle. A controller for autonomous collision avoidance is developed based on a wary strategy that assumes the least tireroad friction for which the maneuver is still feasible. Should the friction be greater, the controller makes use of this and performs better. The controller uses an acceleration-vector reference obtained from optimal control of a friction-limited particle, whose applicability is verified by using numerical optimization on a full vehicle model. By employing an analytical tire model of the tireroad friction limit, to determine slip references for steering and body-slip control, the result is a controller where the computation of its output is explicit and independent of the actual tire-road friction. When evaluated in real-time on a high-fidelity simulation model, the developed controller performs close to that achieved by offline numerical optimization.

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  • 13.
    Fors, Victor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Formulation and interpretation of optimal braking and steering patterns towards autonomous safety-critical manoeuvres2019Ingår i: Vehicle System Dynamics, ISSN 0042-3114, E-ISSN 1744-5159, Vol. 57, nr 8, s. 1206-1223Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Stability control of a vehicle in autonomous safety-critical at-the-limit manoeuvres is analysed from the perspective of lane keeping or lane changing, rather than that of yaw control as in traditional ESC systems. An optimal control formulation is developed, where the optimisation criterion is a linear combination of the initial and final velocity of the manoeuvre. Varying the interpolation parameter in this formulation turns out to result in an interesting family of optimal braking and steering patterns in stabilising manoeuvres. The two different strategies of optimal lane-keeping control and optimal yaw control are shown to be embedded in the formulation and result from the boundary values of the parameter. The results provide new insights and have the potential to be used for future safety systems that adapt the level of braking to the situation at hand, which is demonstrated through examples of how to exploit theresults.

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    Formulation and interpretation of optimal braking and steering patterns towards autonomous safety-critical manoeuvres
  • 14.
    Fors, Victor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Formulation and Interpretation of Optimal Braking Patterns in Autonomous Lane-Keeping Maneuvers2017Konferensbidrag (Refereegranskat)
    Abstract [en]

    The two perspectives of autonomous driving and new active safety in vehicles are complementary, and both hold promise to reduce the number of accidents and associated severe or fatal injuries. They both coincide in the recent interest in finding alternatives to traditional yaw-control systems that can utilize the full potential of the vehicle. By considering the control problem as that of lane-keeping, also at high speed and at-the-limit of tire friction, rather than that of yaw control, leads to the possibility of optimization-based active-braking systems with better performance than those existing today. Here, we investigate the optimal braking patterns in completely autonomous lane-keeping maneuvers resulting from a formulation where the optimization criterion used is an interpolation between the initial and final velocities of the maneuver. Varying the interpolation parameter, i.e., the relative weight between the initial and final velocity, results in different vehicle behavior. The analysis of these behaviors provides several new insights into stabilizing braking patterns for vehicles in at-the-limit maneuvers. Specifically, it is to be noted that the benefits of a lane-keeping strategy are immediate, both in terms of the maximum possible initial velocity and the velocity reduction. The formulation embeds the traditional yaw control and optimal lane-keeping as the end-point values of the interpolation parameter, and adds a continuous family of behaviors in between. This gives a new perspective for investigating the relation between traditional yaw control and optimal lane-keeping for autonomous vehicles.

  • 15.
    Fors, Victor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Slip-Angle Feedback Control for Autonomous Safety-Critical Maneuvers At-the-Limit of Friction2018Ingår i: Proceedings of the 14th International Symposium on Advanced Vehicle Control (AVEC’ 18), 2018Konferensbidrag (Refereegranskat)
    Abstract [en]

    From the basis of optimal control, a closed-loop controller for autonomous vehicle maneuvers at-the-limit of friction is developed.The controller exploits that the optimal solution tends to be close to the friction limit of the tires.This observation allows for simplifications that enable the use of a proportional feedback control in the control loop,which provides a smooth trajectory promising for realization in an actual control system.The controller is in comparison with an open-loop numerical optimal control solution shown to exhibit promising performance at low computational cost in a challenging turn scenario.

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    Slip-Angle Feedback Control for Autonomous Safety-Critical Maneuvers At-the-Limit of Friction
  • 16.
    Fors, Victor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Department of Automatic Control, Lund University, Lund, Sweden.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Yaw-Moment Control At-the-Limit of Friction Using Individual Front-Wheel Steering and Four-Wheel Braking2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    A simplified combined-slip model that only considers the extreme case at the friction limit is suggested and used in a closed-loop controller for autonomous vehicle handling in at-the-limit maneuvers. In the development of the controller it is assumed that the front wheels are individually steered, but it is demonstrated in a left-hand turn scenario that with a simple adaptation, the method is still applicable for a vehicle with equal front-wheel angles.

  • 17.
    Olofsson, Björn
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Nielsen, Lars
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Using Crash Databases to Predict Effectiveness of New Autonomous Vehicle Maneuvers for Lane-Departure Injury Reduction2021Ingår i: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 22, nr 6, s. 3479-3490Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Autonomous vehicle functions in safety-critical situations show promise in reducing the risk and saving lives in accidents compared to existing safety systems. Consequently, it is from many perspectives advantageous to be able to quantify the potential benefits of new autonomous systems for vehicle maneuvers at-the-limit of tire friction. Here, to estimate the potential in terms of saved lives and reduced degree of injuries in accidents for new, not yet existing systems, a framework has been developed by combining available historic data, in the form of crash databases, and statistical methods with comparative calculations of vehicle behavior using numerical optimization rather than simulation. The framework performs effectively, it gives interesting insights into the relation between more traditional active yaw control and optimal autonomous lane-keeping control, and it clearly demonstrates the potential of saved lives by using autonomous vehicle maneuvers.

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  • 18.
    Westny, Theodor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Frisk, Erik
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Vehicle Behavior Prediction and Generalization Using Imbalanced Learning Techniques2021Ingår i: 24th IEEE International Intelligent Transportation Systems Conference (ITSC), 19-22 Sept. 2021, Institute of Electrical and Electronics Engineers (IEEE), 2021, s. 2003-2010Konferensbidrag (Refereegranskat)
    Abstract [en]

    The use of learning-based methods for vehicle behavior prediction is a promising research topic. However, many publicly available data sets suffer from class distribution skews which limits learning performance if not addressed. This paper proposes an interaction-aware prediction model consisting of an LSTM autoencoder and SVM classifier. Additionally, an imbalanced learning technique, the multiclass balancing ensemble is proposed. Evaluations show that the method enhances model performance, resulting in improved classification accuracy. Good generalization properties of learned models are important and therefore a generalization study is done where models are evaluated on unseen traffic data with dissimilar traffic behavior stemming from different road configurations. This is realized by using two distinct highway traffic recordings, the publicly available NGSIM US-101 and I80 data sets. Moreover, methods for encoding structural and static features into the learning process for improved generalization are evaluated. The resulting methods show substantial improvements in classification as well as generalization performance.

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  • 19.
    Westny, Theodor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Lund University, Sweden.
    Frisk, Erik
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Uncertainties in Robust Planning and Control of Autonomous Tractor-Trailer Vehicles2022Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    To study the effects of uncertainty in autonomous motion planning and control, an 8-DOF model of a tractor-semitrailer is implemented and analyzed. The implications of uncertainties in the model are then quantified and presented using sensitivity analysis and closed-loop simulations. The study shows that different model parameters are more or less critical depending on the investigated scenario.- Using sampling-based closed-loop predictions, uncertainty bounds on state variable trajectories are determined. Our findings suggest the potential for the inclusion of our method within a robust predictive controller or as a driver-assistance system for rollover or lane departure warning.

  • 20.
    Westny, Theodor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Oskarsson, Joel
    Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Frisk, Erik
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Evaluation of Differentially Constrained Motion Models for Graph-Based Trajectory PredictionManuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

     Given their adaptability and encouraging performance, deep-learning models are becoming standard for motion prediction in autonomous driving. However, with great flexibility comes a lack of interpretability and possible violations of physical constraints.  Accompanying these data-driven methods with differentially-constrained motion models to provide physically feasible trajectories is a promising future direction. The foundation for this work is a previously introduced graph-neural-network-based model, MTP-GO.  The neural network learns to compute the inputs to an underlying motion model to provide physically feasible trajectories. This research investigates the performance of various motion models in combination with numerical solvers for the prediction task. The study shows that simpler models, such as low-order integrator models, are preferred over more complex ones, e.g., kinematic models, to achieve accurate predictions. Further, the numerical solver can have a substantial impact on performance, advising against commonly used first-order methods like Euler forward. Instead, a second-order method like Heun's can significantly improve predictions.

  • 21.
    Westny, Theodor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Oskarsson, Joel
    Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Lund Univ, Sweden.
    Frisk, Erik
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Evaluation of Differentially Constrained Motion Models for Graph-Based Trajectory Prediction2023Ingår i: 2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV, IEEE , 2023Konferensbidrag (Refereegranskat)
    Abstract [en]

    Given their flexibility and encouraging performance, deep-learning models are becoming standard for motion prediction in autonomous driving. However, with great flexibility comes a lack of interpretability and possible violations of physical constraints. Accompanying these data-driven methods with differentially-constrained motion models to provide physically feasible trajectories is a promising future direction. The foundation for this work is a previously introduced graph-neural-network-based model, MTP-GO. The neural network learns to compute the inputs to an underlying motion model to provide physically feasible trajectories. This research investigates the performance of various motion models in combination with numerical solvers for the prediction task. The study shows that simpler models, such as low-order integrator models, are preferred over more complex, e.g., kinematic models, to achieve accurate predictions. Further, the numerical solver can have a substantial impact on performance, advising against commonly used first-order methods like Euler forward. Instead, a second-order method like Heuns can greatly improve predictions.

  • 22.
    Westny, Theodor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Oskarsson, Joel
    Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Frisk, Erik
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    MTP-GO: Graph-Based Probabilistic Multi-Agent Trajectory Prediction with Neural ODEsManuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    Enabling resilient autonomous motion planning requires robust predictions of surrounding road users' future behavior. In response to this need and the associated challenges, we introduce our model titled MTP-GO. The model encodes the scene using temporal graph neural networks to produce the inputs to an underlying motion model. The motion model is implemented using neural ordinary differential equations where the state-transition functions are learned with the rest of the model. Multimodal probabilistic predictions are obtained by combining the concept of mixture density networks and Kalman filtering. The results illustrate the predictive capabilities of the proposed model across various data sets, outperforming several state-of-the-art methods on a number of metrics.

  • 23.
    Westny, Theodor
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Oskarsson, Joel
    Linköpings universitet, Institutionen för datavetenskap, Statistik och maskininlärning. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Department of Automatic Control, Lund University, Sweden.
    Frisk, Erik
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    MTP-GO: Graph-Based Probabilistic Multi-Agent Trajectory Prediction With Neural ODEs2023Ingår i: IEEE Transactions on Intelligent Vehicles, ISSN 2379-8858, E-ISSN 2379-8904, Vol. 8, nr 9, s. 4223-4236Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Enabling resilient autonomous motion planning requires robust predictions of surrounding road users’ future behavior. In response to this need and the associated challenges, we introduce our model titled MTP-GO. The model encodes the scene using temporal graph neural networks to produce the inputs to an underlying motion model. The motion model is implemented using neural ordinary differential equations where the state-transition functions are learned with the rest of the model. Multimodal probabilistic predictions are obtained by combining the concept of mixture density networks and Kalman filtering. The results illustrate the predictive capabilities of the proposed model across various data sets, outperforming several state-of-the-art methods on a number of metrics.

  • 24.
    Zhou, Jian
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten. Department of Automatic Control, Lund University, Lund, Sweden.
    Frisk, Erik
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Interaction-Aware Motion Planning for Autonomous Vehicles with Multi-Modal Obstacle Uncertainties Using Model Predictive ControlManuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    This paper proposes an interaction-aware motion-planning method for an autonomous vehicle in uncertain multi-vehicle traffic environments. An interaction-aware motion-prediction model is used to predict the behaviors of surrounding vehicles. The multi-modal prediction uncertainties, containing both the maneuver and trajectory uncertainties of surrounding vehicles, are considered in the method for resilient motion planning of the ego vehicle. Based on the prediction of the surrounding vehicles, an optimal reference trajectory of the ego vehicle is computed by model predictive control (MPC) to follow the time-varying reference targets and avoid collisions with obstacles. A trade-off between the performance and robustness of the method can be achieved by tuning a safety-awareness parameter in the MPC. The efficiency of the method is illustrated in challenging highway-driving simulation scenarios and a driving scenario from a recorded traffic dataset.

  • 25.
    Zhou, Jian
    et al.
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Olofsson, Björn
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Frisk, Erik
    Linköpings universitet, Institutionen för systemteknik, Fordonssystem. Linköpings universitet, Tekniska fakulteten.
    Interaction-Aware Moving Target Model Predictive Control for Autonomous Vehicles Motion Planning2022Ingår i: 2022 EUROPEAN CONTROL CONFERENCE (ECC), IEEE , 2022, s. 154-161Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper investigates an integrated traffic environment modeling and model predictive control (MPC) system to realize interaction-aware dynamic motion planning of an autonomous vehicle with multiple surrounding vehicles. The interaction-aware interacting multiple model Kalman filter (IAIMM-KF) from the literature is used to hierarchically predict maneuvers and trajectories of surrounding vehicles and to compute safe targets for the ego vehicle. The targets are terminal speed and reference lane, which are moving targets as they are updated at each time step. Then, an MPC controller is designed for the ego vehicle to generate an optimal trajectory by following the moving targets and including the prediction results to formulate collision-free constraints. The proposed interaction-aware planning method has a proactive planning ability and can avoid collisions by non-local replanning. The strengths and effectiveness of the approach are verified in challenging highway lane-change simulation scenarios.

1 - 25 av 25
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