Moritz Werling

Moritz Werling
BMW Group

Dr.-Ing.

About

48
Publications
91,056
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2,540
Citations

Publications

Publications (48)
Preprint
Full-text available
Implementing an autonomous vehicle that is able to output feasible, smooth and efficient trajectories is a long-standing challenge. Several approaches have been considered, roughly falling under two categories: rule-based and learning-based approaches. The rule-based approaches, while guaranteeing safety and feasibility, fall short when it comes to...
Preprint
Full-text available
Well-established optimization-based methods can guarantee an optimal trajectory for a short optimization horizon, typically no longer than a few seconds. As a result, choosing the optimal trajectory for this short horizon may still result in a sub-optimal long-term solution. At the same time, the resulting short-term trajectories allow for effectiv...
Preprint
Challenging problems of deep reinforcement learning systems with regard to the application on real systems are their adaptivity to changing environments and their efficiency w.r.t. computational resources and data. In the application of learning lane-change behavior for autonomous driving, agents have to deal with a varying number of surrounding ve...
Preprint
Popular Maximum Entropy Inverse Reinforcement Learning approaches require the computation of expected state visitation frequencies for the optimal policy under an estimate of the reward function. This usually requires intermediate value estimation in the inner loop of the algorithm, slowing down convergence considerably. In this work, we introduce...
Preprint
In many real world applications, reinforcement learning agents have to optimize multiple objectives while following certain rules or satisfying a list of constraints. Classical methods based on reward shaping, i.e. a weighted combination of different objectives in the reward signal, or Lagrangian methods, including constraints in the loss function,...
Preprint
The common pipeline in autonomous driving systems is highly modular and includes a perception component which extracts lists of surrounding objects and passes these lists to a high-level decision component. In this case, leveraging the benefits of deep reinforcement learning for high-level decision making requires special architectures to deal with...
Preprint
Full-text available
In many real-world decision making problems, reaching an optimal decision requires taking into account a variable number of objects around the agent. Autonomous driving is a domain in which this is especially relevant, since the number of cars surrounding the agent varies considerably over time and affects the optimal action to be taken. Classical...
Conference Paper
Full-text available
Machine learning techniques have been shown to outperform many rule-based systems for the decision-making of autonomous vehicles. However, applying machine learning is challenging due to the possibility of executing unsafe actions and slow learning rates. We address these issues by presenting a reinforcement learning-based approach, which is combin...
Conference Paper
Full-text available
In order to determine a cooperative driving strategy, it is beneficial for an autonomous vehicle to incorporate the intended motion of surrounding vehicles within its own motion planning. However, as intentions cannot be measured directly and the motion of multiple vehicles often are highly interdependent, this incorporation has proven challenging....
Chapter
New active driver assistance systems that work at the road and navigation level as well as automated driving face a challenging task. They have to permanently calculate the vehicle input commands (such as those for the steering, brakes, and the engine/powertrain) in order to realize a desired future vehicle movement, a driving trajectory. This traj...
Article
In this paper, a trajectory optimization algorithm is proposed, which formulates the lateral vehicle guidance task along a reference curve as a constrained optimal control problem. The optimization problem is solved by means of a linear time-varying model predictive control scheme that generates trajectories for path following under consideration o...
Article
Zusammenfassung Die aus der Literatur bekannten Verfahren zur Optimierung von Fahrtrajektorien überfordern kurz und mittelfristig die Fahrzeugsteuergeräte hinsichtlich ihrer Rechenleistung. Um auch neu aufkommenden Qualitätsanforderungen zu entsprechen, nutzt die vorliegende Arbeit die aus der Literatur bekannten Vorteile der beschränkten, linear-q...
Article
Zusammenfassung In vielen kritischen Verkehrssituationen kann eine Kollision nicht durch alleiniges Bremsen vermieden werden. Insbesondere bei plötzlich den Fahrkorridor betretenden Fußgängern reicht der Bremsweg häufig nicht aus, um rechtzeitig zum Stehen zu kommen. Aus diesem Grund wird ein Trajektorienoptimierungsalgorithmus als wichtiger Teil e...
Article
Full-text available
This paper describes a power-slide control strategy for rear-wheel driven sports cars capable of tracking a course angle reference signal while stabilising large sliding angles of the vehicle. Owing to small slip angles at the front wheels compared to the ones at the sliding rear wheels and the precise yaw rate measurement, a fairly simple control...
Chapter
New active driver assistance systems that work at the road and navigation level as well as automated driving face a challenging task. They have to permanently calculate the vehicle input commands (such as those for the steering, brakes, and the engine/powertrain) in order to realize a desired future vehicle movement, a driving trajectory. This traj...
Conference Paper
Full-text available
In order to reduce the great number of parking incidences and other collisions in low speed scenarios, an obstacle avoidance algorithm is proposed. Since collision avoidance can be achieved by sole braking when driving slowly this algorithm's objective is a comfort orientated braking routine. Therefore, an optimization problem is formulated leading...
Article
Full-text available
Backing up a trailer can be a challenge, particularly for inexperienced recreational drivers. We therefore develop two feedback controllers, which support the driver with automatic steering inputs in various situations. Based on the kinematics of the general one-trailer system, we first derive an input/output-linearizing control law that asymptotic...
Article
Zusammenfassung Das rückwärtige Manövrieren mit Anhänger stellt nicht nur unerfahrene Freizeit-Gespannfahrer vor eine große Herausforderung. Aus diesem Grund werden zwei Regler als Kern eines Fahrerassistenzsystems entwickelt, das den Fahrer durch automatische Lenkeingriffe gezielt entlastet. Basierend auf den kinematischen Beziehungen von Fahrzeug...
Conference Paper
Full-text available
According to the analysis of car accidents many casualties occur at intersections. As ongoing research demonstrates, Advanced Driver Assistance Systems that aim at preventing this type of accident, need to reliably predict the turning maneuver of all relevant participants in the scene. In this work an approach is introduced, which models human driv...
Conference Paper
Full-text available
In many traffic emergency situations a collision cannot be prevented by braking alone. Therefore, we propose an obstacle avoidance algorithm that simultaneously optimizes steering and braking. As an emergency scenario approaches the driving limits, a strong nonlinear constraint between braking and cornering develops, suggesting the formulation of a...
Conference Paper
Full-text available
This paper presents a method for reasoning about the safety of traffic situations. More precisely, the problem of safety assessment for partial trajectories for vehicles is addressed. Therefore, the Inevitable Collision States (ICS) as well as its probabilistic generalization the Probabilistic Collision States (PCS) are used. Thereby, the assessmen...
Article
Full-text available
This paper deals with the trajectory generation problem faced by an autonomous vehicle in moving traffic. Being given the predicted motion of the traffic flow, the proposed semi-reactive planning strategy realizes all required long-term maneuver tasks (lane-changing, merging, distance-keeping, velocity-keeping, precise stopping, etc.) while providi...
Article
Full-text available
Zusammenfassung Die Beherrschung dynamischer Verkehrsszenarien erfordert die Stabilisierung von zeitkritischen Fahrmanövern, wie dem Ausweichen beweglicher Hindernisse oder dem Einfädeln in fließenden Verkehr. Beim autonomen Fahren stoßen hierbei die bisher eingesetzten bahnbasierten Verfahren an ihre Grenzen. Das im Beitrag mittels exakter Ein-/Au...
Article
Full-text available
This paper presents a method for reasoning about the safety of traffic situations. More precisely, the problem of safety assessment for partial trajectories for vehicles is addressed. Therefore, the Inevitable Collision States (ICS) as well as its probabilistic generalization the Probabilistic Collision States (PCS) are used. Thereby, the assessmen...
Chapter
This paper presents a framework for motion planning of autonomous vehicles, it is characterized by its efficient computation and its safety guarantees. An optimal control based approach generates comfortable and physically feasible maneuvers of the vehicle. Therefore, a combined optimization of the lateral and longitudinal movements in street-relat...
Conference Paper
Full-text available
In order to achieve autonomous operation of a vehicle in urban situations with unpredictable traffic, several realtime systems must interoperate, including environment perception, localization, planning, and control. In addition, a robust vehicle platform with appropriate sensors, computational hardware, networking, and software infrastructure is e...
Article
Full-text available
Safe handling of dynamic inner-city scenarios with autonomous road vehicles involves the problem of stabilization of precalculated state trajectories. In order to account for the practical requirements of the holistic autonomous system, we propose two complementary nonlinear Lyapunov-based tracking-control laws to solve the problem for speeds betwe...
Conference Paper
Full-text available
Safe handling of dynamic highway and inner city scenarios with autonomous vehicles involves the problem of generating traffic-adapted trajectories. In order to account for the practical requirements of the holistic autonomous system, we propose a semi-reactive trajectory generation method, which can be tightly integrated into the behavioral layer....
Article
Full-text available
Zusammenfassung Bei der Bahnregelung autonomer Fahrzeuge wird der kürzeste Abstand zwischen Fahrzeugposition und Bahn als Regelfehler verwendet. Um diesen Abstand zu bestimmen, ist der Projektionspunkt auf der Bahn fortwährend zu berechnen. Hierzu sind schnelle Algorithmen notwendig, die sich bei Fahrzeuganwendungen durch hohe numerische Zuverlässi...
Conference Paper
Full-text available
In this contribution, we develope a flatness-based control strategy suitable for parking assistance and autonomous maneuvering in static environments. It is derived from quasistatic trajectory tracking control in a straight-forward manner and preserves the invariance property (with respect to the choice of the initial frame) of the plant for the cl...
Article
Full-text available
Zusammenfassung Dieser Beitrag beschreibt ein Multireglerkonzept, welches verschiedene Quer- und Längsregler zur Erprobung vollautonomen Fahrens bereitstellt. Nach einer Beschreibung der praktischen Anforderungen an ein solches System, wird basierend auf der exakten Ein-/Ausgangslinearisierung eine Querregelungsstrategie beschrieben, der zwei Einsp...
Conference Paper
Full-text available
New technologies, such as Advanced Driver Assistance Systems (Adaptive Cruise Control, Automatic Parking, Lane Keeping Assistance, etc.) lead to a cooperation of human and machine and thus require manual/automatic transfer (MAT). Similar situations for human-machine interaction can be found in robotics and process engineering. Therefore, the primar...
Article
This paper reports on AnnieWAY, an autonomous vehicle that is capable of driving through urban scenarios and that successfully entered the finals of the 2007 DARPA Urban Challenge competition. After describing the main challenges imposed and the major hardware components, we outline the underlying software structure and focus on selected algorithms...
Conference Paper
Full-text available
We propose a method for navigating a car-like vehicle within an unstructured environment. Path planning is posed as a graph search problem. The search graph is set up in a way that implies derivation of a feed forward term for a downstream closed loop controller. An informed search algorithm is used that is guided by a heuristic cost function that...
Conference Paper
Full-text available
This paper describes the hardware and software framework of AnnieWAY, an autonomous vehicle successfully competing at all qualification stages up to the finals of the DARPA Urban Challenge 2007 competition. Besides the hardware premises for by-wire steering, braking, throttle control and sensors, two frameworks for high-level decision making and lo...
Conference Paper
Full-text available
This paper describes an algorithm for handling moving traffic which was deployed on AnnieWAY, an autonomous vehicle successfully entering the finals of the DARPA Urban Challenge 2007 competition. The algorithm allows for a robust and effective collision check for a variety of maneuvers including turning at intersections with oncoming traffic, mergi...
Conference Paper
Full-text available
The urban challenge 2007 is a research program conducted in a competitive format to address the challenging aspects of letting vehicles accomplish missions in urban scenarios fully autonomously. AnnieWAY is one out of eleven autonomous vehicles that entered the finals. As it turned out, one of the major difficulties is the combination of different...
Conference Paper
Full-text available
This paper reports on AnnieWAY, an autonomous vehicle that is capable of driving through urban scenarios and that has successfully entered the finals of the DARPA Urban Challenge 2007 competition. After describing the main challenges imposed and the major hardware components, we outline the underlying software structure and focus on selected algori...
Chapter
This paper reports on AnnieWAY, an autonomous vehicle that is capable of driving through urban scenarios and that has successfully entered the finals of the 2007 DARPA Urban Challenge competition. After describing the main challenges imposed and the major hardware components, we outline the underlying software structure and focus on selected algori...

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