Efficiency analysis of formally verified adaptive cruise controllers

Loos, Sarah M.; Witmer, David; Steenkiste, Peter; Platzer, André

doi:10.1109/itsc.2013.6728453

Cited by 9 publications

(9 citation statements)

References 16 publications

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“…9 Interpretation of Verification Results 16 Recall, that po < p y x holds when the obstacle did not yet pass the intersection.…”

Section: Identification Of Live Controlsmentioning

confidence: 99%

“…Following Loos et al (2013b), we relax equation (23) so that the robot can choose any acceleration − b ≤ a ≤ A and checks this actual acceleration a for safety. This way, it only has to fall back to the emergency braking branch a : = − b if there is no other safe choice available.…”

Section: Refined Models For Safety Verificationmentioning

confidence: 99%

“…The differential invariants capture that time progresses (16), that the orientation stays a unit vector (17), that the new speed v r is determined by the previous speed old(v r ) 9 and the acceleration a r (18), and that the robot does not leave the bounding square of half side length t(v r − ar 2 t) around its previous position old(p r ) (19)-(20).…”

Section: Identification Of Safe Controlsmentioning

confidence: 99%

“….. In (119), instead, we start the deadline timer with a negative time T < 0, 16 such that it becomes T = 0 when the obstacle is located at the intersection.…”

Section: Identification Of Live Controlsmentioning

confidence: 99%

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Formal verification of obstacle avoidance and navigation of ground robots

Mitsch

Ghorbal

Vogelbacher

et al. 2017

The International Journal of Robotics Research

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The safety of mobile robots in dynamic environments is predicated on making sure that they do not collide with obstacles. In support of such safety arguments, we analyze and formally verify a series of increasingly powerful safety properties of controllers for avoiding both stationary and moving obstacles: (i) static safety, which ensures that no collisions can happen with stationary obstacles, (ii) passive safety, which ensures that no collisions can happen with stationary or moving obstacles while the robot moves, (iii) the stronger passive friendly safety in which the robot further maintains sufficient maneuvering distance for obstacles to avoid collision as well, and (iv) passive orientation safety, which allows for imperfect sensor coverage of the robot, i. e., the robot is aware that not everything in its environment will be visible. We complement these provably correct safety properties with liveness properties: we prove that provably safe motion is flexible enough to let the robot still navigate waypoints and pass intersections. We use hybrid system models and theorem proving techniques that describe and formally verify the robot's discrete control decisions along with its continuous, physical motion. Moreover, we formally prove that safety can still be guaranteed despite sensor uncertainty and actuator perturbation, and when control choices for more aggressive maneuvers are introduced. Our verification results are generic in the sense that they are not limited to the particular choices of one specific control algorithm but identify conditions that make them simultaneously apply to a broad class of control algorithms.

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“…9 Interpretation of Verification Results 16 Recall, that po < p y x holds when the obstacle did not yet pass the intersection.…”

Section: Identification Of Live Controlsmentioning

confidence: 99%

Section: Refined Models For Safety Verificationmentioning

confidence: 99%

Section: Identification Of Safe Controlsmentioning

confidence: 99%

“….. In (119), instead, we start the deadline timer with a negative time T < 0, 16 such that it becomes T = 0 when the obstacle is located at the intersection.…”

Section: Identification Of Live Controlsmentioning

confidence: 99%

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Formal verification of obstacle avoidance and navigation of ground robots

Mitsch

Ghorbal

Vogelbacher

et al. 2017

The International Journal of Robotics Research

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“…In [30] the dynamic window algorithm for obstacle avoidance is formally verified using theorem proving. The same technique is used in [26] to verify automatic cruise control under the assumption that all vehicles are automated. Other work uses barrier certificates to prove the safety of UAVs for given environments [6] or to find regions of attractions for an Acrobot [27].…”

Section: Introductionmentioning

confidence: 99%

Formal verification of maneuver automata for parameterized motion primitives

Hess

Althoff

Sattel

2014

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

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An increasing amount of robotic systems is developed for safety-critical scenarios, such as automated cars operating in public road traffic or robots collaborating with humans in flexible manufacturing systems. For this reason, it is important to provide methods that formally verify the safety of robotic systems. This is challenging since robots operate in continuous action spaces in partially unknown environments so that there exists no finite set of scenarios that can be verified before deployment. Verifying the safety during the operation based on the current perception of the environment is often infeasible due to the computational demand of formal verification methods. In this work, we compute sets of behaviors for parameterized motion primitives using reachability analysis, which is used to build a maneuver automaton that connects motion primitives in a safe way. Thus, the computationally expensive task of building a maneuver automaton is performed offline. The proposed analysis method provides the whole set of possible behaviors so that it can be verified whether forbidden state-space regions are avoided during the operation of the robot, to e.g. avoid colliding with obstacles. The method is applied to continuous sets of parameterized motion primitives, making it possible to verify infinitely many motions within the parameter space, which to the best knowledge of the authors has not been published before. The approach is demonstrated for collision avoidance of road vehicles.

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