Minimum-Violation Velocity Planning with Temporal Logic Constraints

Halder, Patrick; Althoff, Matthias

doi:10.1109/itsc55140.2022.9922114

Cited by 3 publications

(2 citation statements)

References 35 publications

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“…Under certain prerequisites, rulebooks induce a lexicographic order on a set of potential system trajectories. Lexicographic preferences provide a clear and comprehensive approach for handling contradicting constraints, ensuring that the most important constraints are satisfied first [1], [11]. Rulebooks can be effectively applied to planning tasks, as demonstrated in [4], [12].…”

Section: A Related Workmentioning

confidence: 99%

Lexicographic Mixed-Integer Motion Planning with STL Constraints

Halder,

Christ,

Althoff

2023

2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)

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Autonomous vehicles are subject to various constraints, such as following the rules of the road (ROTR), adhering to schedules, or providing a comfortable driving experience. However, realizing a driving behavior complying with all constraints is challenging since it is not always possible to satisfy them simultaneously, necessitating the formulation of compromises. In this paper, we propose a solution to this challenge by decomposing the specification of an autonomous vehicle into a rulebook utilized by a novel optimization-based minimum-violation motion planner. In particular, our planner uses reachable sets to prevent collisions with other road users, and it minimally violates the ROTR formalized in signal temporal logic (STL). Furthermore, a mixed-integer convex program (MICP) realization of the planner is provided to demonstrate its effectiveness, especially in dynamically changing environments. We evaluate our approach using realistic ROTR on 1780 scenarios from the CommonRoad benchmark suite. Our results show that our planner generates safe and feasible trajectories, indicating its potential for real-world applications.

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Section: A Related Workmentioning

confidence: 99%

Lexicographic Mixed-Integer Motion Planning with STL Constraints

Halder,

Christ,

Althoff

2023

2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)

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“…Autonomous robotic vehicles are increasingly being adopted in everyday life, for instance through car-platooning applications [1], urban transportation services [2], and robotic wheelchairs [3]. The last class of vehicles is an effective solution for individuals with severe disabilities or handicaps who have no possibility of controlling a typical motorized wheelchair.…”

Section: Introductionmentioning

confidence: 99%

Antifragile Control Systems: The Case of Mobile Robot Trajectory Tracking Under Uncertainty and Volatility

Axenie,

Saveriano

2023

IEEE Access

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Assistive care robots operate in cluttered, complex environments, akin to human residences, and need to face sensor and actuator faults during their operation without compromising safety. In these situations, the system must foresee and provide reactions that are beyond robust in addition to compensating for uncertainty and volatility in its functioning. We propose a new control design framework based on the principles of antifragility. In this work, we provide a formal concept of antifragile control and outline the design procedures for creating a mobile robot trajectory-tracking antifragile controller. An extended comparative evaluation against other controllers and a methodical investigation of the performance under parametrizable uncertainty and errors is also provided. Our findings demonstrate the effectiveness of antifragile closed-loop control in volatile and unanticipated circumstances.

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Towards Safe Autonomous Driving: Model Checking a Behavior Planner during Development

König,

Heinzemann,

Griggio

et al. 2024

Tools and Algorithms for the Construction and Analysis of Systems

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Automated driving functions are among the most critical software components to develop. Before deployment in series vehicles, it has to be shown that the functions drive safely and in compliance with traffic rules. Despite the coverage that can be reached with very large amounts of test drives, corner cases remain possible. Furthermore, the development is subject to time-to-delivery constraints due to the highly competitive market, and potential logical errors must be found as early as possible. We describe an approach to improve the development of an actual industrial behavior planner for the Automated Driving Alliance between Bosch and Cariad. The original process landscape for verification and validation is extended with model checking techniques. The idea is to integrate automated extraction mechanisms that, starting from the C++ code of the planner, generate a higher-level model of the underlying logic. This model, composed in closed loop with expressive environment descriptions, can be exhaustively analyzed with model checking. This results, in case of violations, in traces that can be re-executed in system simulators to guide the search for errors. The approach was exemplarily deployed in series development, and successfully found relevant issues in intermediate versions of the planner at development time.

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Minimum-Violation Velocity Planning with Temporal Logic Constraints

Cited by 3 publications

References 35 publications

Lexicographic Mixed-Integer Motion Planning with STL Constraints

Lexicographic Mixed-Integer Motion Planning with STL Constraints

Antifragile Control Systems: The Case of Mobile Robot Trajectory Tracking Under Uncertainty and Volatility

Towards Safe Autonomous Driving: Model Checking a Behavior Planner during Development

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