Contract-based safety verification for autonomous driving
Name
1083761920-MIT.pdf
Description
Full printable version
Size
6.16 MB
Format
Adobe PDF
Checksum (MD5)
ddcb71c60d324207bcdec4535aa113e4
Author(s)
Liebenwein, Lucas
Advisor(s)
Daniela Rus.
Date Issued
2018
Publisher
Massachusetts Institute of Technology
Abstract
The safe, successful deployment of autonomous systems under real-world conditions, in part, hinges upon providing rigorous performance and safety guarantees. This thesis considers the problem of establishing and verifying the safety of autonomous systems. To this end, we present a novel framework for the synthesis of safety constraints for autonomous systems, so-called safety contracts, that can be applied to and used by a wide set of real-world systems by acting as a design requirement for the controller implementation of the system. The contracts consider a large variety of road models, guarantee that the controlled system will remain safe with respect to probabilistic models of traffic behavior, and ensure that it will follow the rules of the road. We generate contracts using reachability analysis in a reach-avoid problem under consideration of dynamic obstacles, i.e., other traffic participants. Contracts are then derived directly from the reachable sets. By decomposing large road networks into local road geometries and defining assume-guarantee contracts between local geometries, we enable computational tractability over large spatial domains. To efficiently account for the behavior of other traffic participants, we iteratively alternate between falsification to generate new traffic scenarios that violate the safety contract and reachable set computation to update the safety contract. These counterexamples to collision-free behavior are found by solving a gradient-based trajectory optimization problem. We demonstrate the practical effectiveness of the proposed methods in a set of experiments involving the Manhattan road network as well as interacting multi-car traffic scenarios.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 77-83).
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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