Encoding and monitoring responsibility sensitive safety rules for automated vehicles in signal temporal logic

Mohammad Hekmatnejad, Shakiba Yaghoubi, Adel Dokhanchi, Heni Ben Amor, Aviral Shrivastava, Lina Karam, Georgios Fainekos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As Automated Vehicles (AV) get ready to hit the public roads unsupervised, many practical questions still remain open. For example, there is no commonly acceptable formal definition of what safe driving is. A formal definition of safe driving can be utilized in developing the vehicle behaviors as well as in certification and legal cases. Toward that goal, the Responsibility-Sensitive Safety (RSS) model was developed as a first step toward formalizing safe driving behavior upon which the broader AV community can expand. In this paper, we demonstrate that the RSS model can be encoded in Signal Temporal Logic (STL). Moreover, using the S-TaLiRo tools, we present a case study of monitoring RSS requirements on selected traffic scenarios from CommonRoad. We conclude that monitoring RSS rules encoded in STL is efficient even in heavy traffic scenarios. One interesting observation is that for the selected traffic data, vehicle parameters and response times, the RSS model violations are not frequent.

Original languageEnglish (US)
Title of host publicationMEMOCODE 2019 - 17th ACM-IEEE International Conference on Formal Methods and Models for System Design
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450369978
DOIs
StatePublished - Oct 9 2019
Event17th ACM-IEEE International Conference on Formal Methods and Models for System Design, MEMOCODE 2019 - San Diego, United States
Duration: Oct 9 2019Oct 11 2019

Publication series

NameMEMOCODE 2019 - 17th ACM-IEEE International Conference on Formal Methods and Models for System Design

Conference

Conference17th ACM-IEEE International Conference on Formal Methods and Models for System Design, MEMOCODE 2019
CountryUnited States
CitySan Diego
Period10/9/1910/11/19

Keywords

  • Monitoring
  • Responsibility-Sensitive Safety
  • Robustness
  • Signal-Temporal Logic

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Optimization
  • Modeling and Simulation

Fingerprint Dive into the research topics of 'Encoding and monitoring responsibility sensitive safety rules for automated vehicles in signal temporal logic'. Together they form a unique fingerprint.

  • Cite this

    Hekmatnejad, M., Yaghoubi, S., Dokhanchi, A., Amor, H. B., Shrivastava, A., Karam, L., & Fainekos, G. (2019). Encoding and monitoring responsibility sensitive safety rules for automated vehicles in signal temporal logic. In MEMOCODE 2019 - 17th ACM-IEEE International Conference on Formal Methods and Models for System Design [A6] (MEMOCODE 2019 - 17th ACM-IEEE International Conference on Formal Methods and Models for System Design). Association for Computing Machinery, Inc. https://doi.org/10.1145/3359986.3361203