Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 99 tok/s
Gemini 2.5 Pro 43 tok/s Pro
GPT-5 Medium 33 tok/s Pro
GPT-5 High 30 tok/s Pro
GPT-4o 110 tok/s Pro
Kimi K2 207 tok/s Pro
GPT OSS 120B 467 tok/s Pro
Claude Sonnet 4 36 tok/s Pro
2000 character limit reached

Towards a Digital Highway Code using Formal Modelling and Verification of Timed Automata (2209.14036v1)

Published 28 Sep 2022 in cs.LO, cs.FL, and cs.SE

Abstract: One of the challenges in designing safe, reliable and trustworthy Autonomous Vehicles (AVs) is to ensure that the AVs abide by traffic rules. For this, the AVs need to be able to understand and reason about traffic rules. In previous work, we introduce the spatial traffic logic USL-TR to allow for the unambiguous, machine-readable, formalisation of traffic rules. This is only the first step towards autonomous traffic agents that verifiably follow traffic rules. In this research preview, we focus on two further steps: a) retrieving behaviour diagrams directly from traffic rules and b) converting the behaviour diagrams into timed automata that are using formulae of USL-TR in guards and invariants. With this, we have a formal representation for traffic rules and can move towards the establishment of a Digital Highway Code. We briefly envision further steps which include adding environment and agent models to the timed automata to finally implement and verify these traffic rule models using a selection of formal verification tools.

Citations (2)
List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-Up Questions

We haven't generated follow-up questions for this paper yet.