Traffic rule formalization for autonomous vehicle

This study devised and implemented a Defeasible Deontic Logic (DDL)-based formalization approach for translating traffic rules into a machine-computable (M/C) format and thus solving rule issues: rule vagueness (open texture expressions) and exceptions in rules. The resulting M/C format of traffic r...

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Main Authors: BHUIYAN, Hanif, GOVERNATORI, Guido, RAKOTONIRAINY, Andry, WONG, Meng Weng, MAHAJAN, Avishkar
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Language:English
Published: Institutional Knowledge at Singapore Management University 2022
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Online Access:https://ink.library.smu.edu.sg/cclaw/6
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1005&context=cclaw
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Institution: Singapore Management University
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spelling sg-smu-ink.cclaw-10052023-03-22T07:15:26Z Traffic rule formalization for autonomous vehicle BHUIYAN, Hanif GOVERNATORI, Guido RAKOTONIRAINY, Andry WONG, Meng Weng MAHAJAN, Avishkar This study devised and implemented a Defeasible Deontic Logic (DDL)-based formalization approach for translating traffic rules into a machine-computable (M/C) format and thus solving rule issues: rule vagueness (open texture expressions) and exceptions in rules. The resulting M/C format of traffic rules can be utilized for automatic traffic rule reasoning to assist the Autonomous Vehicle (AV) in making legal decisions. The method incorporates the components and behaviour of regulations based on the rule's obligation, prohibition, and permission activities. The need for the encoding methodology is motivated by the desire for automated reasoning over Autonomous Vehicle information involving traffic rules. A Queensland (QLD) overtaking traffic rule is used as a use case to illustrate this proposed encoding methodology’s mechanism and usefulness. 2022-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/cclaw/6 https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1005&context=cclaw http://creativecommons.org/licenses/by-nc-nd/4.0/ Centre for Computational Law eng Institutional Knowledge at Singapore Management University Traffic Rules Norms Defeasible Deontic Logic Transportation Law
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Traffic Rules
Norms
Defeasible Deontic Logic
Transportation Law
spellingShingle Traffic Rules
Norms
Defeasible Deontic Logic
Transportation Law
BHUIYAN, Hanif
GOVERNATORI, Guido
RAKOTONIRAINY, Andry
WONG, Meng Weng
MAHAJAN, Avishkar
Traffic rule formalization for autonomous vehicle
description This study devised and implemented a Defeasible Deontic Logic (DDL)-based formalization approach for translating traffic rules into a machine-computable (M/C) format and thus solving rule issues: rule vagueness (open texture expressions) and exceptions in rules. The resulting M/C format of traffic rules can be utilized for automatic traffic rule reasoning to assist the Autonomous Vehicle (AV) in making legal decisions. The method incorporates the components and behaviour of regulations based on the rule's obligation, prohibition, and permission activities. The need for the encoding methodology is motivated by the desire for automated reasoning over Autonomous Vehicle information involving traffic rules. A Queensland (QLD) overtaking traffic rule is used as a use case to illustrate this proposed encoding methodology’s mechanism and usefulness.
format text
author BHUIYAN, Hanif
GOVERNATORI, Guido
RAKOTONIRAINY, Andry
WONG, Meng Weng
MAHAJAN, Avishkar
author_facet BHUIYAN, Hanif
GOVERNATORI, Guido
RAKOTONIRAINY, Andry
WONG, Meng Weng
MAHAJAN, Avishkar
author_sort BHUIYAN, Hanif
title Traffic rule formalization for autonomous vehicle
title_short Traffic rule formalization for autonomous vehicle
title_full Traffic rule formalization for autonomous vehicle
title_fullStr Traffic rule formalization for autonomous vehicle
title_full_unstemmed Traffic rule formalization for autonomous vehicle
title_sort traffic rule formalization for autonomous vehicle
publisher Institutional Knowledge at Singapore Management University
publishDate 2022
url https://ink.library.smu.edu.sg/cclaw/6
https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1005&context=cclaw
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