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...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2022
|
| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/cclaw/6 https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1005&context=cclaw |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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. |
|---|