Probabilistic Logic Reasoning about Traffic Scenes

Carlos R.C. Souza, Paulo E. Santos

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper describes a probabilistic logic reasoning system for traffic scenes based on Markov logic network, whose goal is to provide a high-level interpretation of localisation and behaviour of a vehicle on the road. This information can be used by a lane assistant agent within driver assistance systems. This work adopted an egocentric viewpoint for the vision and the reasoning tasks of the vehicle and a qualitative approach to spatial representation. Results with real data indicate good performance compared to the common sense interpretation of traffic situations.

Original languageEnglish
Title of host publicationTowards Autonomous Robotic Systems
Subtitle of host publication12th Annual Conference, TAROS 2011, Sheffield, UK, August 31 – September 2, 2011. Proceedings
PublisherSpringer
Pages219-230
Number of pages12
ISBN (Electronic)978-3-642-23232-9
ISBN (Print)978-3-642-23231-2
DOIs
Publication statusPublished - 20 Sep 2011
Externally publishedYes
Event12th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2011 - Sheffield, United Kingdom
Duration: 31 Aug 20112 Sep 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6856 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2011
CountryUnited Kingdom
CitySheffield
Period31/08/112/09/11

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