Interactive discovery of knowledge from activity traces : A synthesis of automata in the analysis and modelling of the activity of car driving
type: Dataset
description: Driving is a dynamic and complex activity. Understanding the origin of a driving situationrequires the analysis of the driver’s choices made while he/she drives. In addition,a driving situation has to be studied in its natural complexity and evolution. LESCOThas developed a model called COSMODRIVE, which provides a conceptual frameworkfor the cognitive simulation of the activity of car driving. In order to run themodel for a simulation, it is necessary to gather knowledge related to the driving situation,for example in the form of an automaton. The conception of such an automatonrequires : 1) the use of real data recorded in an instrumented car, and, 2) the use of humanexpertise to interpret these data. These data are considered in this thesis as activitytraces.The purpose of this thesis is to assist the Knowledge Engineering process of activityanalysis. The present thesis proposes a method to interactively discover knowledgefrom activity traces. For this purpose, data from car driving are considered as M-traces– which associate an explicit semantic to these data. This semantic is then used asknowledge in a Trace Based System. In a Trace Based System, M-traces can be filtered,transformed, reformulated, and abstracted. The resulting traces are then used as inputsin the production of an automaton model of the activity of driving. In this thesis,Workflow Mining techniques have been used to build automata (Petri nets) from logs.These techniques require complete or statistically representative data sets. However,data collected from instrumented vehicles are intrinsically unique, as no two drivingsituations will ever be identical. In addition, situations of particular interest, such ascritical situations, are rarely observed in instrumented vehicle studies. The challenge isthen to produce a model which is a form of generalisation from a limited set of cases,which have been judged by domain experts as being relevant and representative of whatactually happens.In the current…
identifier: NNT: 2012LYO10041
issued: 2026-05-09T15:46:16.741689
language: fr
modified: 2026-05-09T15:46:16.741692
contact point: Organization
  fn: CCSD
keyword: activity-traces
keyword: car-driving
keyword: conduite-automobile
keyword: decouverte-interactive-de-connaissances
keyword: engineering-of-the-dynamic-of-knowledge
keyword: human-activity-modelling
keyword: infoeu-reposemanticsdoctoralthesis
keyword: infoinfo-ohcomputer-science-csother-csoh
keyword: ingenierie-de-la-dynamique-des-connaissances
keyword: interactive-discovery-of-knowledge
keyword: modelisation-de-lactivite-humaine
keyword: petri-nets
keyword: reseaux-de-petri
keyword: theses
keyword: traces-dactivite
landing page: https://theses.hal.science/tel-00864865

Interactive discovery of knowledge from activity traces : A synthesis of automata in the analysis and modelling of the activity of car driving
type: Distribution
format: HTML
issued: 2026-05-09T15:46:16.750189
modified: 2026-05-09T15:46:16.727177
access URL: https://theses.hal.science/tel-00864865

test_moissonnage_selune
type: Agent