Speed limit determination by real-time embedded visual and cartographical data fusion
type: Dataset
description: ADAS (Autonomous Driving Assistance Systems) are more and more integrated in vehicles and provide to drivers more confort and safety. In this thesis, we focused on Intelligent Speed Adaptation. We proposed an approach combining vision and navigation in order to optimally manage the driving context information.Roadsigns, subsigns and markings are visual data used by the driver to determine the current temporary speed limitations. Many research were conducted during last years to recognise the first one, contrary to the second. Commercialised products are even implemented in vehicles. We thus developped a subsign detection and classification module using greyscale images. A morphological reconstruction with a growing region helped us to focus the segmentation on highly contrasted pixels surrounded by homogeneous regions. Global descriptors such as PHOGs combined to a hierarchical structure of SVMs were then used to classify the output rectangles. Finally, we eliminated subsigns which are not applicable to the current lane by considering markings.After having developed a vision module integrating all the available information, we improved the navigation system. The objective was to extract from an embedded database the driving context related to the vehicle position. Urban context or not, functional class, road type and speed limit were collected and modelised into criteria. The sensor reliability was then computed and depended on the satellite configuration and the network digitisation quality. Confidence in each speed limit combined all these elements.Fusion of both sources with the Dempster-Shafer theory led to very good performances on our databases et showed the importance of all the used information.
identifier: NNT: 2013ENMP0042
issued: 2026-05-06T02:26:27.190780
language: fr
modified: 2026-05-06T02:26:27.190785
contact point: Organization
  fn: CCSD
keyword: data-fusion
keyword: fusion-de-donnees
keyword: image-processing
keyword: infoeu-reposemanticsdoctoralthesis
keyword: navigation
keyword: navigation-based-system
keyword: spiotherengineering-sciences-physicsother
keyword: theses
keyword: traitement-dimage
landing page: https://pastel.hal.science/pastel-00957392

Speed limit determination by real-time embedded visual and cartographical data fusion
type: Distribution
format: HTML
issued: 2026-05-06T02:26:27.207754
modified: 2026-05-06T02:26:27.177126
access URL: https://pastel.hal.science/pastel-00957392

test_moissonnage_selune
type: Agent