Automatic recognition of driving scenarios for ADAS design. Issue 11 (2016)
- Record Type:
- Journal Article
- Title:
- Automatic recognition of driving scenarios for ADAS design. Issue 11 (2016)
- Main Title:
- Automatic recognition of driving scenarios for ADAS design
- Authors:
- Lucchetti, Alberto
Ongini, Carlo
Formentin, Simone
Savaresi, Sergio M.
Del Re, Luigi - Abstract:
- Abstract: In this paper, a method to characterize and automatically recognize the most common driving scenarios in on-road experiments is presented. The aim of the proposed approach is to build a suitable simulator to develop and test Advanced Driver Assistance Systems (ADAS's). Therefore, unlike most of the existing algorithms, the whole procedure takes advantage of the intrinsic off-line nature of the problem. Context-free grammars are shown to be an effective and suitable tool for modeling the driving scenarios, while experimental results are used to validate the proposed approach and show limits and potential of a real-world application.
- Is Part Of:
- IFAC-PapersOnLine. Volume 49:Issue 11(2016)
- Journal:
- IFAC-PapersOnLine
- Issue:
- Volume 49:Issue 11(2016)
- Issue Display:
- Volume 49, Issue 11 (2016)
- Year:
- 2016
- Volume:
- 49
- Issue:
- 11
- Issue Sort Value:
- 2016-0049-0011-0000
- Page Start:
- 109
- Page End:
- 114
- Publication Date:
- 2016
- Subjects:
- ADAS -- simulation -- driving scenario detection
Automatic control -- Periodicals
629.805 - Journal URLs:
- https://www.journals.elsevier.com/ifac-papersonline/ ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.ifacol.2016.08.017 ↗
- Languages:
- English
- ISSNs:
- 2405-8963
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7606.xml