CASA: An Alternative Smartphone-Based ADAS

Manolo Dulva Hina, Hongyu Guan (), Assia Soukane () and Amar Ramdane-Cherif ()
Additional contact information
Manolo Dulva Hina: ECE Paris School of Engineering, 37 quai de Grenelle, 75015 Paris, France
Hongyu Guan: LISV Laboratory, Université de Versailles-Paris Saclay, 10-12 avenue de l’Europe, 78140 Vélizy, France
Assia Soukane: ECE Paris School of Engineering, 37 quai de Grenelle, 75015 Paris, France
Amar Ramdane-Cherif: LISV Laboratory, Université de Versailles-Paris Saclay, 10-12 avenue de l’Europe, 78140 Vélizy, France

International Journal of Information Technology & Decision Making (IJITDM), 2022, vol. 21, issue 01, 273-313

Abstract: Advanced driving assistance system (ADAS) is an electronic system that helps the driver navigate roads safely. A typical ADAS, however, is suited to specific brands of vehicle and, due to proprietary restrictions, has non-extendable features. Project CASA is an alternative, low-cost generic ADAS. It is an app deployable on smartphone or tablet. The real-time data needed by the app to make sense of its environment are stored in the vehicle or on the cloud, and are accessible as web services. They are used to determine the current driving context, and, if needed, decide actions to prevent an accident or keep road navigation safe. Project CASA is an undertaking of a consortium of industrial and academic partners. A use case scenario is tested in the laboratory (virtual) and on the road (actual) to validate the appropriateness of CASA. It is a contribution to safe driving. CASA’s contribution also lies in its approach in the semantic modeling of the context of the environment, the vehicle and the driver, and on the modeling of rules for fusion of data and fission process yielding an action to be implemented. In addition, CASA proposes a secured means of transmitting data using light, via light fidelity (LiFi), itself an alternative means of wireless vehicle–smartphone communication.

Keywords: ADAS; data fusion; fission; ontology; context-aware system; safe driving; green driving (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219622021500541
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijitdm:v:21:y:2022:i:01:n:s0219622021500541

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219622021500541

Access Statistics for this article

International Journal of Information Technology & Decision Making (IJITDM) is currently edited by Yong Shi

More articles in International Journal of Information Technology & Decision Making (IJITDM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().