Intelligent Advanced Driver Assistance System for Electric Vehicles

Author

Demestichas, Konstantinos ; Adamopoulou, Evgenia ; Masikos, Michalis ; Kipp, Wolfgang ; Benz, Thomas

Author_Institution

Inst. of Commun. & Comput. Syst., Athens, Greece

fYear

2011

fDate

5-9 June 2011

Firstpage

78

Lastpage

82

Abstract

Fully Electric Vehicles (FEVs) represent a promising solution for the reduction of fuel consumption, air and noise pollution in urban areas. However, the commercial viability of FEVs is at stake if the associated issues of autonomy are not dealt with effectively. Project EcoGem - Cooperative Advanced Driver Assistance System for Green Cars - advocates that the success and user acceptability of FEVs will predominantly depend on their electrical energy consumption rate and the corresponding degree of autonomy that they can offer. EcoGem aims at providing efficient ICT-based solutions to this great issue, by designing and developing a FEV-oriented highly-intelligent Advanced Driver Assistance System, equipped with suitable monitoring, learning, reasoning and management capabilities that will help increase the FEV´s autonomy and energy efficiency.

Keywords

air pollution control; driver information systems; electric vehicles; fuel economy; inference mechanisms; learning (artificial intelligence); noise pollution; Cooperative Advanced Driver Assistance System for Green Cars; FEV learning capability; FEV management capability; FEV monitoring capability; FEV reasoning capability; Project EcoGem; air pollution; energy efficiency; fuel consumption; fully electric vehicles; intelligent advanced driver assistance system; noise pollution; Batteries; Communication system security; Driver circuits; Electric vehicles; Energy efficiency; Wireless communication;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Vehicles Symposium (IV), 2011 IEEE

Conference_Location

Baden-Baden

ISSN

1931-0587

Print_ISBN

978-1-4577-0890-9

Type

conf

DOI

10.1109/IVS.2011.5940409

Filename

5940409