Title :
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
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;
Conference_Titel :
Intelligent Vehicles Symposium (IV), 2011 IEEE
Conference_Location :
Baden-Baden
Print_ISBN :
978-1-4577-0890-9
DOI :
10.1109/IVS.2011.5940409
