Title :
An intelligent predictive system for vehicle maneuvering
Author :
Kumar, Ashok ; Gummadi, Haritha ; Tesch, Robert
Author_Institution :
Dept. of Comput. Sci., Univ. of Louisiana at Lafayette, Lafayette, LA, USA
Abstract :
In today´s world of urban traffic environment, there is an immediate requirement to impose safety measures to avoid fatal accidents. To ensure safe driving, vehicles can be made intelligent by equipping them with sensors. This means that multiple sensors can be incorporated on the vehicle. Such system can act as a warning strategy that guides the driver of the vehicle to make right decisions at times of emergencies. The work in this paper highlights the decision making process by the vehicle by throwing light on applying a new approach. The new feature added is the application of Bayesian inference method to predict the fore vehicle behavior and future states and then, using the data collected from multiple sensors, the best possible decision is made.
Keywords :
automated highways; decision making; inference mechanisms; road safety; road traffic; road vehicles; Bayesian inference method; decision making process; intelligent predictive system; multiple sensors; urban traffic environment; vehicle maneuvering; Bayesian; Intelligent vehicles; manoeuvring; sensors; simulation; software;
Conference_Titel :
Systems Conference, 2010 4th Annual IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-5882-0
DOI :
10.1109/SYSTEMS.2010.5482440