By Topic

Poster Abstract: State Estimation and Sensor Fusion for Autonomous Driving in Mixed-Traffic Urban Environments

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Emrah Adamey ; Electr. & Comput. Eng. Dept., Ohio State Univ., Columbus, OH, USA ; Yuksel Ozan Basciftci ; Peng Gong ; Arda Kurt
more authors

This poster investigates sensory data processing, filtering and sensor fusion methods for autonomous vehicles operating in real-life, urban environments with human and machine drivers, and pedestrians. Extended Kalman Filters were used to develop decentralized data fusion algorithms for communicating vehicles, Particle Filters were improved by assigning trust/confidence values in order to overcome faulty/compromised sensors, and the computational cost of particle filters were distributed by parallelizing the load using the developed Shared-Memory Systematic Resampling algorithm.

Published in:

Cyber-Physical Systems (ICCPS), 2012 IEEE/ACM Third International Conference on

Date of Conference:

17-19 April 2012