@article{ref1,
title="Tentacle algorithm of obstacle avoidence and autonomous driving for intelligent vehicle",
journal="Journal of traffic and transportation engineering (Xi'an, Shaanxi)",
year="2010",
author="Niu, Run-Xin and Xia, Jing-Ting and Wang, Xiao-Hua and Mei, Tao",
volume="10",
number="6",
pages="53-58",
abstract="Obstacle map was established by using velodyne radar. Tentacle regeneration, autonomous driving and avoiding obstacle strategy were analyzed. The influence of sideslip angle on tentacle regeneration was considered. INS(inertial navigation system) sensors with GPS were integrated by Kalman filter, and the longitudinal velocity and lateral velocity of vehicle were obtained. Therefore, tentacle regeneration method corresponding to specific &quot;speed sets&quot; based on sideslip angle identification was promoted. At low-medium speed, trajectory error reduces from 0.40 m to 0.20 m. At high speed, because of using good-performance controller and appropriate fusion parameters, trajectory error reduces from 1.00 m to 0.75 m. Analysis result indicates that the promoted method effectively ensures obstacle avoidence and autonomous driving.<p />",
language="",
issn="1671-1637",
doi="",
url="http://dx.doi.org/"
}