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Article Navigation >  Journal of Traffic and Transportation Engineering  > 2010  >  10(6): 53-58
NIU Run-xin, XIA Jing-ting, WANG Xiao-hua, MEI Tao. Tentacle algorithm of obstacle avoidence and autonomous driving for intelligent vehicle[J]. Journal of Traffic and Transportation Engineering, 2010, 10(6): 53-58. doi: 10.19818/j.cnki.1671-1637.2010.06.009
Citation: NIU Run-xin, XIA Jing-ting, WANG Xiao-hua, MEI Tao. Tentacle algorithm of obstacle avoidence and autonomous driving for intelligent vehicle[J]. Journal of Traffic and Transportation Engineering, 2010, 10(6): 53-58. doi: 10.19818/j.cnki.1671-1637.2010.06.009
shu

Tentacle algorithm of obstacle avoidence and autonomous driving for intelligent vehicle

doi: 10.19818/j.cnki.1671-1637.2010.06.009
  • 1.

    Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui, China

  • 2.

    State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China

More Information
  • Author Bio:

    NIU Run-xin(1971-),male,associate researcher,PhD,+86-551-5393191, rxniu@iim.ac.cn

  • Received Date: 2010-07-27
  • Publish Date: 2010-12-25
    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 "speed sets" 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.

     

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