Perception for collision avoidance and autonomous driving

被引:96
作者
Aufrère, R [1 ]
Gowdy, J [1 ]
Mertz, C [1 ]
Thorpe, C [1 ]
Wang, CC [1 ]
Yata, T [1 ]
机构
[1] Carnegie Mellon Univ, Inst Robot, Pittsburgh, PA 15213 USA
关键词
collision avoidance; autonomous driving; short-range surround sensing; optical flow; triangulation laser sensor; curb detection; LIDAR object detection; sensor fusion; collision prediction;
D O I
10.1016/S0957-4158(03)00047-3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Navlab group at Carnegie Mellon University has a long history of development of automated vehicles and intelligent systems for driver assistance. The earlier work of the group concentrated on road following, cross-country driving, and obstacle detection. The new focus is on short-range sensing, to look all around the vehicle for safe driving. The current system uses video sensing, laser rangefinders, a novel light-stripe rangefinder, software to process each sensor individually, a map-based fusion system, and a probability based predictive model. The complete system has been demonstrated on the Navlab I I vehicle for monitoring the environment of a vehicle driving through a cluttered urban environment, detecting and tracking fixed objects, moving objects, pedestrians, curbs, and roads. (C) 2003 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1149 / 1161
页数:13
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