RECURSIVE 3-D ROAD AND RELATIVE EGO-STATE RECOGNITION

被引：290

作者：

DICKMANNS, ED ^{[1
]}

MYSLIWETZ, BD ^{[1
]}

机构：

[1] BAASEL LASERTECH,STARNBERG,GERMANY

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 1992年 / 14卷 / 02期

关键词：

INTELLIGENT CONTROL; PARALLEL ARCHITECTURES; REALTIME MACHINE VISION; RECURSIVE ESTIMATION; SPATIOTEMPORAL MODELING; 3-D IMAGE SEQUENCE PROCESSING; VISUAL NAVIGATION (OF ROAD VEHICLES);

D O I：

10.1109/34.121789

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The general problem of recognizing both horizontal and vertical road curvature parameters while driving along the road has been solved recursively. A differential geometry representation decoupled for the two curvature components has been selected. Based on the planar solution of [7] and its refinements, a simple spatio-temporal model of the driving process allows us to take both spatial and temporal constraints into account effectively. The estimation process determines nine road and vehicle state parameters recursively at 25 Hz (40 ms) using four Intel 80286 and one 386 microprocessor. Results with the test vehicle (VaMoRs), which is a 5-ton van, are given for a hilly country road.

引用

页码：199 / 213

页数：15

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