scispace - formally typeset
Journal ArticleDOI

Recursive 3-D road and relative ego-state recognition

E.D. Dickmanns, +1 more
- 01 Feb 1992 - 
- Vol. 14, Iss: 2, pp 199-213
TLDR
The general problem of recognizing both horizontal and vertical road curvature parameters while driving along the road has been solved recursively and a differential geometry representation decoupled for the two curvature components has been selected.
Abstract
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 E.D. Dickmanns and A. Zapp (1986) and its refinements, a simple spatio-temporal model of the driving process makes it possible 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 microprocessors. Results with the test vehicle (VaMoRs), which is a 5-ton van, are given for a hilly country road. >

read more

Citations
More filters
Journal ArticleDOI

Vision for mobile robot navigation: a survey

TL;DR: The developments of the last 20 years in the area of vision for mobile robot navigation are surveyed and the cases of navigation using optical flows, using methods from the appearance-based paradigm, and by recognition of specific objects in the environment are discussed.
Journal ArticleDOI

GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection

TL;DR: The generic obstacle and lane detection system (GOLD), a stereo vision-based hardware and software architecture to be used on moving vehicles to increment road safety, allows to detect both generic obstacles and the lane position in a structured environment at a rate of 10 Hz.
Journal ArticleDOI

Video-based lane estimation and tracking for driver assistance: survey, system, and evaluation

TL;DR: A comparison of a wide variety of methods, pointing out the similarities and differences between methods as well as when and where various methods are most useful, is presented.
Journal ArticleDOI

Three Decades of Driver Assistance Systems: Review and Future Perspectives

TL;DR: This contribution provides a review of fundamental goals, development and future perspectives of driver assistance systems, and examines the progress incented by the use of exteroceptive sensors such as radar, video, or lidar in automated driving in urban traffic and in cooperative driving.
Journal ArticleDOI

Deep Multi-Modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges

TL;DR: In this article, the authors systematically summarize methodologies and discuss challenges for deep multi-modal object detection and semantic segmentation in autonomous driving and provide an overview of on-board sensors on test vehicles, open datasets, and background information for object detection.
References
More filters
Book ChapterDOI

Two Multi-Processor Systems for Low-Level Real-Time Vision

Volker Graefe
TL;DR: Two multi-processor systems are described that have been designed to serve as pre-processors in hierarchical computer vision systems for the automatic interpretation of image sequences in real time.
Proceedings Article

Relative 3D-State Estimation for Autonomous Visual Guidance of Road Vehicles

TL;DR: In this paper, the integrated spatio-temporal approach to real-time machine vision, which has allowed outstanding performance with moderate computing power, is extended to obstacle recognition and relative spatial state estimation.
Book ChapterDOI

Control of an Unstable Plant by Computer Vision

TL;DR: The measurement and control concept for a computer vision system that works on the basis of conventional TV-signals and the system is used to stabilize an inverted pendulum on an electro-cart with closed loop corner frequencies up to 1 Hz.
Journal ArticleDOI

Synthesis of a road image as seen from a vehicle

TL;DR: An approach to synthesizing a road image as seen from the vehicle, defined in a model of a road, shows that it is sufficient to extract parameters in order to obtain 3D information in road image analysis.
Related Papers (5)