Vision System For Vehicles Research Articles

IVS 09: Future Research in Vehicle Vision Systems

Visual sensing plays an essential role in intelligent vehicles. With the aid of visual sensors, driver assistance systems can alert the driver to dangerous situations or actions (such as swerving out of the lane or disregarding traffic signs or lights), or even independently take control of the vehicle. Currently, research on vehicle vision systems is receiving continuous global interest.This paper discusses some future directions for this field based on trends we observed at the 2008 IEEE Conference on Intelligent Transportation Systems (ITSC 08) and the 2009 IEEE Intelligent Vehicles Symposium (IVS 09). Our aim is to attract researchers to several critical questions that are important yet difficult. Solving these problems could be of great benefit to both academia and the vehicle industries.

Self-detection of optical contamination or occlusion in vehicle vision systems

We present a novel and practical algorithm for the self-detection problem of contamination or occlusions on the lens of a camera mounted on a vehicle. First, we analyze the intrinsic characteristics of such contamination on the video image. Based on this, cumulative differences are used to segment the static region in the image. A blurred edge detection algorithm based on wavelet decomposition is introduced to confirm if the static region belongs to contamination or an occlusion. Through the combination of these algorithms, contamination or occlusions can be detected. Experimental data are analyzed to show the detection performance of our algorithm and the effect of different contamination or occlusion material.

A temporal fusion strategy for cross-camera data association

The purpose of this work is the design of a distributed vision system for vehicles tracking over wide areas. The tracking is performed by the re-identification of objects perceived by distant non-overlapping cameras. The data association is controlled by a temporal reasoning scheme. Decisions combine temporal and visual information. The visual information is composed by the 3D dimension and the normalised colour histogram of detected objects. Temporal constraints based on an acceleration model between nodes, are continuously updated with respect to the observed traffic behaviour. These constraints maintain a dynamic lifespan for all tracked objects. The management of the uncertainty represents an important component of the system. Statistical measurements are exploited at the sensor level information and a possibilistic approach permits to manage the ambiguities of the data association stage.

The TerraMax autonomous vehicle

AbstractThe TerraMax vehicle is based on Oshkosh Truck's Medium Tactical Vehicle Replacement truck platform and was one of the five vehicles able to successfully reach the finish line of the 132 miles DARPA Grand Challenge desert race. Due to its size (30 000 pounds, 27′ 0″ long, 8′ 4″ wide, and 8′ 2″ high) and the narrow passages, TerraMax had to travel slowly, but its capabilities demonstrated the maturity of the overall system. Rockwell Collins developed, integrated, and installed the intelligent Vehicle Management System, which includes vehicle sensor management, navigation, and vehicle control systems. The University of Parma provided the vehicle's vision system, while Oshkosh Truck Corp. provided project management, system integration, low level controls hardware, modeling and simulation support, and the vehicle. © 2006 Wiley Periodicals, Inc.

Design, Implementation and Testing of a Vision System for Small Unmanned Vertical Take off and Landing Vehicles with Strict Payload Limitations

Alternative designs of a simple, low cost and effective vision system for small, portable, unmanned aerial vertical take off and landing (VTOL) vehicles are presented. Design configurations follow the `on-board' and `on-the-ground' processing concept and they depend on very strict payload limitations and power supply restrictions. Hardware and software components for both designs are described; advantages and disadvantages of both alternatives are compared; computational complexity is calculated and trade offs are discussed. Implementations on a series of small unmanned VTOL vehicles as well as testing details are included and experimental results are presented.

A 100-GOPS programmable processor for vehicle vision systems

New generations of automobiles will include driver assistance systems requiring powerful, low-cost processors to handle video/camera applications and to enable fast, convenient application development. Shrinking feature sizes on processors already in development will bring substantial increases in system speed and functionality.

A vision sensor having an expanded dynamic range for autonomous vehicles

Insufficiency of dynamic range of conventional video cameras is an important problem in realizing a robust vision system for autonomous vehicles because road scenes have a very wide dynamic range of brightness. To solve the problem, a method for expanding the dynamic range of video cameras by combining the images taken under different exposure conditions has been developed. Using this method, an experimental vision sensor with a wide dynamic range has been manufactured. The developed sensor has a dynamic range of 10 000, which is approximately 30 times as wide as that of a conventional video camera. The effectiveness of the developed vision sensor in comparison with a conventional video camera was confirmed from the experiments on a highway under various lighting conditions.