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Proceedings Paper

Assessment of driver vision enhancement technologies
Author(s): Louis J. Denes; Richard Grace; David A. Purta; Alberto M. Guzman
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Paper Abstract

Driver vision enhancement systems provide augmented information to improve the driver's perceptual ability when visibility is reduced. Vision enhancement is a technologically- challenging mission. We surveyed two classes of technologies: imaging systems (visible and infrared) and radars (millimeter-wave and laser radars). Night (IR) vision and radar-based systems promise meaningful vision enhancement functionality to the driver. Available field test data give thermal imagers operating in the range of 8 to 12 micrometers an edge. This spectral regime has a long (miles) clear night range, adequate object discrimination and handles inclement weather conditions better than other shorter wavelength imagers. Uncooled thermal imagers, because of their potentially low-cost, are emerging as a front runner technology. All weather penetration of a radar based system is attractive for certain driving scenarios. They are not particularly adept in high resolution imaging. This combination makes them more of interest as automated warning devices. Icons replace the actual objects imaged to indicate the hazard ahead. True all-weather high-resolution vision enhancement systems are beyond near- term capabilities. Overall, vision enhancement systems under development today will have good utility with the challenge that they become `affordable'.

Paper Details

Date Published: 27 December 1995
PDF: 12 pages
Proc. SPIE 2592, Collision Avoidance and Automated Traffic Management Sensors, (27 December 1995); doi: 10.1117/12.228917
Show Author Affiliations
Louis J. Denes, Carnegie Mellon Research Institute (United States)
Richard Grace, Carnegie Mellon Research Institute (United States)
David A. Purta, Carnegie Mellon Research Institute (United States)
Alberto M. Guzman, Carnegie Mellon Research Institute (United States)

Published in SPIE Proceedings Vol. 2592:
Collision Avoidance and Automated Traffic Management Sensors
Alan C. Chachich; Marten J. de Vries, Editor(s)

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