Mobile Standards-Based Traffic Light Detection in Assistive Devices for Individuals with Color-Vision Deficiency

Considering the substantial population affected by some form of color-vision deficiency (CVD), reliable traffic control signal head light detection is an important problem for driver-assistance systems. While a large number of technologies can be used to localize traffic lights, without drastic changes in infrastructure, only visual information can be used in identifying the status of the light. In addition, traffic light detection is not currently integrated into any driver-assistance systems, making driving for individuals with CVD (where permitted) dangerous to other drivers, pedestrians, and themselves. This paper presents a robust, traffic-standards-based, and computationally efficient method for detecting the status of the traffic lights without relying on Global Positioning System, lidar, radar information, or prior (map-based) knowledge.

To the extent of our knowledge, this is the first work to use official Institute of Transportation Engineers (U.S.) and British Standards Institute (European Union) standards for defining traffic light colors, as well as integrating a number of fail-safe mechanisms designed to prevent erroneous detection. The algorithm can be easily ported over to an embedded smart camera platform and used as a windshield-mounted driver-assistance device by individuals with CVD. The system can accurately identify the status of the light at 400 ft away from the intersection, reliably detecting solid, faulty, arrow, and high-visibility signal lights. Over 50 h of video (over 2000 intersections) were tested with the system, containing intersections with one to four traffic lights, governing different lanes of traffic, with 97.5% accuracy of solid light detection.

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