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Rapid proliferation of small, unmanned aircraft systems (UAS) promises to revolutionize traditional methods used to carry out civil engineering surveys and analyses and conduct physical infrastructure inspections. One of the most promising areas of implementation of innovative UAS technology includes the integration of UAS into current state Department of Transportation (DOT) bridge inspections. While regular bridge inspections are paramount for road user safety, many traditional inspection methods and procedures are cumbersome, expensive, and time consuming; present significant hazards to both the traveling public and the inspection personnel; and are disruptive to normal operations of the transportation facilities. The results of recent studies indicate that UAS can serve as a useful tool in many highway bridge inspection procedures, while significantly reducing costs and time and improving safety. The major factors that affect the success of integrating UAS into the bridge inspection process relate to selection of the proper types of UAS platforms and avionics, data collection sensors and processing software, as well as conduct of task-specific pilot training. The paper provides an examination of current standard bridge inspection procedures and protocols currently carried out by state DOTs; an evaluation of state DOT experiences with the integration of UAS technology into bridge inspections; and an assessment of the issues and challenges associated with this technology. It is expected that this paper will be of interest to a wide range of stakeholders representing state and federal governments, academia, and industry.

The ability of an automated license plate reading (ALPR) system to convert video images of license plates into computer records depends on many factors. Of these, two are readily controlled by the operator: the quality of the video images captured in the field and the internal settings of the ALPR used to transcribe these images. A third factor, the light conditions under which the license plate images are acquired, is less easily managed, especially when camcorders are used in the field under ambient light conditions. A set of experiments was conducted to test the effects of ambient light conditions, video camcorder adjustments, and internal ALPR settings on the percent of correct reads attained by a specific type of ALPR, one whose optical character recognition process is based on template matching. Images of rear license plates were collected under four ambient light conditions: overcast with no shadows, and full sunlight with the sun in front of the camcorder, behind the camcorder, and orthogonal to the line of sight. Three camcorder exposure settings were tested. Two of the settings made use of the camcorder’s internal light meter, and the third relied solely on operator judgment. The license plates read ranged from 41% to 72%, depending most strongly on ambient light conditions. In all cases, careful adjustment of the ALPR led to significantly improved read rates over those obtained by using the manufacturer’s recommended default settings. Exposure settings based on the operator’s judgment worked best in all instances.

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