Effect of Work Zone Lighting on Drivers’ Visual Performance and Perceptions of Glare

Nighttime crashes at work zones are major concerns for construction workers and motorists. Although in a majority of the U.S. states, department of transportation specifications for work zone lighting mention that contractors should reduce glare for workers and drivers, only two states advocate detailed specifications like light positions, orientation, and light levels. Although some studies have examined the impact of glare from work zone lights on workers and others have calculated veiling luminance levels for drivers in the work zone, the effect of work zone lighting on drivers’ visual performance and glare perception has never been studied in a realistic setting. The goal of this study was to understand the impact of commercially available portable light towers (metal halide, LED, and balloon) and their orientation on drivers’ visual performance and their perceptions of glare. Participants drove through a realistic work zone simulated on the Virginia Smart Road. Visual performance was assessed by a detection task and perception of visibility and glare were assessed by questionnaires. Results indicated that the type of light tower and its orientation affect visual performance and perceptions of visibility and glare. Light towers aimed toward the driver resulted in lowering drivers’ visual performance, both objectively and subjectively. When the light towers were aimed away from or perpendicular to the driver, the visual performance was higher and the differences in visual performance between the types of light towers were minimal. These findings indicate that these orientations should be preferred for work zone light towers.

Short Road to Next Ride

This article discusses about the Virginia Smart Road that is frequently used by automobile researchers to test new ideas and concepts. The Virginia Smart Road is a unique, state-of-the-art, closed test-bed research facility managed by the Virginia Tech Transportation Institute and owned and maintained by the Virginia Department of Transportation. Over two-dozen major non-proprietary research projects use the Smart Road for testing in a given year. Participating organizations include heavy hitters such as car manufacturers, the Department of Transportation, the National Highway Traffic Safety Administration, and the Federal Highway Administration’s Research and Innovative Technology Administration. The Smart Road features two paved lanes and three bridges, one of which ranks, at 175 feet, as the tallest state-maintained bridge in Virginia. It also has a signalized intersection; in-pavement sensors for moisture, temperature, strain, vibration, and weighing in motion; a lighting test bed; and the half-mile-long weather-making section. Some other features include an on-site data acquisition system, a high-bandwidth fiber network, a differential global positioning system base station, and traffic signal phase and timing using remote controls.

Relationship Between Backcalculated and Laboratory-Measured Resilient Moduli of Unbound Materials

The resilient moduli of an unbound granular subbase (used at the Virginia Smart Road) obtained from laboratory testing were compared with those backcalculated from in situ falling weight deflectometer deflection measurements. Testing was performed on the surface of the finished subgrade and granular subbase layer shortly after construction. The structural capacity of the constructed subgrade and the depth to a stiff layer were computed for 12 experimental sections. The in situ resilient modulus of the granular subbase layer (21-B) was then back-calculated from the deflections measured on top of that layer. The back-calculated layer moduli were clearly stress-dependent, showing an exponential behavior with the bulk stress in the center of the layer. Resilient modulus test results of laboratory-compacted specimens confirmed the stress dependence of the subbase material modulus. Three resilient modulus models were fitted to the data. Although all three models showed good coefficients of determination ( R2 > 90%), the K-θ model was selected because of its simplicity. The correlation between field-backcalculated and laboratory-measured resilient moduli was found to be strong. However, when the stress in the middle of the layer was used in the K-θ model, a shift in the resilient modulus, θ, was observed. This finding suggests that a simple shift factor could be used for the range of stress values considered.