Journal of Infrastructure Systems

This paper presents a procedure to estimate runway overrun risks of landing aircraft under different combinations of operating factors, including aircraft landing weight, landing speed, landing location, pavement skid resistance, and runway length. The procedure consists of two main parts: determination of braking distance, and calculation of overrun risk. A significant contribution is the determination of available skid resistance as a function of aircraft speed and pavement conditions in the calculation of braking distance. Any aircraft type as well as dimensions of pavement grooves, if present, can be considered. The impacts of low skid resistance on overrun risk, owing to either wet weather conditions, traffic polishing effect on pavement surface texture, or changes of groove dimensions caused by contamination or load-induced deformation, are considered. A demonstrative example is presented to (1) calculate the braking distances of a B777 aircraft for different landing weights, landing speeds, pavement groove dimensions, and pavement skid resistance states; and (2) determine the corresponding overrun risks as a function of aircraft landing speed, landing location, and available runway length. Compared with existing overrun risk prediction methods, the proposed method is unique in that it deterministically considers airport- and runway-related factors in the overrun risk calculation, and it does not require any historical incident and accident data. It estimates aircraft-specific overrun risk for the specific runway analyzed under actual runway operating conditions.

The assessment of bridge settlements is a challenging and significant problem. Moreover, aging of highway bridges is a growing concern in the US, especially when continuous monitoring is lacking. To facilitate expedient monitoring of bridges, this paper presents a projected laser system (PLS) method for monitoring that can autonomously measure and remotely report relative vertical settlements of bridges. The method uses a vision-based measurement system involving the projection of a laser pattern from a laser unit to a target unit. A cost-effective prototype implementing the PLS method was built using low-cost electronic hardware parts. The prototype of the proposed embedded system design was shown to have sub-millimeter accuracy in a laboratory experiment, and was deployed in the field to monitor a pedestrian–vehicle bridge to evaluate its overall performance.

Pavement markings are a key transportation asset and traffic control device that facilitate safe and predictable driving. The effectiveness of pavement markings is dependent on their condition, particularly during nighttime and adverse weather. The Federal Highway Administration (FHWA) has developed regulations to guide minimum pavement marking retroreflectivity levels, which poses a potential challenge to public agencies because the current practice of visual inspection is labor intensive and the results can be subjective. To address the identified challenges and needs of public agencies, the objective of this research is twofold: (1) to serve as a proof of concept for the use of mobile light detection and ranging (LiDAR) to locate and assess the pavement markings for selected testing sections by developing and evaluating new automated LiDAR processing algorithms, and (2) to investigate the feasibility of identifying the deterioration trend of the retroreflectivity condition. This study developed a complete pavement marking inventory with retroreflectivity conditions for the 14 selected testing sections and also compared historical and current data to inform the deterioration trends of three types of marking materials, including polyurea, epoxy, and thermoplastic. The findings of this study will guide future phases with a larger selection of testing sections, material types, and roadway characteristics. The outcomes of the series of studies will help better define the benefit-to-cost ratio for different marking materials and eventually lead to the development of public agencies’ pavement marking standards.

Pavement cracks are a kind of common distress in road service time, and their length measurement is critical for pavement maintenance. The current automatic method of crack length measurement uses segmentation algorithms to obtain crack curves, which is time-consuming and complex. In this study, an effective method of crack length measurement was proposed and validated. The method consists of a detection module based on an object detection algorithm and a length calculation module. To increase the speed and accuracy of crack detection, an improved pavement crack detection algorithm BiFPN-enhanced YOLO V5 (YOLO V5-BiFPN) based on you look only once version 5 (YOLO V5) and bidirectional feature pyramid network (BiFPN) is proposed, and gamma correction was utilized to process pavement images. YOLO V5-BiFPN was tested in a real pavement image data set and achieved remarkable performance. In the length calculation module, the diagonal length of the crack bounding box output by the object detection algorithm can be defined as the crack length. To validate the measurement method, the true value of crack length was obtained from the segmentation data set by skeletonization. The error between the calculation result of the proposed method and the real value is 3.4%, and the average processing time of each image is 14.2 ms. The developed method addresses the problem of considerable time and financial cost associated with the existing crack length measurement methods.