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Ensuring adequate pavement cross-slope on highways can improve driver safety by reducing the potential for ponding to occur or vehicles to hydroplane. Mobile laser scanning (MLS) systems provide a rapid, continuous, and cost-effective means of collecting accurate 3D coordinate data along a corridor in the form of a point cloud. This study provides an evaluation of MLS systems in terms of the accuracy and precision of collected cross-slope data and documentation of procedures needed to calibrate, collect, and process this data. Mobile light detection and ranging (LiDAR) data were collected by five different vendors on three roadway sections. The results indicate the difference between ground control adjusted and unadjusted LiDAR derived cross-slopes, and field surveying measurements less than 0.19% at a 95% confidence level. The unadjusted LiDAR data incorporated corrections from an integrated inertial measurement unit and high-accuracy real-time kinematic GPS, however it was not post-processed adjusted with ground control points. This level of accuracy meets suggested cross-slope accuracies for mobile measurements (±0.2%) and demonstrates that mobile LiDAR is a reliable method for cross-slope verification. Performing cross-slope verification can ensure existing pavement meets minimum cross-slope requirements, and conversely is useful in identifying roadway sections that do not meet minimum standards, which is more desirable than through crash reconnaissance where hydroplaning was evident. Adoption of MLS would enable the South Carolina Department of Transportation (SCDOT) to address cross-slope issues through efficient and accurate data collection methods.

Abstract.In this paper, to analyze the Jointed Plain Concrete Pavement (JPCP), a 3-D dynamic model of the pavement was modeled using ABAQUS. Moving load with different speed and interaction between the Dowel bar and concrete has been considered in this research. The output for the strain in the joints has been validated with accurate experimental results. Research has shown that the finite element analysis, is an accurate and efficient method to model the interaction between the dowel bar and surrounding concrete. The results showed that with increasing the speed of moving load, the maximum strain in joints decreases. Such reduction is about 18 % for the 20 ton axial load and the speed of 120 km/hr. relative to the speed of 32 km/hr. In addition, with increasing the axial load, the maximum strain in the joints increases. This increase is more for the lower speeds. In addition, it is found that decreasing the loading speed and increasing the axial load will result in increasing the maximum strain and maximum stress in the connected area of dowel bar and surrounding concrete. Thus it may become more than the ultimate tensile strength and result in initiate cracking in the tensile area of concrete slab, especially in the joints. Furthermore, the results showed that changing the mechanical specification of concrete would not significantly affect the maximum strain in the JPCP, which using C50 instead of C25, the maximum strain would increase about 10 %. However, the mechanical specification of JPCP could affect the cracking propagation and concrete durability.

The AASHTO Highway Safety Manual (HSM) presents a variety of methods for quantitatively estimating crash frequency or severity at a variety of locations. The HSM predictive methods require the roadway network to be divided into homogeneous segments and intersections, or sites populated with a series of attributes. It recommends a minimum segment length of 0.1 mi. This research focuses on segment lengths of less than 0.1 mi for statewide screening of midblock crash locations to identify site specific locations with high crash incidence. The paper makes an argument that many midblock crashes can be concentrated along a very short segment because of an undesirable characteristic of a specific site. The use of longer segments may “hide” the severity of a single location if the rest of the segment has few or no additional crashes. In actuality, this research does not divide sections of roads into short segments. Instead, a short-window approach is used. The underlying road network is used to create a layer of segment polygons using GIS buffering. Crash data are then overlaid and aggregated to the segment polygons for further analysis. The paper makes a case for the use of short fixed segments to do statewide screening and how accurately geocoded crash data is key to its use. A comparison is made with a sliding-window approach (Network Kernel Density). The benefit of using fixed segments is that they are much less complex than using the sliding-window approach. Because the segmentation can be the same from year to year, direct comparisons can be made over time while spatial integrity is maintained.

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