Advances in machine vision techniques have led to algorithms and integrated systems that can be applied in transportation engineering to improve surveillance and control. Despite these advances, certain problems in the effective integration of machine-vision based systems at complex intersections and complex freeway sections still remain. These are related to increasing system performance in the identification, analysis, and detection of the traffic state in real time. This work examines the feasibility of providing transformed visual input to existing machine-vision based systems, in order to gain increased efficiency and cost effectiveness of integrated transportation systems. Two transformations are developed, homography-based transformation and panoramic image reprojection. Homography-based transformation operates on video of the road scene, provided by classical cameras, and seeks to transform any view to a top-down view. This transforms the three-dimensional problem of image analysis for, e.g., road event detection to a two-dimensional one. Panoramic image reprojection employs panoramic cameras to reduce required hardware, and the complexity and cost incurred in obtaining the desired road view. The image reprojection technique allows the reconstruction of undistorted, perspectively correct views from panoramic images in real time. Tests at sites in Spain, the United Kingdom, and Greece are performed on-line and off-line in combination with operating machine-vision based incident detection systems. Test results indicate that the two methods simplify the input provided to machine vision, and reduce the workload and amount of hardware in implementing complex machine-vision based systems for incident detection. Both modules can be integrated into incident detection systems to improve their overall efficiency and ease of application.

This paper describes a new sampling approach to collect driving data. Traditional data collection assesses the percentage of vehicle miles traveled by road facility and time of day, and collects data in proportion to how real-world driving occurs. While the traditional approach is reasonable, it would be better to establish statistical targets. Statistical targets minimize uncertainties about how well data represent real-world driving and allow confidence levels to be computed. We illustrate statistical sampling with a California study that collected over $180\mathrm{h}$ of driving data. Road load power (RLP) was estimated based on speeds and accelerations and used as a surrogate for emissions-producing behavior. The variance of RLP (RPV) was used to establish statistical targets. The new method facilitated fine-tuned data collection by facility and time of day. The research team estimated, at a 90% confidence interval, that mean RVP was within $\pm 11$ to $\pm 23\%$ of the true mean among facilities studied. The method ensured that key facilities were adequately represented, thus providing a data resource to build facility-specific emissions tools.

The writers claim that the process of pedestrians’ entry to the signal-controlled crosswalk can affect the values of pedestrian delays. The existing models have been based on some typical situations and would not always consider the character of pedestrians’ entry process. The use of these models for crosswalks where pedestrians’ entry process is not uniform can lead to inaccurate estimation of pedestrian delays. A number of measurements have been carried out, recording the entry process and the delays. The delay values estimated using the existing models have been compared with the values from field measurements. The comparison has proved that there are situations in which the existing models do not provide accurate estimation of delays. Therefore, three new delay estimation models have been proposed. They differ in the degree of accuracy and complexity as well as practical utility. The results obtained using the new models have been compared with the results of field measurements. At the end of the paper the sensitivity of all the models to the selected parameters has been analyzed. Finally, a conclusion and evaluation of the whole research close this paper.

In recent years, there has been a movement in local government regulations toward restricting the mounting height of on-premise, commercial signing and other roadside oriented signs. This has caused some concern among sign designers and fabricators that automobile drivers will have difficulty in seeing and reading many of these low profile signs. These potential visibility difficulties are caused by the presence of other vehicles; either those in front of the subject vehicle, those in the adjacent travel lane, or those traveling in the opposite direction; blocking the line of sight between the subject vehicle driver and any low-mounted, roadside sign. The objective of this research was to determine the probability of another automobile blocking the line of sight between the driver of a subject vehicle and an on-premise, low-mounted, roadside sign. The results indicated that this probability is a function of the position of the subject vehicle, the position(s) of one or more object vehicles, the volume of vehicles on the road, and the speed of the vehicles on the road.

This paper presents an objective approach for establishing similarities in vehicle classification and axle load distributions between traffic data collection sites. It is based on clustering techniques that identify in succession groups of sites of decreasing similarity on the basis of the attributes specified (e.g., either the percentage of vehicles by class or the percentage of axles by load interval, respectively). This method is implemented in identifying clusters of sites with similar vehicle class distribution and axle load distributions, respectively. Extended coverage weigh-in-motion data (i.e., more than $299\text{days}∕\text{year}$ ) from the long-term pavement performance database was used for this purpose. These data included 178 sites distributed through seven states. The paper explains the clustering methodology for one of these states and presents the clustering results for all seven states. This methodology allows estimation of traffic input to the new mechanistic-empirical pavement design guide from limited site-specific traffic data.

The objective of this research is to evaluate how the physical properties and thickness of asphalt pavements influence behaviors of ultra thin whitetopping (UTW). The results of the three-dimensional finite-element method reveal that properties of asphalt and concrete layers, bonding between the two layers, and temperature strongly affect the distress of UTW. Based on results of FEM analysis, a wheel tracking device called the “heart wheel load simulator (HWLS)” was developed and used to perform an experiment to observe behavior variation in accordance with asphalt and concrete layer thicknesses as well as temperature. The results of HWLS simulation show that the effect of temperature is not significant and the increase of the tensile strain with the increase of a load is relatively small for a $100\mathrm{mm}$ concrete layer, as compared to a $50\mathrm{mm}$ concrete layer. In addition, for a $50\mathrm{mm}$ concrete layer with a less than $150\mathrm{mm}$ asphalt layer, the increased ratio of the tensile strain at the bottom of the concrete slab is significantly higher. Therefore, this research recommends that an at least $150\mathrm{mm}$ asphalt layer after milling be required in order to apply UTW safely.

The Federal Aviation Administration’s National Airport Pavement Test Facility (NAPTF) was constructed to generate high-quality, full-scale accelerated test data from pavements subjected to dynamic simulated heavy aircraft traffic. During the first round of testing, the flexible pavement sections were subjected to dual-tridem Boeing 777 gear and dual-tandem Boeing 747 gear trafficking to study and compare their effect on pavement structural responses and rutting performance. This paper presents the results from traffic testing on a low-strength subgrade flexible pavement section with a substantially thick unbound granular subbase layer. Data from in situ instrumentation and heavy weight deflectometer (HWD) testing were analyzed at different stages of trafficking to evaluate the pavement structural deterioration imposed by the test gears. At the end of traffic testing, posttraffic forensic investigation studies were conducted to investigate the failure mechanism of pavement structures. The results showed that the maximum HWD deflections $\left(D_0\right)$ , the backcalculated moduli, and the mean rut depths were similar for both test gears throughout the traffic testing. Some correlation may exist between percentage $D_0$ change and the accumulated rutting.

Thermoplastic pipes with a wide variety of wall geometries have been developed to obtain higher stiffness with utilization of less pipe material. The geometries of these profiles induce local bending, which may influence their structural performance. The localized deformations are investigated here for a range of commonly used pipe profiles using three-dimensional finite-element analysis. The study revealed that local bending governs the wall strains in some profiles. Among the three profile types considered, the effect of local bending was the greatest in the lined corrugated profiles. Circumferential strain distributions in the boxed and tubular profiles were almost uniform along the pipe axis, though axial and radial stress and strain indicated that these profiles also experienced local bending. While finite-element analysis using an axisymmetric idealization of the profiles appeared successful in capturing most of the characteristics of the three-dimensional profile response, certain aspects for the helically wound boxed profile were not captured well using this approach.

The impact of left turns on operation is probably the most significant factor in the performance of conventional intersections. As a result engineers have looked to alternative measures for dealing with left turns at intersections to improve performance, some of which have been unconventional schemes. The purpose of this paper is to discuss an unconventional intersection scheme, the upstream signalized crossover (USC), which is a four-legged intersection designed to eliminate left turn opposing conflicts by crossing the left and through traffic to the left side of the road at all four approaches prior to the intersection. The crisscrossing of traffic upstream of the intersection results in four additional secondary signalized intersections. VISSIM was used to model and analyze the unconventional USC intersection as well as a conventional intersection for comparison. The analysis revealed that the USC intersection can handle higher traffic volumes at reduced overall delays. In terms of left turn delay, the conventional intersection performed better at lower volumes. However, the USC was able to handle much higher left turn volumes while maintaining acceptable level of delay. In terms of through movement delay, the USC intersection was found to perform significantly better than the conventional intersection.