Wheel Path Wandering Based On Field Data

The position and width of wheel path on a pavement lane is an important consideration in conducting pavement distress survey, especially for distinguishing longitudinal cracking from fatigue cracking. Currently, the widely used wheel path definition is derived from the LTPP distress manual with fixed width and position, in which the influence of traffic wander on wheel path was overlooked. This thesis attempts to develop a new wheel path definition based on the lateral placement investigation of heavy vehicles\u27 wandering in the field. Generally, the factors influencing vehicle lateral placement can be divided into seven categories, but only four factors are considered to be the most important in this research: weather, visibility, horizontal curve, and traffic condition. To achieve this goal, a high resolution digital camera mounted on overpass is utilized to acquire lateral placement data under low and heavy traffic condition, during daytime and nighttime, in sunny, rainy, and windy weather, and at five different locations on an interstate highway. Based on the collected data, statistical methods are utilized to investigate the influence of the four factors on the lateral displacement distribution of truck wheels. Herein, the ANalysis Of VAriance (ANOVA) test was applied to rank the effects of four factors on wheel shift, and the Phillips-Perron test (pp.test) was employed to check the stability of data. Subsequently, an approach is proposed to analyze the lateral position data with different parameters. A new analysis model called Multi-Factor Traffic Lateral Position (M-FTLP) is developed in the research to compute the frequency distribution of wheel-path wandering at different deviation levels. The M-FTLP model exploits local information (index weight) to determine lateral distribution of truck positions at a particular location. Based on the frequency distributions of the wandering deviation levels from M-FTLP model, the wheel paths at the five sample road segments are identified

Pavement hydroplaning risk evaluation with Inertial Measurement Unit (IMU) and 1mm 3D texture data

During wet weather automobiles traveling on pavements may experience hydroplaning that would cause out-of-control accidents. Annually 14% of all accidents with fatalities occur on wet pavements. However, not many studies have been conducted on identifying pavement sections with hydroplaning risks for pavement safety survey purpose. This is primarily due to two facts: 1) that it is difficult to acquire the high-quality texture and geometry data which serve as basis data for hydroplaning study; 2) that the existing hydroplaning speed prediction models may not be applicable on irregular pavement sections e.g. pavements with large slopes or long rutting track. To overcome these limitations, in this study PaveVision3D Ultra is used to collect 1mm 3D texture data with full lane coverage at highway speed. Inertial Measurement Unit (IMU) system is used to measure the geometry feature of pavements such as cross slope and longitudinal grade. ANalysis Of VAriance (ANOVA) test results indicated the collected texture data have good reliabilities if the data collection is conducted at a constant speed, while IMU data have the good repeatability regardless of data collection speed. Subsequently the existing prediction models are evaluated by validating the predicted water film depth (WFD) and hydroplaning speed with the measured values from eTape liquid level sensor and Dynamic Friction Tester (DFT). Results indicate the predicted values from Gallaway and University of South Florida (USF) models have good agreements with the ground truth. However, the two models only functions well on regular pavement. For pavements with large slopes or long rutting track, the models might work properly since effects of large slope and rutting on hydroplaning are not considered. In this study impacts of large slopes on vertical load are considered and incorporated the existing models. A new model named as 3S-WFD model is developed in the research to estimate water film depth of rutting pavement under three scenarios. Finally case studies are provided for hydroplaning evaluation on regular pavements, large sloping pavements, and rutting pavements, respectively. Results indicate the data and models used in this study can efficiently identify pavement segments with potential hydroplaning risks so that pavement engineers can take remedial measures to minimize potential traffic accidents. The methodologies proposed in the research would be beneficial in complementing the network level pavement safety survey by highway agencies

A Study on the Curriculum Setting and Characteristics of the Undergraduate Philosophy Major at Oxford University

The philosophy faculty at Oxford University is ancient and stately, with profound cultural background and a good tradition of philosophical concept of education and training target, which influences the philosophical education in Britain and even in the whole world. By cultivating the students’ ability of reading, logical thinking and critical thinking, it encourages students to correctly understand the world and use the knowledge effectively to solve various practical problems. This article tries to sort out the development of undergraduates’ education of philosophy at Oxford University, to analyze the curriculum setting of philosophy in the latest ten years, and to summarize the characteristics of philosophy education

In Vivo Molecular Imaging in Retinal Disease

There is an urgent need for early diagnosis in medicine, whereupon effective treatments could prevent irreversible tissue damage. The special structure of the eye provides a unique opportunity for noninvasive light-based imaging of ocular fundus vasculature. To detect endothelial injury at the early and reversible stage of adhesion molecule upregulation, some novel imaging agents that target retinal endothelial molecules were generated. In vivo molecular imaging has a great potential to impact medicine by detecting diseases or screening disease in early stages, identifying extent of disease, selecting disease and patient-specific therapeutic treatment, applying a directed or targeted therapy, and measuring molecular-specific effects of treatment. Current preclinical findings and advances in instrumentation such as endoscopes and microcatheters suggest that these molecular imaging modalities have numerous clinical applications and will be translated into clinical use in the near future

Pavement Friction Estimation Based on the Heinrich/Klüppel Model

Tire-pavement interaction is a critical analysis for conducting friction measurements and safety evaluation on highway pavements. Substantial field studies and research efforts indicate pavement friction can be predicted with tire/texture-related models (e.g. empirical or analytical models); however, developing a reliable friction prediction model for network level pavement survey still remains a challenge. In this paper Heinrich/Klüppel friction prediction model is utilized to estimate friction on Asphalt Concrete (AC) pavements. High resolution texture data are acquired from Ames high-speed profiling system, and subsequently pavement friction data are collected on the same sections with Dynatest 6875 Highway friction tester. Findings from the study indicate a good agreement between the predicted and measured Friction Numbers (FNs). It is concluded that Heinrich/Klüppel friction theory can be used as a promising surrogate for pavement safety evaluation. This study would be beneficial for complementing the existing safety evaluation methods used in highway safety program

Compact-Size Low-Profile Wideband Circularly Polarized Omnidirectional Patch Antenna With Reconfigurable Polarizations

A compact-size low-profile wideband circularly polarized (CP) omnidirectional antenna with reconfigurable polarizations is presented in this communication. This design is based on a low-profile omnidirectional CP antenna which consists of a vertically polarized microstrip patch antenna working in TM01/TM02 modes and sequentially bended slots etched on the ground plane for radiating horizontally polarized electric field. The combined radiation from both the microstrip patch and the slots leads to a CP omnidirectional radiation pattern. The polarization reconfigurability is realized by introducing PIN diodes on the slots. By electronically controlling the states of the PIN diodes, the effective orientation of the slots on ground plane can be changed dynamically and the polarization of antenna can be altered between left-hand circular polarization (LHCP) and right-hand circular polarization (RHCP). The proposed antenna exhibits a wide-operational bandwidth of 19.8% (2.09-2.55 GHz) with both axial ratio below 3 dB and return loss above 10 dB when radiates either LHCP or RHCP waves. Experimental results show good agreement with the simulation results. The present design has a compact size, a thickness of only 0.024? and exhibits stable CP omnidirectional conical-beam radiation patterns within the entire operating frequency band with good circular polarization

Impacts of Sample Size on Calculation of Pavement Texture Indicators with 1mm 3D Surface Data

The emerging 1mm resolution 3D data collection technology is capable of covering the entire pavement surface, and provides more data sets than traditional line-of-sight data collection systems. As a result, quantifying the impact of sample size including sample width and sample length on the calculation of pavement texture indicators is becoming possible. In this study, 1mm 3D texture data are collected and processed at seven test sites using the PaveVision3D Ultra system. Analysis of Variance (ANOVA) test and linear regression models are developed to investigate various sample length and width on the calculation of three widely used texture indicators: Mean Profile Depth (MPD), Mean Texture Depth (MTD) and Power Spectra Density (PSD). Since the current ASTM standards and other procedures cannot be directly applied to 3D surface for production due to a lack of definitions, the results from this research are beneficial in the process to standardize texture indicators’ computations with 1mm 3D surface data of pavements

Trichoderma reesei FS10-C enhances phytoremediation of Cd-contaminated soil by Sedum plumbizincicola and associated soil microbial activities

This study aimed to explore the effects of Trichoderma reesei FS10-C on the phytoremediation of Cd-contaminated soil by Sedum plumbizincicola as well as soil fertility. After characterizing the Cd tolerance of T. reesei FS10-C, a pot experiment was carried out to investigate the plant growth and Cd uptake of S. plumbizincicola with the addition of inoculation agents with/without T. reesei FS10-C. The soil samples in pots were analyzed for pH, available phosphorus (P), microbial biomass C, enzyme activities, microbial community functional diversity and Trichoderma colonization ability. The results indicated that FS10-C possessed high Cd resistance up to 300 mg L-1. All inoculation agents enhanced the biomass of plant shoots by 6-53% fresh weight and 16-61% dry weight as well as Cd uptake in plant shoots by 10-53% compared with the control. In addition, soil biomass C, enzyme activities and microbial community evenness were all increased to varying degrees by all inoculation agents, indicating that soil microbial biomass and activities were both enhanced. It was also found that the two inoculation agents accompanied by FS10-C were better compared with the inoculation agents without FS10-C on all accounts, from which it could be concluded that T. reesei FS10-C was effective in improving Cd phytoremediation of S. plumbizincicola and soil fertility. Furthermore, among all the inoculation agents, solid fermentation powder of FS10-C demonstrated the greatest capacity to enhance plant growth, Cd uptake, nutrient release, and microbial biomass and activities, as indicated by its superior ability to colonize Trichoderma. Thus, we could also conclude that solid fermentation powder of FS10-C was a good candidate for use as an inoculation agent for T. reesei FS10-C to improve the phytoremediation of Cd-contaminated soil and soil fertility

Transfer Learning Based Traffic Sign Recognition Using Inception-v3 Model

Traffic sign recognition is critical for advanced driver assistant system and road infrastructure survey. Traditional traffic sign recognition algorithms can't efficiently recognize traffic signs due to its limitation, yet deep learning-based technique requires huge amount of training data before its use, which is time consuming and labor intensive. In this study, transfer learning-based method is introduced for traffic sign recognition and classification, which significantly reduces the amount of training data and alleviates computation expense using Inception-v3 model. In our experiment, Belgium Traffic Sign Database is chosen and augmented by data pre-processing technique. Subsequently the layer-wise features extracted using different convolution and pooling operations are compared and analyzed. Finally transfer learning-based model is repetitively retrained several times with fine-tuning parameters at different learning rate, and excellent reliability and repeatability are observed based on statistical analysis. The results show that transfer learning model can achieve a high-level recognition performance in traffic sign recognition, which is up to 99.18 % of recognition accuracy at 0.05 learning rate (average accuracy of 99.09 %). This study would be beneficial in other traffic infrastructure recognition such as road lane marking and roadside protection facilities, and so on

Lane Marking Detection and Reconstruction with Line-Scan Imaging Data

Lane marking detection and localization are crucial for autonomous driving and lane-based pavement surveys. Numerous studies have been done to detect and locate lane markings with the purpose of advanced driver assistance systems, in which image data are usually captured by vision-based cameras. However, a limited number of studies have been done to identify lane markings using high-resolution laser images for road condition evaluation. In this study, the laser images are acquired with a digital highway data vehicle (DHDV). Subsequently, a novel methodology is presented for the automated lane marking identification and reconstruction, and is implemented in four phases: (1) binarization of the laser images with a new threshold method (multi-box segmentation based threshold method); (2) determination of candidate lane markings with closing operations and a marching square algorithm; (3) identification of true lane marking by eliminating false positives (FPs) using a linear support vector machine method; and (4) reconstruction of the damaged and dash lane marking segments to form a continuous lane marking based on the geometry features such as adjacent lane marking location and lane width. Finally, a case study is given to validate effects of the novel methodology. The findings indicate the new strategy is robust in image binarization and lane marking localization. This study would be beneficial in road lane-based pavement condition evaluation such as lane-based rutting measurement and crack classification. Document type: Articl