2,563 research outputs found

    Cost Estimate Modeling of Transportation Management Plans for Highway Projects, Research Report 11-24

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    Highway rehabilitation and reconstruction projects frequently cause road congestion and increase safety concerns while limiting access for road users. State Transportation Agencies (STAs) are challenged to find safer and more efficient ways to renew deteriorating roadways in urban areas. To better address the work zone issues, the Federal Highway Administration published updates to the Work Zone Safety and Mobility Rule. All state and local governments receiving federal aid funding were required to comply with the provisions of the rule no later than October 12, 2007. One of the rule’s major elements is to develop and implement Transportation Management Plans (TMPs). Using well-developed TMP strategies, work zone safety and mobility can be enhanced while road user costs can be minimized. The cost of a TMP for a road project is generally considered a high-cost item and, therefore, must be quantified. However, no tools or systematic modeling methods are available to assist agency engineers with TMP cost estimating. This research included reviewing TMP reports for recent Caltrans projects regarding state-of-the-art TMP practices and input from the district TMP traffic engineers. The researchers collected Caltrans highway project data regarding TMP cost estimating. Then, using Construction Analysis for Pavement Rehabilitation Strategies (CA4PRS) software, the researchers performed case studies. Based on the CA4PRS outcomes of the case studies, a TMP strategy selection and cost estimate (STELCE) model for Caltrans highway projects was proposed. To validate the proposed model, the research demonstrated an application for selecting TMP strategies and estimating TMP costs. Regarding the model’s limitation, the proposed TMP STELCE model was developed based on Caltrans TMP practices and strategies. Therefore, other STAs might require adjustments and modifications, reflecting their TMP processes, before adopting this model. Finally, the authors recommended that a more detailed step-by-step TMP strategy selection and cost estimate process be included in the TMP guidelines to improve the accuracy of TMP cost estimates

    Real-Time Fatigue Analysis of Driver through Iris Recognition

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    In recent days, the driver’s fault accounted for about 77.5% of the total road accidents that are happening every day. There are several methods for the driver’s fatigue detection. These are based on the movement of the eye ball using eye blinking sensor, heart beat measurement using Electro Cardio Gram, mental status analysis using ElectroEncephaloGram, muscle cramping detection, etc. However the above said methods are more complicated and create inconvenience for the driver to drive the vehicle. Also, these methods are less accurate. In this work, an accurate method is adopted to detect the driver’s fatigue based on status of the eyes using Iris recognition and the results shows that the proposed method is more accurate (about 80%) compared to the existing methods such as Eye blink Sensor method

    Permanent Concrete Pavement Markings

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    The visibility, durability, and cost-effectiveness of surface pavement markings and previous experience with permanent concrete pavement markings (PCPM) (markings with a service life similar to that of the pavement) are described. The use of durable materials, such as thermoplastics, polyesters, and epoxies, improves the service life of surface markings. However, these marking materials still exhibit problems of adhesion to pavement and rapid wear in high traffic areas. Snow removal procedures significantly reduce marking service life. Wet nighttime visibility is a continuing problem with surface markings. Previous attempts at developing PCPM have produced systems with very good durability, but poor nighttime visibility. The potential for developing cost-effective PCPM systems that can provide both long-term durability and adequate visibility throughout the service life and the requirements for such systems are discussed. Polymers, such as epoxies, can provide superior durability and adhesion to pavement. The application of larger than standard size glass beads can improve wet nighttime visibility. The cost of PCPM systems can be significantly reduced using effective methods of placing grooves in which the marking material is placed. Generally, there is a good probability that a cost-effective PCPM system with satisfactory durability and visibility can be developed. The PCPM systems with thicknesses of 9.5 mm (3/8 in.) or less will be cost-effective for a 20- year service life, and the systems with thicknesses of 3.2 mm (1/8 in.) or less will be costeffective for a I 0-year service life

    The State-of-the-Art Review on Applications of Intrusive Sensing, Image Processing Techniques, and Machine Learning Methods in Pavement Monitoring and Analysis

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    In modern transportation, pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians. Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users. Therefore, monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance, which in turn ensures public transportation safety. Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions. Advanced technologies can be employed for the collection and analysis of such data, including various intrusive sensing techniques, image processing techniques, and machine learning methods. This review summarizes the state-of-the-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches

    Video based vehicle detection for advance warning Intelligent Transportation System

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    Video based vehicle detection and surveillance technologies are an integral part of Intelligent Transportation System (ITS), due to its non-intrusiveness and capability or capturing global and specific vehicle behavior data. The initial goal of this thesis is to develop an efficient advance warning ITS system for detection of congestion at work zones and special events based on video detection. The goals accomplished by this thesis are: (1) successfully developed the advance warning ITS system using off-the-shelf components and, (2) Develop and evaluate an improved vehicle detection and tracking algorithm. The advance warning ITS system developed includes many off-the-shelf equipments like Autoscope (video based vehicle detector), Digital Video Recorders, RF transceivers, high gain Yagi antennas, variable message signs and interface processors. The video based detection system used requires calibration and fine tuning of configuration parameters for accurate results. Therefore, an in-house video based vehicle detection system was developed using the Corner Harris algorithm to eliminate the need of complex calibration and contrasts modifications. The algorithm was implemented using OpenCV library on a Arcom\u27s Olympus Windows XP Embedded development kit running WinXPE operating system. The algorithm performance is for accuracy in vehicle speed and count is evaluated. The performance of the proposed algorithm is equivalent or better to the Autoscope system without any modifications to calibration and lamination adjustments

    Smart Technical Textiles Based on Fiber Optic Sensors

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    Abstracts of the Second Urban Sound Symposium

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    Following the successful first Urban Sound Symposium held at Ghent University in 2019, the second edition in 2021 had to face the challenges of the pandemic. The symposium turned this challenge into an opportunity for giving easier access to practitioners and experts from around the globe who are confronted with urban sound in their professional activities. It was organized simultaneously in Ghent, Montreal, Nantes, Zurich, London and Berlin by researchers at Ghent University, Mc Gill University, Université Gustave Eiffel, EMPA, University College London and TU Berlin. The online event created opportunities for interaction between participants at poster-booths, virtual coffee tables, and included social activities
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