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  • Mobility and traffic research  (16)
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  • Mobility and traffic research  (16)
  • 1
    Online Resource
    Online Resource
    Viscosity Evaluation Index of Hot-Applied Sealant for Asphalt Pavement
    SAGE Publications ; 2015
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2481, No. 1 ( 2015-01), p. 83-89
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2481, No. 1 ( 2015-01), p. 83-89
    Abstract: The relationship of viscosity to temperature is one of the most important factors in the application of hot-applied sealants. However, the present evaluation system cannot fully reflect the field performance of the sealants, given the lack of consideration of application conditions. A rotational viscometer and Rotor SC4-27 were used in this study to test the viscosity of hot-applied sealants, with viscosity at 50% torsional moment taken as the apparent viscosity. Nine kinds of sealants were tested in the temperature range of 160°C to 200°C. Analysis also was conducted to evaluate the correlation of the viscosity index with other indexes. The results showed no obvious correlation between them. Thus the viscosity index proposed in this study could be included in the present evaluation system in which the recommended pour temperature is 190°C, and the rotational viscosity is in the range of 1 to 3 Pa-s.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2481-11
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2015
    detail.hit.zdb_id: 2403378-9
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  • 2
    Online Resource
    Online Resource
    Use of Markov Chain Model Based on Actual Repair Status to Predict Bridge Deterioration in Shanghai, China
    SAGE Publications ; 2016
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2550, No. 1 ( 2016-01), p. 106-114
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2550, No. 1 ( 2016-01), p. 106-114
    Abstract: Bridge condition prediction is crucial in preparing conservation budgets for the maintenance of bridges. A bridge management system has been formally used and promoted for urban bridge management in Shanghai, China, since 2004, and 16,623 bridge records have been accumulated. Although there are many data records, predicting bridge deterioration precisely is difficult because the data composition is complicated and the maintenance history is varied. Therefore a Markov chain model was applied as a decision aid to consider the different conservation strategies. More than 66,000 data records were used to calibrate the model. The modeling considered two conservation regimes: ( a) routine maintenance and minor repair and ( b) medium and major repair. The repair rate was obtained through an actual conservation survey. The influence of spatial distribution was also considered. Bridge conservation efforts were uneven at the city level. The condition of bridges in the central city is much better than that of those in suburban areas, although the proportion (55.6%, 2014) of suburban bridges is larger. Furthermore, based on the present status of bridges, conservation efforts have been insufficient generally and even worse in suburban areas. The medium and major repair levels have had a significant impact on deck systems and superstructure but quite a small impact on substructure and the whole bridge. Thus the present conservation efforts cannot improve the overall bridge condition fundamentally. As a result, the condition of bridges in Shanghai has deteriorated rapidly.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2550-14
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2016
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  • 3
    Online Resource
    Online Resource
    Evaluation of Ballast Behavior under Different Tie Support Conditions using Discrete Element Modeling
    SAGE Publications ; 2018
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2672, No. 10 ( 2018-12), p. 106-115
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2672, No. 10 ( 2018-12), p. 106-115
    Abstract: This paper presents findings of a railroad ballast study using the discrete element method (DEM) focused on mesoscale performance modeling of ballast layer under different tie support conditions. The simulation assembles ballast gradation that met the requirements of both American Railway Engineering and Maintenance-of-Way Association (AREMA) No. 3 and No. 4A specifications with polyhedral particle shapes created similar to the field-collected ballast samples. A full-track model was generated as a basic model, on which five different support conditions were studied in the DEM simulation. Static rail seat loads of 10 kips (44.5 kN) were applied until the DEM model became stable. The pressure distribution along the tie-ballast interface predicted by DEM simulations was in good agreement with previously published results backcalculated from laboratory testing. Static rail seat loads of 20 kips (89 kN) were then applied in the calibrated DEM model to evaluate in-track performance. Results from the validated full-track DEM simulations indicated that only a small portion of ballast particles participated in load distribution under static loading. Particles on the shoulders and particles in the areas with poor support conditions often experience no or very low contact forces. Load transfer mechanisms investigated through a contact force network varied greatly among different support conditions: lack of rail seat support, full support, and lack of center support had wider force distribution angles than the high center binding and severe center binding conditions. The severe center binding scenario was found to be the most critical support condition in terms of causing the highest tie-ballast contact pressure exceeding 30% of the AREMA allowable pressure.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/0361198118790643
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2018
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  • 4
    Online Resource
    Online Resource
    Convolutional Neural Network with Attention Module for Identification of Tunnel Seepage
    SAGE Publications ; 2022
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2676, No. 11 ( 2022-11), p. 112-123
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2676, No. 11 ( 2022-11), p. 112-123
    Abstract: As tunnel construction proceeds ever more rapidly, the efficiency of seepage detection by engineers with expert knowledge is facing unprecedented challenges. Moreover, it suffers from strong subjectivity. In recent years, deep learning, as an algorithm of machine learning, has achieved state-of-the-art performance in pattern recognition. In this paper, we address such a problem by building convolutional neural networks that operate on conventional graphics processing units. Within the project, the data is obtained by an infrared thermal imager since there exist different characteristics of temperature between the area of seepage and non-seepage. Considering the difficulty of collecting many images, generative adversarial nets and other data augmentation skills are applicable to enlarge data sets. We design several novel architectures where the attention mechanism is plugged into various traditional models, considered as VGG16 network with Attention Module and RestNet34 with Attention Module, and the overall identification accuracy achieved is more than 97%. The codes of this project can be found at https://github.com/Scotter-Qian/cnn .
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981221091774
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
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  • 5
    Online Resource
    Online Resource
    Hierarchical Automated Machine Learning Approach for Self-Optimizable Driving Distraction Recognition Based on Driver’s Lane-Keeping Performance
    SAGE Publications ; 2023
    In:  Transportation Research Record: Journal of the Transportation Research Board
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications
    Abstract: With the enrichment of smartphone uses, phone-related driving distractions have become a threat to driving safety. One way to mitigate driving distractions is to detect them and provide real-time warnings. However, most existing driving distraction recognition algorithms are pretrained models composed of structures, hyperparameters, and parameters that may not be able to account for drivers’ individual differences and, thus, might result in low model accuracy. This study proposes a domain-specific hierarchical automated machine learning (HAT-ML) model that self-learns personalized optimal models to detect driving distractions from vehicle movement data. The HAT-ML model integrates key modeling steps into auto-optimizable layers, including knowledge-based feature extraction, feature selection by recursive feature elimination, automated algorithm selection, and hyperparameter autotuning by Bayesian optimization. In our eight-degrees-of-freedom driving simulator experiment, we demonstrated the effectiveness of the proposed model using three driving distraction tasks: browsing a short message, browsing a long message, and answering a phone call. The HAT-ML model was found to be reliable and robust for predicting phone-related driving distraction, achieving satisfactory results with a predictive accuracy of 80% at the group level and 90% at the individual level. Moreover, the results revealed that each distraction and driver type required different optimized hyperparameter values, which demonstrated the value of utilizing HAT-ML to detect driving distractions. The key elements that dominated the performance of the model have several theoretical and practical implications. The proposed method not only enhanced performance, but also provided data-driven insights about model development.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981231196152
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
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  • 6
    Online Resource
    Online Resource
    Use of Multi-Rotor Unmanned Aerial Vehicles for Fine-Grained Roadside Air Pollution Monitoring
    SAGE Publications ; 2019
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2673, No. 7 ( 2019-07), p. 169-180
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2673, No. 7 ( 2019-07), p. 169-180
    Abstract: With increasing numbers of motor vehicles, vehicle exhaust gas has become one of the most important sources of urban air pollutants. After being emitted from the motor vehicle, exhaust gas spreads through the air along the road and is gradually deposited in the surrounding area, having an adverse impact on pedestrians and residents. At present, most research on vehicle exhaust directly measures the total emissions from the exhaust pipe or monitors the time variation of air pollutants at the roadside by setting roadside monitoring stations. The spatial resolution of these two methods is very low, however, and it is impossible to describe accurately the diffusion patterns of exhaust gas in the atmosphere after discharge. Some scholars have conducted research on the quality of roadside air by hand-held portable devices, but these are limited by the speed of travel, and the spatial and temporal resolution of the acquired data is also very low. By using multi-rotor unmanned aerial vehicles (UAVs) and portable equipment, this study demonstrates an atmospheric environment monitoring system based on multi-rotor UAV by designing corresponding hardware circuits and software programs. With flexible requirements for takeoff or landing sites and high maneuverability of multi-rotor UAVs, the system increases the capability for high resolution spatial and temporal monitoring of the diffusion of traffic-emitted pollutants. The system can conduct fixed-point measurement by hovering, and can also measure air pollutants in complex urban terrain, providing an innovation in the study of vehicle exhaust gas diffusion.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/0361198119847991
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2019
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  • 7
    Online Resource
    Online Resource
    Evaluation of the Effectiveness of Mississippi's Pavement Warranty Program
    SAGE Publications ; 2013
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2366, No. 1 ( 2013-01), p. 98-109
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2366, No. 1 ( 2013-01), p. 98-109
    Abstract: More and more state highway agencies have adopted pavement warranty programs in their project contracting to foster contractor innovation, enhance pavement performance, reduce agency costs, and preserve the investment in pavement construction. The Mississippi Department of Transportation (DOT) initiated its pavement warranty program in 2000. This study evaluated the effectiveness of that program on the basis of the international roughness index and data on rutting, cracking, and other typical surface distresses collected and stored in the database of the agency's pavement management system. The distribution of this pavement performance data at different lengths of service was developed for both warranted and nonwarranted projects to reveal the pavement performance characteristics under the two contracting methods. Pair-wise comparison of the distribution of the pavement performance data at different lengths of service was conducted to investigate pavement deterioration patterns over time for both warranted and nonwarranted pavements. Finally, two-sample t-tests were performed to compare the performance of warranted and nonwarranted pavements at the same length of service. The results of the study showed that the deterioration rate of the warranted pavements was slower than that of the nonwarranted pavements and that the performance of the warranted pavements was superior to that of the nonwarranted pavements at the same length of service. On the basis of the statistical analyses, it could be concluded that the pavement warranty program in Mississippi can effectively improve the pavement performance for the state.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2366-12
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2013
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  • 8
    Online Resource
    Online Resource
    Approaches to Adaptive Lighting on Roadways
    SAGE Publications ; 2015
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2485, No. 1 ( 2015-01), p. 26-32
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2485, No. 1 ( 2015-01), p. 26-32
    Abstract: Adaptive lighting is an approach to lighting design that proposes to change the light level on a roadway on the basis of the needs of drivers. A review of the literature and building the connection between crashes and light level allowed the development of a system to select roadway luminance levels and then modify these levels on the basis of the needs of the driver. This adaptive lighting system uses parameters such as traffic volume, ambient light levels, pavement marking quality, intersection density, and, most important, the presence of pedestrians to allow lighting design criteria to be selected through a weighting system. As these parameters (such as traffic volume) change, a new light requirement is determined, and the lighting system can be adjusted with controllable luminaires and a master control system. Guidelines for the implementation of this system and an example are provided.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2485-04
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2015
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  • 9
    Online Resource
    Online Resource
    Dynamic Origin–Destination Matrix Prediction with Line Graph Neural Networks and Kalman Filter
    SAGE Publications ; 2020
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2674, No. 8 ( 2020-08), p. 491-503
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2674, No. 8 ( 2020-08), p. 491-503
    Abstract: Modern intelligent transportation systems provide data that allow real-time dynamic demand prediction, which is essential for planning and operations. The main challenge of prediction of dynamic origin–destination (O-D) demand matrices is that demand cannot be directly measured by traffic sensors; instead, it has to be inferred from aggregate traffic flow data on traffic links. Specifically, spatial correlation, congestion and time dependent factors need to be considered in general transportation networks. This paper proposes a novel O-D prediction framework combining heterogeneous prediction in graph neural networks and Kalman filter to recognize spatial and temporal patterns simultaneously. The underlying road network topology is converted into a corresponding line graph in the newly designed fusion line graph convolutional networks (FL-GCNs), which provide a general framework of predicting spatial-temporal O-D flows from link information. Data from the New Jersey Turnpike network are used to evaluate the proposed model. The results show that the proposed approach yields the best performance under various prediction scenarios. In addition, the advantage of combining deep neural networks and Kalman filter is demonstrated.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/0361198120919399
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2020
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  • 10
    Online Resource
    Online Resource
    Evaluation of Flood-Vulnerable Pavement Network in Support of Resilience in Pavement System Management
    SAGE Publications ; 2023
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2677, No. 8 ( 2023-08), p. 474-482
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2677, No. 8 ( 2023-08), p. 474-482
    Abstract: Transportation systems play a pivotal role in the nation’s economic and societal development. Transportation assets, such as pavements and bridges, are inevitably subject to the effects of climate and environment. These stressors mainly include flood, precipitation, heat, wildfire, and wind. Specifically, more extreme weather events, such as hurricanes and snowstorms, have occurred in recent years. This requires stakeholders to better prepare transportation infrastructure resilience in planning, design, construction, and management. Its importance is manifested through nationwide policy and state-level practice. For example, in Bipartisan Infrastructure Law, the FHWA directs all state DOTs to incorporate resilience in their transportation asset management plans. A critical element in resilience is to evaluate the effect of climatic or environmental stressors on facilities’ performance. This study examines the impact of flood on the TxDOT-managed pavement network. It proposes a method to evaluate the flood-vulnerable pavement network in the context of resilience. First, the GIS tool is used to overlap a 100-year frequency flood with the road network to identify weak pavement sections subject to flood risk. Second, a simulation is run to determine sections affected by flood over a 10-year analysis horizon. Then, different deterioration models are used to predict the network-level pavement performance, to reflect (1) normal deterioration without flood, (2) optimistic accelerated deterioration under flooding, and (3) pessimistic accelerated deterioration under flooding. It is found that the network-level pavement will experience varying levels of performance reduction, owing to a 100-year flood impact. The quantified performance change can serve to enhance infrastructure resilience preparation for more reliable pavement system management.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981231156934
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
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