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  • Online Resource  (6)
  • Mobility and traffic research  (6)
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  • Online Resource  (6)
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  • Mobility and traffic research  (6)
  • 1
    Online Resource
    Online Resource
    Learning Spatial-Temporal Dynamics for Short-Term Passenger Flow Prediction in Urban Rail Transit
    SAGE Publications ; 2023
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2677, No. 5 ( 2023-05), p. 1330-1348
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2677, No. 5 ( 2023-05), p. 1330-1348
    Abstract: Accurate short-term passenger flow prediction in urban rail transit (URT) plays an important role in ensuring the stable operation of the URT systems. Because of the complex dynamic spatial-temporal dependencies and potential semantic correlations of the URT network, accurate and effective short-term passenger flow prediction is challenging. To solve these problems, a novel model called the dynamic spatial-temporal graph convolutional network (DSTGCN) was proposed. Firstly, spatial semantic graphs (SSGs) were established to encode the spatial dependencies and semantic correlations of the URT network. Meanwhile, the dynamic graph convolutional network (DGCN) with the spatial attention mechanism was used to learn the dynamic spatial correlations of the nodes in the SSGs. Then, the long short-term memory (LSTM) network was integrated into the DGCN to learn the dynamic changes of passenger flow and capture local temporal dependencies. Moreover, the temporal attention mechanism was introduced after LSTM to capture global dynamic temporal correlations by adjusting the weights of different sequence information. Finally, the full connection layers were used to output the prediction results. Several experiments were conducted on Nanning Metro Line 1 real datasets to evaluate the model. The experimental results showed that the DSTGCN can effectively capture the dynamic spatial-temporal dependencies and semantic associations of the passenger flow. Besides, the prediction performances of the DSTGCN were better than those of existing baseline models, and it can provide technical support for improving the intelligent planning and operation decisions of URT systems.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981221143109
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2403378-9
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    Online Resource
  • 2
    Online Resource
    Online Resource
    Role of Surface Roughness in Surface Energy Calculation of Aggregate Minerals
    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: Surface energy is a key material property and can work as a crucial parameter in various mechanical models to predict the moisture sensitivity and fatigue damage of asphalt mixtures. The calculated surface energy values of the aggregate minerals strongly depend on their surface roughness. Therefore, it is very relevant for accurate calculation of surface energy to study the relationship between roughness and surface energy. This study aims to investigate the relationship between surface roughness and surface energy of aggregate minerals. Two minerals—quartz and calcite—were used for this study. The surfaces of the mineral specimens were treated to achieve four levels of roughness. Their surface roughness was described by three roughness parameters. Based on the sessile drop method, an optical tensiometer with a 3D topography module was employed to measure the contact angle and the surface energy of the minerals with different roughness. The influences of surface roughness on the contact angle and the surface energy were then analyzed. The results showed that the contact angle for both quartz and calcite decreases with the increasing surface roughness when it is less than 90° and increases when it is greater than 90°. The Wenzel equation can remove the effect of surface roughness on the contact angles of the minerals. The surface energy of quartz and calcite in the presence of roughness at the microscale would be underestimated when using the measured (apparent) contact angle. The corrected surface energy based on the Wenzel equation must be applied to represent the real surface energy of the minerals.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981231170188
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2403378-9
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    Online Resource
  • 3
    Online Resource
    Online Resource
    Investigation into the Abnormal Phenomenon of Rail Corrugation Superposition in Small-Radius Curve Section of Intercity Railway
    SAGE Publications ; 2023
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2677, No. 5 ( 2023-05), p. 540-555
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2677, No. 5 ( 2023-05), p. 540-555
    Abstract: Focusing on the mechanism of the abnormal phenomenon of rail corrugation on the low rail of small-radius curve section of Guangzhou–Zhuhai intercity railway, the distribution regularities and the track irregularities are studied through the overall and local field surveys. Then, the dynamic model of vehicle-track system on the section is established to explore the wheel-rail dynamic characteristics. Next, the relevant finite element model of the wheel-rail system and the wear model of rail corrugation are established. The friction self-excited vibration analysis and feedback vibration analysis are carried out to investigate the dynamic causes of such abnormal rail corrugation. Field survey proposes that the dominant wavelength of the abnormal rail corrugation is 200–300 mm and the sub-wavelength is 70–100 mm. Analyses show that the friction self-excited vibration of the multi-wheelset-track system caused by the saturated creep force on the guide wheelset in the small-radius section may induce the rail corrugations with these two wavelengths. The possibility of inducing the rail corrugation with 200–300 mm wavelength is greater. On the other hand, the feedback vibration of corrugated wear will aggravate the development of the two corrugated wears. Overall, the generation and development of the abnormal rail corrugations are affected by the self-excited vibration of the wheel-rail system and the feedback vibration of track irregularity.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981221133086
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
    detail.hit.zdb_id: 2403378-9
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    Online Resource
  • 4
    Online Resource
    Online Resource
    Transformation of Transportation Data Models from Unified Modeling Language to Web Ontology Language
    SAGE Publications ; 2008
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2064, No. 1 ( 2008-01), p. 81-89
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2064, No. 1 ( 2008-01), p. 81-89
    Abstract: Transportation data models traditionally are represented in Unified Modeling Language (UML). UML diagrams are intuitive for understanding transportation concepts and their relationships and thus provide standardized ways to construct transportation data models. Many UML models have been developed for this purpose. However, because UML does not consider semantics, sharing UML data is difficult. Reusing UML diagrams also is difficult. In contrast, web ontology language (OWL) describes the semantics of ontology and thus is good for knowledge sharing and reasoning. OWL data are easier to share and better for performing logical inference. Unfortunately, no automatic method is available to transform data models from UML to OWL. A method to automate the transformation process is presented, using transportation data as a case study. Results indicate that transportation data represented in OWL have many advantages, including facilitated data sharing and inference. They also indicate that although many elements in UML can be transformed to OWL, some do not have OWL counterparts.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2064-11
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2008
    detail.hit.zdb_id: 2403378-9
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  • 5
    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
    detail.hit.zdb_id: 2403378-9
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  • 6
    Online Resource
    Online Resource
    Rule-Based Forecasting of Traffic Flow for Large-Scale Road Networks
    SAGE Publications ; 2012
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2279, No. 1 ( 2012-01), p. 3-11
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2279, No. 1 ( 2012-01), p. 3-11
    Abstract: As traffic data collection becomes less costly and more commonplace, large-scale traffic flow forecasting is increasingly needed. This paper proposes a rule-based approach for forecasting traffic flow based on the K nearest neighbor (KNN) nonparametric regression model, the rule-based KNN (RKNN) model. Rules were extracted from the historical data through the use of rough set theory, which found the nearest neighbors. Traffic impact factors, such as weather and time of day, were incorporated into the rules. Every historical record was labeled with a rule. With current data on traffic flow states and traffic flow impact, the nearest neighbors could be found quickly from the historical data records covered by the corresponding rule. An additional methodology was proposed to keep the historical data and the rules up to date. A case study on an Interstate freeway in Virginia, I-395, was conducted to evaluate the performance of the RKNN approach. The results showed that the proposed approach could decrease the mean absolute percentage error by 26.86%. Moreover, the proposed algorithm reduced calculation time by 65.69%, compared with the traditional KNN algorithms. This difference indicates the effectiveness of the proposed algorithm for use with large urban road networks.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2279-01
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2012
    detail.hit.zdb_id: 2403378-9
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