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  • Mobility and traffic research  (12)
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  • Mobility and traffic research  (12)
  • 1
    Online Resource
    Online Resource
    Study on Stability of Excavation Surface of Shield Tunnel in Clay Layer
    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: If an excavation surface becomes unstable, it will cause damage such as soil collapse or surface uplift. Through field investigations and tests, the stability of the shield tunnel excavation surface and its influencing factors are studied in this paper. Equations for solving the limit support pressure of the excavation surface of the overlying multilayer soil tunnel and for the safety factor of the excavation surface are deduced. The single reduction method and the double reduction method are respectively used to solve the safety factor of the excavation face under the basic working conditions, and the numerical simulation method of the safety factor of the excavation face is clarified. Based on FLAC3D numerical simulation software, the ultimate support pressure and safety factor were used as the evaluation criteria for the stability of the excavation face to analyze the response of objective factors such as internal friction angle and cohesion, as well as engineering factors such as hole diameter to the stability of the excavation face. The greater the internal friction angle and cohesion, the smaller the hole diameter, the more stable the excavation surface, and the internal friction angle has the greatest impact on the stability of the excavation surface.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981231169281
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
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  • 2
    Online Resource
    Online Resource
    Experimental Features and Characteristics of Speed Dispersion in Urban Freeway Traffic
    SAGE Publications ; 2007
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 1999, No. 1 ( 2007-01), p. 150-160
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 1999, No. 1 ( 2007-01), p. 150-160
    Abstract: Characteristics of speed dispersion in urban freeway traffic are presented. Two definitions of speed dispersion are proposed: the standard deviation of the individual speeds and the average speed difference of two neighboring vehicles. On the basis of the definitions, traffic data obtained from two urban freeways in China are studied, and different characteristics of speed dispersion are found in four substates of traffic flow, which correspond to four regions in the empirical fundamental diagram. In the bunching state of congested traffic, the flow rate decreases with an increase in speed dispersion at a given mean speed. In the bunching state of fluid traffic, the speed dispersion of traffic flow is small, and in the free state of fluid traffic, speed dispersion is distributed in a disorderly manner in a wide range. Such phenomena are more remarkable under the definition of the average speed difference for speed dispersion. In addition, some possible explanations are presented for the characteristics of speed dispersion in each traffic substate. These speed dispersion studies provide a new approach for microscopic modeling and understanding of traffic flow characteristics.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/1999-16
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2007
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  • 3
    Online Resource
    Online Resource
    Nonlinear Model-Based Subway Station-Level Peak-Hour Ridership Estimation Approach in the Context of Peak Deviation
    SAGE Publications ; 2022
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2676, No. 6 ( 2022-06), p. 549-564
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2676, No. 6 ( 2022-06), p. 549-564
    Abstract: Existing techniques for estimation of subway station-level long-term peak-hour ridership (PHR) may produce underestimated PHR values that may result in stations being designed with insufficient capacity during the planning stage; this in turn may increase congestion on the platforms in actual operation. One of the reasons for this potential undesirable outcome is that peak deviation phenomena often arise between stations and lines in subway systems, which could create underestimated PHR values. The default assumption has always been that the peak hour of passenger flow of each station always overlaps with its attributed line. This paper presents a framework of a station-level long-term PHR estimation method calibrated using the peak deviation coefficient (PDC) and a nonlinear model (eXtreme Gradient Boosting). This approach can estimate the PDC values for PHR prediction, and can also quantify the relative importance of PDC associated factors, yielding an explanation of the main causes of peak deviation phenomena. Using a real-world, large-scale passenger flow dataset from Xi’an, China, the approach produces more stable and accurate predictive performance compared with conventional methods (i.e., absolute percentage error controlled within 20% versus 50%, and mean average percentage error reduced by 3.26%–8.35%). Meanwhile, it is found that the relative importance of the unimproved land use ratio ranks in the top four for all types of peak periods; this ratio is a key factor that may be used to mitigate ridership deviations between stations and line peaks. In addition, for subway networks, the influence of land use entropy increases from the morning peak hour to the evening peak hour and weakens across the route from origin to destination.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981221075624
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
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  • 4
    Online Resource
    Online Resource
    Catchment-Area Delineation Approach Considering Travel Purposes for Station-Level Ridership Prediction Task
    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: Station-catchment-area delineation is a key component of direct ridership models for urban rail-transport systems as it can determine the relationship between the urban-rail-transit station-level ridership and the variables within the station catchment area. The neglect of differences in the passenger-flow distribution for different travel purposes in previous studies has led to low accuracy of the obtained walk-to-station distances. Therefore, this paper proposes a station-catchment-area delineation method which is based on web map data to obtain accurate walk-to-station distances and considers differences in the distance thresholds and the ridership attraction intensity (RAI) for six travel purposes (corresponding to commercial, medical, residential, educational, administrative, and recreational land uses). In the case study, the ridership data of Xi’an Metro, the 2015 Xi’an Residential Travel Survey data, and the corresponding Gaode Map data are employed to extract passengers’ walking-distance distribution for several travel purposes to delineate the station catchment areas and build direct ridership models. Several geographically weighted regression (GWR) models are constructed to evaluate and examine the effects of the various station-catchment-area delineation methods on the model findings. The obtained results show that the proposed station-catchment-area delineation method significantly improves the ridership prediction performance compared with the traditional circular-buffer method, with the entry and exit ridership prediction accuracy improving by 3.57% and 6.65% on average, respectively. Finally, this study will guide transportation planners on how to delineate station catchment areas when constructing direct-demand models for urban rail stations.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981231189738
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
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  • 5
    Online Resource
    Online Resource
    Use of Support Vector Machine Models for Real-Time Prediction of Crash Risk on Urban Expressways
    SAGE Publications ; 2014
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2432, No. 1 ( 2014-01), p. 91-98
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2432, No. 1 ( 2014-01), p. 91-98
    Abstract: This study adopted a novel methodology—a support vector machine (SVM) with two penalty parameters—for the evaluation of real-time crash risk on urban expressway segments by using dual-loop detector data. The purpose of this study was to develop a model that can effectively identify traffic conditions prone to crashes and support implementation of proactive traffic safety management. On the basis of crash data and the corresponding detector data collected on expressways of Shanghai, China, different combinations of dual-loop detector data and time segments before crashes were used to develop the optimal crash risk estimation model by SVM. The transferability of the SVM model was assessed by examining whether the model developed on one expressway was applicable to other similar ones. In addition, the prediction results and transferability of the SVM model were compared with those given by other frequently used classification algorithms, including logistic regression, Bayesian networks, naïve Bayes classifier, k-nearest neighbor, and back propagation neural network. The results showed that the SVM model was more suitable to the prediction of real-time crash risk with small-scale data than other algorithms, with its accuracy in classifying crashes reaching a best of 80%. A comparison to similar studies by other researchers implied that the proposed model achieved better prediction accuracy.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2432-11
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2014
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  • 6
    Online Resource
    Online Resource
    Multi-Modal Urban Traffic Transfer Schedule Timetable Bi-Objective Optimization: Model, Algorithm, Comparison, and Case Study
    SAGE Publications ; 2024
    In:  Transportation Research Record: Journal of the Transportation Research Board
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications
    Abstract: The optimization of the connection between urban rail transit and the bus is an essential issue that benefits passenger travel and the urban structure and has social benefits, which can be realized by reasonably adjusting the bus departure schedule. This study is necessary because the development status quo of China’s urban transportation network planning is unreasonable, travel efficiency is not high, and operating costs are high. This paper sets up the decision variables of bus departure time and departure interval at each station, establishes a dual-objective optimization model with the minimum schedule change and the minimum transfer time, and studies the application of the augmented Chebyshev algorithm in the dual-objective optimization model. Secondly, based on the Shenzhen metro and public transportation integrated circuit card data, the case analysis uses the generalized Chebyshev algorithm and the non-dominated sorting genetic algorithm, respectively. The optimization results show that using the improved augmented and generalized Chebyshev algorithm in the bus schedule alteration time within a reasonable range can maximize the total transfer time, which compared with the original scheme is shortened by 68.06%. In contrast, genetic algorithms will make the complete bus schedule alteration prominent, and the whole transfer time is substantially increased. The results show that the improved augmented generalized Chebyshev algorithm is more suitable for solving the dual-objective rail transit connection problem.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981241229089
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2024
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  • 7
    Online Resource
    Online Resource
    The Impacts of Incentives on Seat Yielding Behavior on the Bus
    SAGE Publications ; 2023
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2677, No. 2 ( 2023-02), p. 1579-1591
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2677, No. 2 ( 2023-02), p. 1579-1591
    Abstract: The global target to achieve inclusive public transportation includes the availability of courtesy seating for vulnerable individuals such as elderly people, people with disabilities, pregnant women, and children. The frequent usage of courtesy seats by passengers who are not vulnerable individuals is an issue pertaining to public transportation. It is important to encourage the travelers to yield seats in the presence of vulnerable individuals because the latter might get seriously injured by falling if they stay on a moving vehicle. This study explores the influence of incentives and situational factors affecting individuals’ decisions to yield seats to vulnerable people. Through an online questionnaire survey, 404 valid responses were obtained. The generalized linear mixed model (GLMM) with repeated measures was used to identify the influential factors affecting the self-reported decisions of yielding seats to vulnerable individuals. The results indicate that the situational factors (health, crowd, vulnerable passenger type, standing time after yielding seats), incentive types, and incentive amounts are significant factors affecting the decisions to yield seats. The study’s findings also indicate that travelers are more sensitive to people with disabilities and pregnant women than to elderly people and children. The practical implications, including campaigning, education interventions, and incentive-based mechanism, were suggested to encourage travelers to yield seats to vulnerable individuals.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981221113311
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
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  • 8
    Online Resource
    Online Resource
    Strategies to Enhance the Resilience of an Urban Rail Transit Network
    SAGE Publications ; 2022
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2676, No. 1 ( 2022-01), p. 342-354
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2676, No. 1 ( 2022-01), p. 342-354
    Abstract: An urban rail transit (URT) system is an important component of an urban infrastructure system; however, it is vulnerable to disturbances, such as natural disasters and terrorist attacks. Constructing a highly resilient URT network has practical significance for enhancing its capability to respond to disturbances. In this paper, models are developed to optimize a URT network’s structure with regard to resilience and to enhance the resilience of a disrupted URT network. A bi-level programming model that aims to maximize a URT network’s global accessibility and global efficiency is formulated to optimize the structure of the network. A novel repair strategy, called the simulation repair strategy, is proposed to enhance the resilience of a disrupted URT network by optimizing the repair sequence of failed stations. The models are utilized to enhance the resilience of the Chengdu subway network. The result indicates that the bi-level programming model guides the construction of new links to optimize the structure of the Chengdu subway network. Deliberate attacks are more harmful to the Chengdu subway network than random attacks. The network’s operators need to pay attention to the operations of critical stations (e.g., Chunxi Road station and Tianfu Square station) to prevent disturbances from exerting considerable negative effects on the network’s normal operations. The simulation repair strategy exhibits higher repair efficiency than the conventional repair strategy, and it effectively enhances the resilience of the disrupted Chengdu subway network.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981211037888
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2022
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  • 9
    Online Resource
    Online Resource
    Predictive Strategy for Transit Signal Priority at Fixed-Time Signalized Intersections: Case Study in Nanjing, China
    SAGE Publications ; 2012
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2311, No. 1 ( 2012-01), p. 124-131
    Details
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2311, No. 1 ( 2012-01), p. 124-131
    Abstract: It is essential to give priority to transit vehicles at signalized intersections in the megacities of China such as Nanjing. This study developed a transit signal priority (TSP) strategy for fixed-time signals with the use of techniques for advanced and continuous vehicle detection and prediction of arrival time. In the proposed model, transit vehicles were traced once they were positioned at one intersection and were advancing to the subject intersection. For instance, the location and the speed of a transit vehicle were measured every few seconds, and the prediction was made simultaneously by a model integrating historic and real-time data. With the predicted arrival time, the length of the transit signal phase would be adjusted to give the green light to the transit vehicle. The proposed strategy was evaluated with VISSIM simulation and compared with conventional TSP strategies (green extension and early green) in a typical roadway and traffic setting of Nanjing. Results indicated that the conventional TSP strategy could hardly result in significant improvement in transit delay and that the proposed strategy significantly reduced the transit travel time. Despite these findings, the adverse impacts on the delay of other road traffic by TSP could not be ignored. Results of the simulation model indicated that the proposed predictive TSP strategy was less disruptive to other traffic and that its performance in nonpeak periods was superior to that in peak periods. The results also suggest that a well-designed algorithm for the prediction of arrival time is the key to success in implementing predictive TSP control.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.3141/2311-12
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2012
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  • 10
    Online Resource
    Online Resource
    Trajectory-Based Spatiotemporal Multi-Task Multi-Graph Network for Traffic State Prediction
    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: As a critical application in intelligent transportation systems, traffic state prediction still faces various challenges, such as unsatisfactory capability of utilizing multi-source data and modeling spatiotemporal network relevancies. Therefore, we propose a trajectory-based multi-task multi-graph convolutional network (Tr-MTMGN), a novel spatiotemporal deep learning framework for traffic state prediction on a citywide scale. This method firstly mines the underlying information from vehicle trajectories and designs a multi-graph convolution block to investigate spatial correlations. Sequentially, the multi-head self-attention layer is integrated into the multi-task learning framework to capture the temporal dependencies of the traffic state. The proposed model was evaluated on field data collected in Zhangzhou, China, and demonstrated superior performance when compared with existing state-of-the-art baselines.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    URL: Article
    DOI: 10.1177/03611981231185773
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2023
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