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20 June 2024, Volume 43 Issue 6 Previous Issue   
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Transportation Infrastructure Engineering
Transportation+Big Data & Artificial Intelligence
Transportation Equipment


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Transportation Infrastructure Engineering

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Bridge Construction Progress Identification Method Based on UAV Point Cloud and BIM Model FENG Dongming1,2,3， GE Jian1,2， WU Gang1,2,3， YUAN Jianbin4 2024, 43(6): 1-7.  DOI: 10.3969/j.issn.1674-0696.2024.06.01 Abstract ( )   PDF (3600KB) ( )   In order to accurately and automatically monitor bridge construction progress, a bridge construction progress identification method based on unmanned aerial vehicle (UAV) point cloud and BIM model was proposed. Firstly, as-built point clouds were obtained based on UAV flight planning and 3D reconstruction, and the BIM model was converted into as-planned point clouds by turning the BIM model into point clouds. Secondly, bridge components were segmented based on the nearest neighbor search and color region growth after the registration between as-built and as-planned point clouds. Finally, the percentage of completion of each bridge component was acquired. Taking Shanxi Linyi Yellow River Bridge as the research example, the as-built and as-planned point cloud data were collected, and the accuracy of the calculated percentage of completion of each component was above 95%. The proposed method can quickly collect progress data and realize bridge construction progress identification at the component level, which improves the automation of bridge construction progress monitoring. References | Related Articles | Metrics

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Schemes and Effect Evaluation of Retrofit Construction Sequences for Reinforced Concrete Arch Bridge XU Lueqin1,2, YANG Zhongyou1, ZHOU Shuixing1,2, YUE Kefeng1, SHEN Zhengxuan1 2024, 43(6): 8-15.  DOI: 10.3969/j.issn.1674-0696.2024.06.02 Abstract ( )   PDF (2749KB) ( )   In order to study the optimal reinforcement construction sequence of reinforced concrete arch bridge, three sets of targeted reinforcement schemes were designed against the background of the reinforcement scheme design of a four-span box-shaped arch bridge in service, and the mechanical properties of the main arch ring under different demolition and reinforcement construction sequences were analyzed. The stress change law of the arch ring during construction and the load effect of the original arch ring after reinforcement were evaluated by using the change rate of dead-load stress (αD) and the change rate of load effect (αN). The research results show that the demolition and retrofit sequence of the arch building has little influence on the mechanical properties of the main arch ring after reinforcement, but it has a great influence on the stress state of the main arch ring during the reinforcement process. When the arch vault is symmetrically demolished αD＜0, the structure is in the state of "unloaded", which is conducive to the stress of the arch bridge in the construction process. The change rate of load effect (αN) increases with the decrease of the dead load of the arch structure and the growth rate slows down. Therefore, the utilization rate of the reinforcement layer material also increases with the decrease of the dead load of the arch structure, and the growth rate slows down. The larger the αN, the better the reinforcement effect. References | Related Articles | Metrics

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Mechanical Characteristics of Sand High-Density Sponge Cushion in Shed Tunnel WANG Xing1,2,3, WANG Shuaishuai2, HUANG Shuai2,MEI Hua4,HU Zhaoxia4 2024, 43(6): 16-24.  DOI: 10.3969/j.issn.1674-0696.2024.06.03 Abstract ( )   PDF (5528KB) ( )   Based on a tunnel entrance project, more effective rockfall impact protection structures were explored. A 1∶10 geometric similarity model test and LS-DYNA numerical calculation method were used to reveal the mechanical response mechanism of sand high-density sponge composite cushion under rockfall impact. The model test results show that the peak stress at the center of the roof belly decreases from 1.71 MPa to 0.75, 0.24 MPa with the addition of 3 and 6 cm high-density sponge to form the composite cushion, and the decrease is 55.90% and 86.43%. The results of numerical calculation equally proportional to the test show that after adding 3 and 6 cm sponges to form a composite cushion layer, the peak stress at the center of the roof belly decreases from 1.13 MPa to 0.57 and 0.22 MPa, with a decrease of 49.73% and 80.35%. The numerical calculation results of actual working conditions indicate that the stress level of the shed tunnel with composite cushion is significantly reduced, the overall stress inside the board is relatively uniform, and the stress concentration state at the center has been basically eliminated. The stress curve has changed from a broken line form of pure sand cushion to a wave like pattern, with the peak stress decreasing from 5.63 MPa to 1.77 MPa and with a reduction of up to 68.56%. The peak displacement decreases from -3.08 mm to -2.51 mm and the peak acceleration decreases from 514 m/s2 to 445 m/s2. References | Related Articles | Metrics

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Comparison of Preparation Methods of Terminal Blend Rubber Powder Modified Asphalt LU Bensheng1, YANG Fan2, ZHANG Guoyang3, ZHOU Xiaojing3, TANG Naipeng4 2024, 43(6): 25-31.  DOI: 10.3969/j.issn.1674-0696.2024.06.04 Abstract ( )   PDF (960KB) ( )   The high-temperature terminal blend (TB) rubber powder modified asphalt technology can simultaneously solve the high viscosity, poor storage stability and odor emission issues caused by traditional asphalt rubber (AR). However, the 260 ℃ high-temperature process may cause safety issues and production difficulty is relatively high. The molecular structure, solubility, molecular weight distribution, rheological properties, segregation and other indicators of rubber powder modified asphalt prepared by high-temperature method (260 ℃), chemical activation method (200 ℃) and high-speed shear method (200 ℃) were comprehensively compared by means of FTIR, solubility test, gel permeation chromatography (GPC), rheological test and storage stability test. The results indicate that the rubber powder modified asphalt prepared by three kinds of methods all undergo desulfurization reaction (enhanced active polymer groups at 966 cm-1 peak in infrared spectrum) and degradation reaction (degradation of large molecular chain segments of partial rubber powder, which produces molecular chains equivalent in size to asphaltene). The degree of desulfurization degradation by high-temperature method and chemical activation method is more severe than that by shear method. The solubility of TB rubber powder modified asphalt prepared by high-temperature method and chemical activation method is greater than 96% and is about 4%~7% higher than that of shear method. The viscosity at 135 ℃ is about 1.2~1.3 Pa·s, which is about one-third of that of shear method. Under 20% rubber powder content, it is difficult to prepare low viscosity TB rubber powder modified asphalt by high-speed shear method at 200 ℃ and 48 hours of development. Reducing the content of rubber powder can accelerate the degradation of rubber powder during the development process. The high-speed shear method has the potential to prepare low content TB rubber powder modified asphalt. References | Related Articles | Metrics

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Experimental Study on Collapse Models of Landslide Dam with Different Cross-Section Discharge Troughs XU Fugang, CHEN Zhiyu, CAO Jun, FENG Bo, GE Junwei 2024, 43(6): 32-38.  DOI: 10.3969/j.issn.1674-0696.2024.06.05 Abstract ( )   Taking the Jinsha River Baige landslide dam on November 3, 2018 as a prototype, the same particle grading material was used, and 7 kinds of test conditions were set up, which considered the cross-sectional shape, position, size, and other aspects of the installed discharge troughs. Under the same condition of controlling the upstream water inflow, the experimental breaching process under each condition was observed to reveal the evolution mechanism of landslide dam breaching and its influencing factors. The results show that the breaching process can be divided into four stages: the initial gestation stage, the erosion stage of the backwater slope, the erosion stage of the backwater steep bank, and the stable equilibrium stage of the riverbed. During the breaching process of different cross-sectional shapes of discharge troughs, the impact range of erosion degree is ranked from strong to weak as natural group, triangular groove, rectangular groove, and trapezoidal groove. For the cross-sectional shape and size as well as the location of the discharge trough, when the width is the same and the depth is lower, the breaching process will be earlier under the influence of the constraints; when the section of the discharge trough is the same and the layout is located on one side, under the influence of the fixed constraints on one side, the breaching width expansion will be smaller than that when the layout is located at the center. The research results can provide a reference for the analysis of failure mechanism and emergency rescue and disposal of landslide dam. References | Related Articles | Metrics

Transportation+Big Data & Artificial Intelligence

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IDBiLSTM Short-Term Traffic Flow Prediction with Fused Hysteretic Extreme Learning Machine ZHANG Yang1，WANG Ziliang1，YAO Fangyu1，XU Haoyue2，YANG Shumin3 2024, 43(6): 39-46.  DOI: 10.3969/j.issn.1674-0696.2024.06.06 Abstract ( )   PDF (1545KB) ( )   In deep learning short-term traffic flow prediction, there are some problems, such as the weak real-time performance in data processing and the poor prediction performance caused by the insufficient reuse and correction ability of the algorithm for traffic flow data. To address these problems, a kind of short term traffic flow prediction method using deep bidirectional long short-term memory neural network which incorporated a hysteretic extreme learning machine was proposed. Firstly, a weight-sharing mechanism was introduced to optimize the structure of the bidirectional long and short-term memory network model, and the weights and biases were continuously updated during the training process of the model, so as to make full use of the reverse-order data to enhance the reuse and correction ability of the data. Secondly, in order to further improve the real-time performance of the algorithm, the extreme learning machine model was introduced and the hysteretic parameters of the biological neural system were embedded in the activation function of its neurons, which optimized the computational efficiency and enhanced the overall real-time performance of the algorithm. The experimental results show that the proposed method has improved prediction accuracy and algorithm real-time performance, its average absolute error is respectively reduced by 6.82 and 6.47 and its computation speed is respectively improved by 12 and 19 seconds, compared with the classical method CNN-BiLSTM and multivariate ensemble CNN-LSTM, which has good short-term traffic flow prediction capability and real-time performance. References | Related Articles | Metrics

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Traffic Flow Data Completion Framework Model Based on VAR-LRTC-TNN SUN Qiuxia1, WANG Qi1, LI Qing1, SUN Lu2, JIA Xiuyan1 2024, 43(6): 47-53.  DOI: 10.3969/j.issn.1674-0696.2024.06.07 Abstract ( )   PDF (1574KB) ( )   The traffic flow data collected from various sensing systems frequently occurs continuously data missing due to detector and communication failure. Therefore, it is crucial to accurately complete the missing traffic flow data to develop a reasonable traffic management strategy. Given the low-rank nature of traffic flow data, the low-rank tensor completion model could effectively characterize the global consistency of traffic flow data, but it failed to well capture the local change trend of the data, which to some extent affected the effectiveness. In view of the above problems, a traffic flow completion framework model by combining VAR model with LRTC-TNN model based on residual sequence was proposed. The VAR model was used to roughly estimate the missing data and remove the average trend. The LRTC-TNN model was used to complete the residual time series and then restore the average trend, so as to achieve high-precision completion of traffic flow data. The proposed method not only retained the global structure of traffic flow data, but also considered the characteristics of local variation of the data. The research results indicate that the proposed model framework has higher completion accuracy for the continuously missing of data for single and multiple sensors than the filling method based on the original traffic flow data does. References | Related Articles | Metrics

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Optimization of Rail Transit Feeder Bus Routes Based on Improved NSGA-II PEI Yulong, JIANG Fengshuai, WANG Wanjiao, HE Qingling 2024, 43(6): 54-63.  DOI: 10.3969/j.issn.1674-0696.2024.06.08 Abstract ( )   PDF (1566KB) ( )   In order to solve the problems of irrational planning and imperfect scheduling of feeder bus routes, a loop feeder bus route optimization method based on improved NSGA-II was proposed. Firstly, combining with the bi-level programming theory, the upper layer model was constructed with the minimization of passenger travel time cost, the maximization of bus enterprise operation revenue and feeder bus service rate as the objective functions and the number of stops of the feeder bus line, the length of the line and the frequency of departure as the constraints. And the lower layer feeder passenger flow distribution model was constructed with the Logit model. Secondly, the initialized population of NSGA-II was optimized using Floyd algorithm, and the model solution flow was designed for the proposed model. Finally, taking Harbin City Subway Line 1 Medical University First Hospital Subway Station as a case study, the proposed multi-objective bi-level programming model and algorithm were applied for solution and compared with the original NSGA-II algorithm and the NSGA-II algorithm based on Logistic chaos mapping. The research results show that the improved NSGA-II algorithm based on Floyd algorithm has a faster convergence speed and better performance in solving multi-objective bi-level programming models. The solution results can obtain multiple mutually non-dominated optimal solutions at the Pareto front. Different solution sets correspond to different objective function values, but all of them can achieve the optimal overall benefit of the connecting bus network, and the solution results are expressed by the compromise optimal solution set. References | Related Articles | Metrics

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Willingness to Continue Using Shared Electric Bicycle Based on TAM-CPV Model ZENG Chao1, 2, CHU Jialiang1, WANG Song1, YU Li3, MAO Chaoyan1 2024, 43(6): 64-70.  DOI: 10.3969/j.issn.1674-0696.2024.06.09 Abstract ( )   PDF (765KB) ( )   It is crucial to deeply analyze the factors affecting the use of shared electric bicycles and enhance the willingness of shared electric bicycle users to continue using them, in order to promote the healthy and orderly development of shared electric bicycles and improve the level of refined management of delivery. Based on technology acceptance model (TAM), the perceived pleasure and perceived risk in the customer perceived value (CPV) theory were introduced, meanwhile, the perceived cost factors were also introduced. The model of willingness to continue using shared electric bicycle based on TAM-CPV model was established. Based on the supervision data, field survey data and network survey data of Chongqing shared electric bicycle operation, SPSS and AMOS software were comprehensively used to test and analyze the structural equation model. The research results show that the perceived ease of use is the most significant positive factor affecting the willingness to continue to use, followed by the perceived pleasure, and the perceived cost is the only negative factor. It is indicated that the government management department should pay attention to the rationality of the shared bicycle delivery point, and the enterprise should pay attention to the user experience and billing rules of the shared bicycle APP. References | Related Articles | Metrics

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Alleviating Effect of Different Color Light Environments on Drivers Visual Fatigue in the Middle Section of Long Tunnel LIU Changbao, ZANG Yanwei, SUN Xing 2024, 43(6): 71-77.  DOI: 10.3969/j.issn.1674-0696.2024.06.10 Abstract ( )   PDF (1893KB) ( )   Based on long tunnel lighting, the visual fatigue relief effect in different colored light environments was quantified by selecting parameters such as pupil area, scanning amplitude, and scanning speed in the simulated driving experiment. The causes of drivers visual fatigue were analyzed, and comprehensively evaluated through fuzzy evaluation model. The measures to alleviate drivers visual fatigue by arranging different color light environments were proposed. The research results show that the pupil area and saccade amplitude corresponding to different color light environments have significant differences, with red light having the best visual fatigue relief effect, followed by yellow light. The change rate of pupil area corresponding to three colors of light environment is all less than 20%, which will not bring significant visual stimulation to the driver. References | Related Articles | Metrics

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Risky Riding Behavior of Campus E-bikes Based on Structure Equation Model DENG Yuanchang1,2，LIU Feifei1,2 2024, 43(6): 78-86.  DOI: 10.3969/j.issn.1674-0696.2024.06.11 Abstract ( )   PDF (801KB) ( )   In order to improve campus traffic safety, the influencing factors of college students risky E-bikes riding behaviors on the campus were explored. According to the results of the preliminary research, "environmental regulation attitude" variable was added into the planned behavior theory (TPB) model, then a questionnaire was compiled, and the structural equation model (SEM) based on the extended TPB was constructed. Through correlation analysis and model path testing, 264 valid sample data were empirically studied. Results show that on campus, students average daily riding time, cycling accident rate and charging conflict rate are positively correlated with risky riding behaviors, and behavior attitude, subjective norm, and perceived behavior control have a certain effect on safe behavior intention. The strongest inhibitory factor on risky riding behavior is safe behavior intention, followed by environmental control attitude. Perceived behavior control presents a promoting effect on risky riding behavior, which is different from previous studies. The research results can provide references for the effective control of risky riding behaviors on campus. References | Related Articles | Metrics

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Heterogeneous Influence of Built Environment on Pedestrian Accident Injury Severities at Intersections PAN Yiyong, LI Shuo 2024, 43(6): 87-93.  DOI: 10.3969/j.issn.1674-0696.2024.06.12 Abstract ( )   PDF (423KB) ( )   In order to investigate the influence of built environment and other factors on the severity of pedestrian accidents, a random parameters Logit model with heterogeneity in means and variances was established to analyze the heterogeneity of pedestrian accident injury severities at intersections. By use of the data of pedestrian collision accidents, 27 influencing factors were selected from six aspects such as pedestrians and drivers, vehicles, roads, environment, time and built environment. The elasticity coefficient was used to analyze the influence of significant variables on accident injury severities. The results show that the existing of the accessibility of subway station is a random parameter, and setting the vehicle status as other will reduce the mean value of the random parameter and pedestrian accident injury severities at the intersections. Variance is significantly related to afternoon, which will increase the dispersion of random parameter, widen the distribution and increase the randomness. The impact of different land use types and intersection types on pedestrian accident injury severities is significantly different. When the accessibility of commercial areas and subway stations exists, the probability and severity of pedestrian accidents at intersections decrease. Moreover, factors such as pedestrian misconduct significantly increase the severity of pedestrian accidents at intersections. The research results provide a reference and basis for formulating the optimization and improvement measures of the built environment of intersections. References | Related Articles | Metrics

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4D Trajectory Prediction Based on Transformer-GRU Network ZHAI Wenpeng, SONG Yiqiao, ZHANG Zhaoning 2024, 43(6): 94-101.  DOI: 10.3969/j.issn.1674-0696.2024.06.13 Abstract ( )   PDF (2058KB) ( )   The 4D trajectory prediction of aircraft is one of the key technologies based on trajectory-based operations (TBO), which has significant significance. Based on Transformer-GRU (T-GRU) network, a trajectory prediction method was proposed and 4D trajectory prediction was realized by combining with Adamax optimizer. Firstly, the self-attention mechanism of the Transformer network was used to model the input sequence, and the features of time-series data were obtained through the GRU network. Secondly, the original trajectory data was preprocessed by resampling interpolation and median filtering to eliminate the impact of data missing and outliers on prediction. Finally, the experimental results were evaluated through error indicators such as EE, EAT, ECT and EA, and compared with other commonly used trajectory prediction methods. The research results show that the proposed T-GRU network-based 4D trajectory prediction model has higher accuracy and robustness in trajectory prediction, compared with traditional deep learning methods. References | Related Articles | Metrics

Transportation Equipment

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Parameter Identification of Permanent Magnet Synchronous Motor Based on Improved Dung Beetle Optimization Algorithm ZHAO Qiang， WANG Haojie， XIE Chunli 2024, 43(6): 102-108.  DOI: 10.3969/j.issn.1674-0696.2024.06.14 Abstract ( )   PDF (1468KB) ( )   A parameter identification method based on an improved dung beetle optimization (DBO) algorithm was proposed to address the current issues of insufficient accuracy and low efficiency in multi-parameter identification of permanent magnet synchronous motors (PMSM). Firstly, the PMSM full rank discrete equation was established in the synchronous rotating coordinate system. Secondly, to improve the precision of DBO algorithm in identifying PMSM model, Tent mapping and reverse learning strategy were used to enhance the uniformity of initial population, and a nonlinear update factor was designed. The factor was adjusted as the number of iterations increased, which could improve the search and development capabilities of DBO. Finally, to address the slow convergence problem of DBO, the location update strategy for obstacle-free ball-rolling beetles were improved to accelerate its convergence, and the PMSM parameter identification fitness function was designed and DBO algorithm was improved and applied for parameter identification flowchart. Simulation and experiment verification show that the improved DBO algorithm has faster speed and higher accuracy in parameter identification of permanent magnet synchronous motors. References | Related Articles | Metrics

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Optimization of Vehicle Steady-State Handling Characteristics Based on Dynamic Simulation RONG Bing1， LIU Ke2， LIAO Yinghua2， MOU Zonghai2， LIU Changzhao3 2024, 43(6): 109-117.  DOI: 10.3969/j.issn.1674-0696.2024.06.15 Abstract ( )   PDF (3225KB) ( )   To address the problem of poor handling stability and comfort of a pure electric vehicle, the dynamic simulation parameter matching analysis method was used to effectively support real vehicle matching, which achieved significant results. Firstly, the vertical stiffness of the front and rear suspensions was matched and analyzed to optimize the body pitch response due to vertical vibrations at different bias frequencies. To optimize the coordination of front and rear suspension roll motion, the roll stiffness of the front and rear suspension was optimized and matched, with the goal of consistency in the compression rate of the lateral acceleration relative to the travel of the front and rear suspension when turning to the outer side, which was based on multi-body dynamics simulation of vehicle steady-state turning conditions of vehicles. Secondly, dynamic simulation research was carried out on the effects of roll, lateral force, and return torque steering on the whole vehicle understeer, and an optimization approach for the whole vehicle understeer degree based on hard point layout and bush matching was proposed, providing effective improvement ideas and solutions for actual vehicle tuning. Finally, the real vehicle matching verified the effectiveness of the optimized scheme. The results show that after optimization, the balance between front and rear suspension vertical jump and roll motion is better, the steady-state control characteristics are significantly improved, and the subjective evaluation score exceeds the target by 0.5 points, resulting in a 10% improvement in handling performance. The proposed scheme has been applied to mass-produced vehicle types, providing a reference case for developing vehicle handling stability performance. References | Related Articles | Metrics

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Mechanical Properties and Energy Absorption Characteristics of SLM-Formed Ti-6Al-4V Layered Hybrid Lattice Structure REN Yi1, 2， RAN Wei1， PU Lin1， CAI Siyang1， ZHAO Yucheng1 2024, 43(6): 124-132.  DOI: 10.3969/j.issn.1674-0696.2024.06.16 Abstract ( )   PDF (5091KB) ( )   The Ti-6Al-4V titanium alloy lattice structure formed by selective laser melting (SLM) was used as the object of study. Firstly, a single lattice structure composed of body-centered cubic (BCC) unit cell and the layered-hybrid lattice structure composed of BCC unit cell and face-centered cubic (FCC) unit cell were designed and prepared. Secondly, the surface morphology and geometry structure of the prepared lattice structures were characterized by using scanning electron microscopy (SEM). Thirdly, quasi-static uniaxial compression tests on the lattice structure were performed by using a universal mechanical testing machine, and the mechanical and energy absorption properties of different lattice structures were compared. Finally, the deformation modes of the single lattice structure and the layered hybrid lattice structure were analyzed and discussed. The results show that the elastic modulus of the layered hybrid lattice structures TBF-A and TBF-B is respectively increased by 27.80% and 24.15%, the yield strength is respectively increased by 22.96% and 18.36%, and the specific energy absorption is respectively increased by 96.01% and 33.33%, compared with the single BCC lattice structure. In addition, in terms of deformation behavior, the BCC lattice structure undergoes overall fracture along the 45° direction, and the fracture of the TBF-A and TBF-B layered hybrid lattice structures occurs only in the region of the matrix phase (BCC lattice structure) due to the presence of the reinforce phase (FCC lattice structure). References | Related Articles | Metrics