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20 November 2024, Volume 43 Issue 11 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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Literature Review and Prospect of Asphalt Pavement Compaction Detection Based on Ground Penetrating Radar HE Zhaoyi1, ZHANG Yu2, SONG Gang2, XU Diping3, WU Zhou3 2024, 43(11): 1-10.  DOI: 10.3969/j.issn.1674-0696.2024.11.01 Abstract ( )   PDF (561KB) ( )   The compaction quality of asphalt pavement in the construction process is an important factor affecting its performance, and insufficient compaction or excessive compaction will cause premature damage to asphalt pavement. In order to promote the development of ground penetrating radar (GPR) in the field of asphalt pavement compaction detection, and more comprehensively evaluate the compaction quality of asphalt pavement, the detection principle, system composition and data processing method of GPR were systematically expounded. The research status of GPR in the field of asphalt pavement compaction detection was summarized and concluded. The research results show that the dielectric properties of asphalt mixture are affected by the factors such as the volume ratio of its components, radar frequency and pavement temperature. The compaction degree of asphalt mixture can be predicted by establishing a composite dielectric model, but its accuracy and application range still need to be improved. For the water-bearing asphalt mixture, the presence of water may cause the measured dielectric constant to be biased, thereby affecting the accuracy of density prediction. In the future, the signal processing method of GPR can be optimized to improve the detection accuracy of GPR on the dielectric constant of asphalt mixture. The composite dielectric model with a wide range of application is further established to improve the accuracy and scope of density prediction. The GPR and the road roller are combined to establish a complete real-time monitoring system for asphalt pavement compaction. References | Related Articles | Metrics

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Slope Stability Analysis on Relevance Vector Machine Based on Beetle Antennae Search Optimization Algorithm ZHANG Yan1,2, TANG Beichang1, MENG Qingpeng1,2 2024, 43(11): 11-17.  DOI: 10.3969/j.issn.1674-0696.2024.11.02 Abstract ( )   PDF (995KB) ( )   In order to predict slope stability quickly and accurately as well as control slope damage in time, a slope stability analysis model of relevance vector machine (RVM) based on beetle antennae search (BAS) optimization algorithm was proposed. Based on RVM model, the nonlinear mapping relationship between slope influence factors and stability was established. The parameters of RVM model were optimized by BAS algorithm, and an optimization model of RVM slope stability analysis based on BAS algorithm was proposed. The proposed model was applied to the slope stability analysis of Beijing-Urumqi expressway. The analysis results show that compared with the actual value, the maximum absolute relative error based on the BAS-RVM model is 3.90%. Under the same learning sample, compared with the RVM model, support vector machine (SVM) model and radical basis function (RBF) model, the BAS-RVM model has better reliability and fit, and higher accuracy in predicting results, whose mean absolute error (EMA), root mean square error (ERMS) and relative root mean square error (ERRMS) are much lower than those of other three kinds of models. References | Related Articles | Metrics

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Identification Method of Bridge Dynamic Characteristics Considering Environmental Factors LI Atan1, ZHU Yichen2, ZHANG Likui1, XIONG Wen2, ZHAO Xianmin1 2024, 43(11): 18-26.  DOI: 10.3969/j.issn.1674-0696.2024.11.03 Abstract ( )   PDF (3343KB) ( )   In long-term structural health monitoring (SHM), operational modal analysis (OMA) techniques are commonly used to identify the dynamic characteristics of structures, i.e., the bridge natural frequency and damping ratio. However, traditional operational modal analysis methods do not consider the effects of environmental changes, which can affect the accuracy of structural parameter identification. Data-driven models are capable of assessing and predicting environmental trends, but they can’t reflect the physical meaning of structural parameters. To address these issues, a method for identifying the dynamic characteristics of bridges considering environmental factors was proposed, which combined operational modal analysis with data-driven models to identify dynamic parameters while considering environmental changes. Bayesian probabilistic framework was employed and the uncertainty and correlation in the data were incorporated into the proposed model. The rationality of the proposed method was validated through a simulated data example and applied it to the suspension cable monitoring data of a large-span suspension bridge. The results show that the proposed method can provide more consistent modal parameter estimation under different temperature conditions, while the identified temperature-related parameters are all within the predicted 0.95 confidence interval and are consistent with the pre-discovered trends of temperature effects. It is illustrated that the proposed method can effectively identify the dynamic characteristics of bridges while considering environmental factors. References | Related Articles | Metrics

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Shrinkage and Creep Effect of Corrugated Steel Webs Cable-Stayed Bridge Based on Fine Model XU Shizhan, MA Haokai, MA Yinggang 2024, 43(11): 27-36.  DOI: 10.3969/j.issn.1674-0696.2024.11.04 Abstract ( )   PDF (3240KB) ( )   In order to overcome the defect of creep recovery after unloading in the calculation of concrete creep by using the age-adjusted effective modulus method, and solve the problem of the general calculation program such as ANSYS without a dedicated concrete creep analysis model, the calculation method of concrete creep based on the principle of effective modulus method adjusted by age to determine the creep coefficient was proposed. The formula for calculating the creep coefficient of concrete was derived, and a calculation program was developed. The effectiveness of the proposed calculation method was verified by combining existing theory and experimental data. The shrinkage and creep effects of a corrugated steel web box girder cable-stayed bridge without back cables were calculated. The results show that under the influence of shrinkage and creep effect, the internal force redistribution of the structure is obvious, and most structural responses have been fully developed to more than 60% of the 10-year incremental value within one year of completion of the bridge. Under the action of creep, the stresses gradually increases at the mid span bottom plate of the cable span, the bottom plate of the main beam root section, and the root position of the cable side of the main tower. The force safety issues at these locations should be focused on. References | Related Articles | Metrics

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Influence of Residual Stress on Buckling Performance of Bridge Corrugated Steel Webs ZHENG Shangmin, WU Zhiqiang 2024, 43(11): 37-42.  DOI: 10.3969/j.issn.1674-0696.2024.11.05 Abstract ( )   PDF (2397KB) ( )   A numerical analysis model of corrugated steel web considering residual stress was established based on finite element software for a 1200-type corrugated steel web bridge, in order to investigate the impact of residual stress on the buckling performance of corrugated steel webs of bridge. Considering the effect of residual stress on the buckling performance of corrugated steel webs, the simplified calculation method for the ultimate buckling load of corrugated steel webs considering the residual stress was proposed by analyzing the thickness, length-to-height ratio and the change of steel strength of the corrugated steel webs. The research results indicate that the residual stress reduces the ultimate buckling load of the corrugated steel web, which accelerates the failure speed of the corrugated steel web after buckling. As the thickness and steel strength increase, the sensitivity of the ultimate buckling load of the corrugated steel web to the residual stress shows an increasing trend. As the length-to-height ratio increases, the sensitivity of the ultimate buckling load of the corrugated steel web to the residual stress shows a decreasing trend. The reduction coefficient method can be used to calculate the effect of welding residual stress on the buckling performance of corrugated steel webs. References | Related Articles | Metrics

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Optimization of Airport Airside Towing Schedule Considering Time Cost ZHANG Yifan1, QIAO Guoxuan1, LI Ruyi2, GUAN Haohan2, LI Haifeng1 2024, 43(11): 43-51.  DOI: 10.3969/j.issn.1674-0696.2024.11.06 Abstract ( )   PDF (1240KB) ( )   Currently, large hub airports generally suffer from a shortage of contact gate resources and low towing efficiency, resulting in an inability to meet the actual demand for bridge rate. The fundamental reason is the lack of efficient and reasonable towing scheduling plans. To avoid problems such as unreasonable allocation of towing scheduling, low utilization of contact gate, and high comprehensive towing costs caused by manual towing scheduling at airports, an optimization method for towing scheduling considering time cost was proposed. Firstly, according to the actual operational data and business rules of airport, the factors such as the spatial distribution of gates and the cost of towing time were comprehensively taking into account, and the optimization goal was to improve the bridge rate and reduce the cost of towing time. Secondly, considering constraints such as towing effectiveness, towing volume during time period and flight supporting time window, a towing scheduling optimization model was established. Then tabu search algorithm was designed and improved to solve the proposed model. Finally, the effectiveness of using the proposed model to construct an airport towing scheduling scheme was verified by using actual historical flight data and gate scenarios from Beijing Daxing International Airport. The research results show that the proposed towing scheduling scheme can increase the bridge rate by 4.2%, reduce the towing time cost by 10.2%, and effectively improve the existing towing scheduling method. References | Related Articles | Metrics

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Multi-objective Route Planning for the Northwest Passage Based on the Improved A* Algorithm PAN Jiacai, LU Mengjie, YANG Chaopeng, WEI Kai, JIA Shihao 2024, 43(11): 52-59.  DOI: 10.3969/j.issn.1674-0696.2024.11.07 Abstract ( )   PDF (10840KB) ( )   Global warming has led to the melting of Arctic sea ice, and the number of ships carrying out commercial activities in the northwest passage is increasing. Aiming at the demand for safety and economy of ship navigation under complex ice conditions in the Arctic northwest passage, a multi-objective route planning model in ice area based on the dynamic weighted A* algorithm was constructed with full consideration of the sea ice characteristics, the ice-breaking capacity of ships and the actual navigation risks, and with the fuel consumption and voyage time of ships as the optimization objectives. A dynamic weighted A* algorithm considering the safety distance was proposed, and an exponential attenuation factor was introduced to adjust the search strategy of A* algorithm to reduce the unnecessary search space, and it was applied to the ice area route planning model for simulation analysis of northwest passage route planning. The results of simulation experiments show that the proposed method is able to plan a route with better fuel consumption and sailing time on the basis of ensuring the safety of ship navigation, which effectively solves the problem of safety distance between the ship and the coastline and the edge of the bad ice area, ensuring the safety of navigation in the ice area. References | Related Articles | Metrics

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Forecast of Cargo Throughput of Wenzhou Port Based on Grey Markov Model CHANG Yimei1, LIN Yiting1, DING Tianming2 2024, 43(11): 60-67.  DOI: 10.3969/j.issn.1674-0696.2024.11.08 Abstract ( )   PDF (690KB) ( )   Wenzhou Port is located in the middle of the golden coastline of the southeast coast. And in the past 40 years, Wenzhou Port has jumped from a single small port to be a major port along the coast of the country and an important hub of the national comprehensive transportation system, which has gradually integrated into global trade. In order to better help the relevant departments of Wenzhou Port and port enterprises to guide the port production operation and construction planning, a grey Markov-based port cargo throughput prediction model was firstly established to study the trend and change of cargo throughput in Wenzhou Port. Then, the established model was verified by the cargo throughput data of Wenzhou Port from 2002 to 2022. The results show that the optimized grey Markov prediction model is more accurate than the single grey prediction model, and the average relative error of the optimized model is about 2.1%. Finally, the port cargo throughput of Wenzhou Port from 2023 to 2027 is predicted. The forecast results show that the cargo throughput of Wenzhou Port shows a fluctuating upward trend year by year, which will greatly affect the strategic positioning and long-term development planning of Wenzhou Port and further promote the construction of the collection and distribution system, the construction of deep-water berths and the level of port radiation network of Wenzhou Port. References | Related Articles | Metrics

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Energy-Saving Optimization of High-Speed Train Operation Curve Based on IWOA HOU Tao, ZHOU Wenqi 2024, 43(11): 68-75.  DOI: 10.3969/j.issn.1674-0696.2024.11.09 Abstract ( )   PDF (909KB) ( )   In order to reduce the energy consumption of high-speed train operation and make the calculation of the additional resistance of the train passing through the point of variable slope and variable curvature more accurate and closer to the reality, an improved whale optimization algorithm (IWOA) was put forward to optimize the energy saving of high-speed trains operation curve. Firstly, the multi-mass additional resistance model of high-speed train was established. Secondly, the influence of full load rate on the energy consumption of train operation was considered, and a new energy consumption model was constructed with ontime, punctuality, and speedlimit as the constraints. Thirdly, the optimal position of the intermediate line traction-inert condition transition point was searched by IWOA. IWOA introduced the chaotic mapping strategy, the self-adaptive convergence factor and the Harris Hawk siege mechanism, which could effectively improve the convergence speed and optimization accuracy of the algorithm, and its global search capability was greatly enhanced, so as to achieve the purpose of further energy-saving operation of high-speed trains. Finally, the simulation was carried out based on the MATLAB platform with the parameters of the Hefei Station-Bengbu Station line and the parameters of the CRH3 high-speed train as examples. The simulation results show that the PSO, GA algorithms and IWOA are used to optimize the energy saving of high-speed train operation curves, and the optimized curves reduce the energy consumption of train operation by 7.81%, 10.16% and 15.95% respectively. Therefore, the effect of IWOA on train energy saving optimization is more obvious. References | Related Articles | Metrics

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Optimization Model of Emergency Medical Material Delivery Path under sudden Public Health Emergencies CHEN Chao, WANG Jiamiao, MA Xinsheng 2024, 43(11): 76-83.  DOI: 10.3969/j.issn.1674-0696.2024.11.10 Abstract ( )   PDF (853KB) ( )   A more widely applicable optimization model for the distribution path of emergency medical material was reconstructed, which could be quickly applied to the path planning of urban emergency medical material distribution in sudden public health emergencies. The marginal contribution of the new model was reflected in the following two aspects. Firstly, in the case of joint distribution by multiple distribution centers, the three most important goals of emergency medical material distribution, namely the shortest distribution path, the lowest total cost and the minimum unmet degree of urgent needs, were simultaneously considered. Secondly, the parameters of the emergency medical material distribution path model were updated, which was mainly reflected in the use of a relatively mature emergency medical material demand urgency evaluation index system, the use of the metabolic GM (1,1) model to predict the number of infections, the use of analytic hierarchy process and entropy method to determine weights, and the use of the grey correlation degree TOPSIS method to calculate the emergency medical material demand urgency. Finally, the new model was verified by taking the emergency medical material dispatch after the COVID-19 in Xi’an as an example, the NSGA-Ⅱ algorithm was used to solve the proposed model. Eight vehicle optimal routes for emergency medical supplies distribution in Xi’an were determined. References | Related Articles | Metrics

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Proactive Electric Vehicle Routing Problem Based on Consumer Behavior Prediction GE Xianlong1, JIANG Yunyun1, YIN Qiushuang1, YANG Yushu2 2024, 43(11): 84-94.  DOI: 10.3969/j.issn.1674-0696.2024.11.11 Abstract ( )   PDF (3053KB) ( )   Under the requirement of massive, dispersed, and randomly arrived e-commerce logistics orders, a proactive logistics service mode based on demand prediction was proposed. The product attributes, user behaviors, customer interaction characteristics and other behavior trajectory data were combined to predict the potential purchasing intentions of customers, and the predicted order demands was advanced to customers’ nearest warehouse. Therefore, a two-echelon electric vehicle network optimization model of “central depot to forward center to customer” was established. Given the complexity of the problem, a two-stage hybrid heuristic intelligent optimization algorithm was designed. In the first stage, a two-edge successive correction method was used to obtain the initial solution, and in the second stage, a hybrid simulated genetic algorithm was designed to iteratively optimize the initial solution. The experimental results show that the total transportation distance and total cost of the first level network for proactive delivery are reduced by 106% and 101%, respectively, while the total cost of the second level network is increased by only 9%. References | Related Articles | Metrics

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Phased Dynamic Trajectory Control Method for Mixed-Connected Vehicles in Urban Road Networks ZHAO Xin1, 2, MA Jiabao1, 2, ZHOU Shuhan1, 2, YUAN Wang1,2 2024, 43(11): 95-102.  DOI: 10.3969/j.issn.1674-0696.2024.11.12 Abstract ( )   PDF (3531KB) ( )   As urban development progresses, the connected and autonomous vehicles (CAVs) are gradually replacing some human-driven vehicles (HDVs) on road segments. However, HDVs will not be completely replaced in the foreseeable future. Therefore, the mixed traffic environment of CAVs and HDVs that has emerged at this time is the driving environment we are currently facing and will face in the future. The driving behavior of CAVs and HDVs interferes with each other on road sections, resulting in low efficiency of hybrid driving. In order to mitigate the interaction between CAVs and HDVs, a phased dynamic lane guidance algorithm for separating CAVs and HDVs in mixed traffic environments (SCHME) was proposed. The proposed algorithm separated the mixed flow vehicle set in the upstream section of the intersection, adjusted the driving routes of CAVs and performed real-time dynamic updates. Under the condition of meeting kinematic constraint and convergence, HDVs adjusted the routes according to the dynamic routes of CAVs, achieving an increase in vehicle operating efficiency in mixed driving environments within the road section under the condition of the minimum generalized safety loss cost for each vehicle. The operating state of vehicle before entering the intersection was simulated by MATLAB. It is concluded that the SCHME algorithm can improve the average vehicle traffic efficiency within a road section by 17% under the condition of the minimum generalized safety loss cost. At the same time, when the vehicle optimization array is larger and the vehicle set is farther away from the intersection, the lower the penetration rate of CAVs, the lower the generalized safety loss cost per vehicle. References | Related Articles | Metrics

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Intelligent Vehicle Path Tracking Control Considering Variable Universe Fuzzy Steering Angle Compensation and Network Time Delay ZHANG Jie1,3, LIN Hua2, GAO Jianjie3, ZHOU Xingxing4, ZHOU Junchao5 2024, 43(11): 103-113.  DOI: 10.3969/j.issn.1674-0696.2024.11.13 Abstract ( )   PDF (3437KB) ( )   In intelligent vehicle path tracking control system, the network time delay will directly affect the control performance of the controller and reduce the stability of vehicle driving. Meanwhile, the intelligent vehicle path tracking control usually does not consider the future road curvature and expected speed information, resulting in poor control accuracy. To improve the stability and control accuracy of intelligent vehicles in path tracking, a state feedback controller with time delay control was designed for intelligent vehicle path tracking control systems with network time delay, and a design method for feedforward steering angle compensation controller based on variable universe fuzzy control was proposed. Firstly, the Frenet coordinate system principle was applied to complete the kinematic and three degree of freedom dynamic modeling of intelligent vehicles, meanwhile, a T-S fuzzy method was used to linearize the model for the time-varying parameters of the system. Secondly, an H∞ state feedback controller with time delay control was designed to handle with the network transmission delay existing in the controller input. Finally, in order to improve the accuracy of steering control, a variable universe fuzzy control was designed with vehicle speed and road curvature as inputs for feedforward steering angle compensation. The results show that compared with the traditional control method, the proposed control method can improve the stability and control accuracy of vehicle path tracking control under the condition of time delay and achieve the better path following performance, by controlling the transmission delay and incorporating variable universe feedforward fuzzy steering angle compensation. References | Related Articles | Metrics

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Optimization of Semi-active Suspensions Skyhook Control Algorithm Based on Response Surface Methodology RONG Bing 2024, 43(11): 114-121.  DOI: 10.3969/j.issn.1674-0696.2024.11.14 Abstract ( )   PDF (3449KB) ( )   The damping control co-simulation model for the semi-active suspension of the entire vehicle was established, based on continuous skyhook control algorithm within the adjustable damping coefficient range of CDC shock absorbers and vehicle muti-body dynamics model. To optimize the damping coefficient of the front and rear suspension skyhook of the control algorithm, the comprehensive evaluation index was established to balance ride comfort and handling stability, which was consisted of suspension vibration isolation index for continuous small and medium-sized excitations, suspension vibration reduction index for single pulse excitations, and suspension response index for angular step excitations. Secondly, the central composite bounded design was adopted to define DOE strategy, and a quadratic response surface model between the optimization variables and the comprehensive evaluation index was constructed by simulating and calculating the comprehensive evaluation index. The optimization objective was to minimize the comprehensive evaluation index, and the damping coefficients of the front and rear suspension skyhook after optimization were 5.39 and 3.61 Ns/mm, respectively. Finally, the proposed method was verified by simulation and comparison. It is verified that the optimized continuous skyhook control algorithm can significantly improve ride comfort on the premise of ensuring handling stability equivalent to passive suspension. Under continuous small and medium excitation, the suspension vibration isolation comfort is improved by 20.44%, and under single pulse excitation, the suspension impact comfort is improved by 56.67%. References | Related Articles | Metrics

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Design of Integrated Controller for Anti-rollover Trajectory Tracking of Intelligent Commercial Vehicles FENG Ying, QIAO Baoshan, YUAN Xianju, DENG Zhaowen 2024, 43(11): 122-129.  DOI: 10.3969/j.issn.1674-0696.2024.11.15 Abstract ( )   PDF (2042KB) ( )   A tracking integrated controller that could predict and control the anti-rollover trajectory was designed to address the high center of gravity and inertia of intelligent commercial vehicles, which were prone to rollover during curved driving. The vehicle trajectory was tracked and controlled by the active steering system, based on model predictive control (MPC) principle, and the rollover motion status of vehicles was monitored by use of the predictive function of MPC. The equivalent lateral load transfer rate was used as a trigger signal, if it was less than the threshold, the anti-rollover active suspension control would not work; on the contrary, active suspension control would be activated to prevent rollover. The co-simulation of vehicle typical working conditions was carried out by MATLAB/Simulink and Trucksim software. The research results demonstrate that the proposed anti-rollover trajectory tracking system can ensure the tracking accuracy of the vehicle and effectively avoid rollover accidents. References | Related Articles | Metrics

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Blast Hole Identification Method Based on CE-YOLOv8 HU Qiguo1, LIU Yang1, YU Penglin1, REN Yurong1, YU Xun2 2024, 43(11): 130-138.  DOI: 10.3969/j.issn.1674-0696.2024.11.16 Abstract ( )   PDF (13732KB) ( )   In order to realize the automatic loading of explosives in engineering blasting, the pre-task of blast hole detection was studied. Due to the problems of different hole shapes, many gravels and complex detection backgrounds in the actual engineering, which were prone to omissions and misjudgments in the detection process. Therefore, a more efficient blast hole detection method CE-YOLOv8 was proposed on the improvement of YOLOv8. Firstly, the C2f module in the backbone network was replaced by a C2f_DCN module, increasing the spatial deformation adaptability of the network, so that the features of the blast hole could be extracted more accurately and the detection accuracy of the blast hole can be improved. Secondly, the improved attention mechanism C-CBAM was added into the YOLOv8 feature extraction network, the input features of the CBAM attention mechanism were grouped, and a parallel branch was added to realize multi-scale feature processing. The information was fused through the cross-space learning module to improve the receptive field and representation ability of the model. Finally, E-IOU was introduced as a calculation method to evaluate the correlation between anchor boxes, which overcame the shortcomings of traditional IOU in gradient transfer and accelerated the convergence of the network. The experimental results show that the improved model has a good identification effect on blast holes, in which the mean average Precision (mAP) is increased to 98.6%, and the Precision and Recall reaches 95.7% and 96.1%, respectively. The improved method has a wide application prospect for identifying blast holes in blasting engineering, so as to realize intelligent explosive loading. References | Related Articles | Metrics