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20 February 2024, Volume 43 Issue 2 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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Influence of Flange Size on Flexural Behavior of Geopolymer Concrete T-BeamsXU Yong1, 2, 3, MAO Yuguang1, 2, 3, LIU Yiwei1, 2, 3, SU Jie1, 2, 3, DU Yunxing1, 2, 3, SHI Caijun1, 2, 3 2024, 43(2): 1-9.  DOI: 10.3969/j.issn.1674-0696.2024.02.01 Abstract ( )   PDF (3281KB) ( )   The influence of flange width and thickness on the flexural behavior of geopolymer concrete T-beams was investigated by the four-point bending test of five geopolymer concrete T-beams with different flange sizes and one ordinary concrete T-beam. Meanwhile, the difference between geopolymer concrete and ordinary concrete T-beam were evaluated. The results show that the flexural ultimate load, yield load, crack behavior and failure mode of geopolymer concrete T-beams are similar to those of ordinary concrete T-beams. The ductility of geopolymer concrete T-beam is better than that of ordinary concrete T-beam. However, the strain of the longitudinal reinforcement in mid span tension is relatively larger, and the stiffness, crack loading, and bearing capacity of geopolymer concrete T-beam under the maximum crack width limit are relatively lower. As the flange width increases from 200 mm to 500 mm, the stiffness, yield load, flexural ultimate load, ductility, and bearing capacity under the maximum crack width limit of the geopolymer concrete T-beam all increase. The strain of the tensile longitudinal reinforcement at the mid span decreases, and there is no significant change in cracking load. However, the wider the flange width, only a part of the width close to the web can effectively bear the load. The effect of increasing flange thickness on the flexural behavior of geopolymer concrete T-beams is basically the same as that of increasing flange width. However, its effect on improving the bearing capacity under the maximum crack width limit is significant. The design formulas for the normal section flexural bearing capacity of GB 50010—2010 and ACI 318—19 are applicable to geopolymer concrete T-beams. The prediction of GB 50010—2010 is more accurate, and the safety reserve of ACI 318—19 is higher. References | Related Articles | Metrics

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Stress Detection Method of Steel Strand Based on Permanent Magnet Effect YUAN Feiyun1,3, YAN Hongguang3, YANG Yuedong4, ZHANG Benniu2, JIANG Haifei2 2024, 43(2): 10-16.  DOI: 10.3969/j.issn.1674-0696.2024.02.02 Abstract ( )   PDF (739KB) ( )   A new method for nondestructive stress detection of steel strand was proposed based on the permanent magnet effect. Based on the molecular circulation model of permanent magnet, the magnetic field intensity distribution of rectangular permanent magnet was derived, and a force-magnetic relationship theoretical model that reflected the stress on steel strands and the magnetic induction strength of permanent magnets inside the sensor was established. Ansys Maxwell electromagnetic finite element software was used to carry out numerical analysis on the proposed force-magnetic relationship theoretical model. The results show that there is a functional correspondence between the force state of the steel strand and the magnetic induction strength of the permanent magnet. Taking the midpoint of the axis as the origin, the initial magnetic strength value at the origin is the highest. At this time, the strain and stress of the steel strand increase, and the magnetic strength value gradually decreases along both sides according to a certain pattern. Thereby, a new type of stress detection sensing structure was proposed, and an experimental verification platform was built. Experimental data analysis shows that under multiple loading and unloading cycles, the magnetic flux decreases with the increase of stress during loading and increases with decrease of stress during unloading. Both the linear function and the quadratic function can well describe the interrelationship between magnetic induction intensity and stress-strain values, which verifies the feasibility and effectiveness of the proposed detection theory and sensing structure. References | Related Articles | Metrics

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Reliability Analysis of Permanent Pavement Structure Based on Truncated Distribution WANG Guoqing1，ZHANG Quan2,3，HE Zhaoyi3，QIN Lusheng1，QIU Wenli1 2024, 43(2): 17-23.  DOI: 10.3969/j.issn.1674-0696.2024.02.03 Abstract ( )   PDF (671KB) ( )   In order to establish a reliability analysis method for permanent pavement structures based on the variability range of the measured parameters, firstly, a double-sided truncated distribution random number sampling method with parameter boundedness was established, which was based on the principles of probability equivalence and inverse transformation method. Secondly, limit state equations were established and a multi-indicator reliability calculation program was developed by selecting the verification indicators of surface layer, base layer, and subgrade structure in the current asphalt pavement design specifications. The analysis results were compared with the reliability program of theoretical distribution random variables. Finally, combined with the measured parameter variability level, the established reliability analysis method was used to evaluate the post-construction reliability of the permanent pavement structure of the Jing-De Expressway. The results show that the truncated distribution better conforms to the actual distribution of engineering parameters, and the calculated reliability is more accurate. Under moderate traffic load levels, the reliability of the Jing-De Expressway pavement structure ranges from 95.2 to 98.7%. After accumulating equivalent axle load cycle failure points, the reliability values of the surface layer, base layer, and subgrade of the permanent pavement structure all decrease with the increase of axle load cycles, and the greater the load, the faster the rate of reliability value decrease, and the lower the reliability. References | Related Articles | Metrics

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Laser-Constrained Binocular Robust Algorithm for Measuring 3D Texture of Pavement WANG Yuanyuan1,LI Renjie2,LIU Yanyan3,ZHANG Hengtong2,LIU Dezheng2 2024, 43(2): 24-29.  DOI: 10.3969/j.issn.1674-0696.2024.02.04 Abstract ( )   PDF (3218KB) ( )   In order to improve the universality of the laser-constrained binocular reconstruction algorithm to measure the three-dimensional texture of the road surface, enhance the anti-light interference ability of the algorithm, and solve the problem of robust extraction under the changing illumination of the laser-constrained target, a laser-constraint recognition model was established based on Faster-RCNN (faster-region based convolutional neural network). The artificially constructed laser-constraint targets were extracted within the illumination range of 5~1 050 lux, the sub-region segmentation of the constrained target to be tested was carried out, and the binocular 3D reconstruction under the stereo matching of sub-region segmentation was realized. The results show that the fitting coefficient of the mean texture depth measurement values of the improved algorithm and the sand paving method under the illumination intensity of 1 050 lux is 0.987, which is better than 0.887 of the original laser-constrained binocular reconstruction algorithm. The maximum fluctuation error and the average fluctuation error of the improved algorithm in the illumination range of 5~1 050 lux are 0.141 mm and 0.084 mm respectively, which are 70.20% and 76.83% lower than the original laser-constrained binocular reconstruction algorithm respectively. References | Related Articles | Metrics

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Research Progress of the Impact of Urban Sprawl on the Ecosystem Service Flows and Implications for the Yangtze River Basin, China GUAN Dongjie1,2, HE Xiujuan1,3, ZHOU Lilei1 2024, 43(2): 30-39.  DOI: 10.3969/j.issn.1674-0696.2024.02.05 Abstract ( )   PDF (2839KB) ( )   A comprehensive review of the current research status on the impact of urban sprawl on ecosystem service flows is conducive to promoting the sustainable social and economic development of regions. The research on the impact of urban sprawl on ecosystem service flow was summarized. The results show that the research on the impact of urban sprawl on ecosystem service flows is still in its infancy. Urban sprawl changes the flow, velocity, and direction of ecosystem service flows through both carrier transmission and flow paths, leading to a decrease in the total amount of ecosystem service flows and an increase in spatial heterogeneity. The single index change, scale, and multi-scenario simulation of urban sprawl are the main entry points to explore the impact process of urban sprawl on ecosystem service flows. The diffusion effect of ecosystem service flows caused by urban sprawl mainly stems from changes in land use types and changes in human living patterns. Previous studies have to some extent explained the impact of urban sprawl on ecosystem service flows, but there is still a significant gap in revealing the impact mechanism, analyzing the impact process, evaluating the impact effects and exploring the rational allocation of ecosystem service flows to promote sustainable urban development. Under this premise, a research framework for the impact of urban sprawl in the Yangtze River Basin on ecosystem service flows should be established based on the research approach of “mechanism revelation-impact simulation-effect evaluation” in the future. And the sustainable development of cities in the Yangtze River Basin and a reasonable allocation plan for ecosystem service flow should be explored, to realize coordinated progress between ecological protection and social development in the Yangtze River Basin. References | Related Articles | Metrics

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Choice Behavior of Shared Parking Based on Structural Equation Model SONG Rui1, QIN Wanyi1, SHI Wen1, XUE Xingjian2 2024, 43(2): 40-47.  DOI: 10.3969/j.issn.1674-0696.2024.02.06 Abstract ( )   PDF (936KB) ( )   Shared parking is of great significance in solving the problem of urban traffic parking. To analyze the factors influencing the choice behavior of urban shared parking users, a hybrid-based multinomial choice model was constructed. The upper layer of the proposed model extended the technology acceptance model by introducing three latent variables such as the perceived risk, knowledge level and service quality. The structural equation model was used to analyze the structural relationship and path significance between each latent variable and verify the hypotheses proposed by the model. The latent variables and social attribute variables estimated by the upper level were brought into the lower-level multinomial Logit model and the model parameters were also calibrated. The research results show that the latent variables of parking users, the personal and household attributes and the parking characteristics all have significant influence on users' choice of shared parking. Compared to roadside parking, shared parking is more attractive to users in terms of service quality and safety, but its advantages are not obvious compared to the specialized public parking lots. References | Related Articles | Metrics

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Vehicle Driving Intention Recognition Model Based on Taillight Status in Mixed Traffic Flow ZHAO Shuen, ZHAO Dongyu 2024, 43(2): 48-56.  DOI: 10.3969/j.issn.1674-0696.2024.02.07 Abstract ( )   PDF (5649KB) ( )   In view of the existing traffic situation of hybrid driving of autonomous vehicle (AV) and human-driven vehicle (HV) for a long time, a vehicle driving intention recognition model based on the taillight status in mixed traffic environment was proposed by combining deep learning and HSV color characteristic extraction method. The proposed model was limited by the region of interest (RoI) area detected by the Mask R-CNN vehicle detection model, and HV in this area was taken as the research object. According to the correlation of taillight positions, vertical and horizontal constraints were added in the rear area of HV to locate the taillights which transmitted the signal of light status. A taillight status recognition algorithm based on time sequence was proposed on the basis of the specified combination of light status and the flashing frequency of turn signals. The CSRT (channel and spatial relatability tracking) was used to track HV taillights and count the timing status of taillights. With the dynamical lights status as input, a driving intention recognition model based on taillight status was constructed. The Cityspaces dataset and traffic flow video data based on real road conditions were used to train, validate and test the proposed model. The research results show that the accuracy and recall rate for video stream vehicle taillight detection of the driving intention recognition model based on the taillight status are 96.0% and 98.2% respectively, the average accuracy rate of the driving intention recognition reaches 95.9%, and the recognition time of single frame is 20 ms. The proposed method provides an effective theoretical basis for AV decision-making and planning in high-speed mixed traffic environments. References | Related Articles | Metrics

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A Lightweight Driver Distraction Behavior Detection Method Based on BiViTNet GAO Shangbing1,2, ZHANG Yingying1,2, WANG Teng1,2, ZHANG Qintao1, LIU Yu1 2024, 43(2): 57-64.  DOI: 10.3969/j.issn.1674-0696.2024.02.08 Abstract ( )   PDF (1234KB) ( )   To address the issues of complex models, low detection efficiency, and lack of global visual representation in driver distraction behavior detection based on convolutional neural networks, a bidirectional interaction neural network based on vision transformer (BiViTNet) was proposed to identify driver behavior. ViT (vision transformer) was introduced into the network to encode global information, which could improve the detection accuracy to a certain extent. The proposed network consisted of two parallel branches, and the first one was based on the lightweight CNN structure and the second one was based on the ViT structure. The bidirectional feature interaction module (BiFIM) was used to solve the problem of feature asymmetry between CNN branch and ViT branch. Finally, the features of the two branches were fused and driver behaviors were detected. The experiment was carried out on the self-built multi-view driver dataset. The accuracy of the verification set reached 97.18%, the parameter quantity was 38.22 MB, and the MAdds was 271.20×106. The research shows that lightweight BiViTNet improves the accuracy of drivers distracted behavior identification and can assist drivers driving safety to a certain extent. References | Related Articles | Metrics

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Analysis of Driving Safety on Prairie Highway Based on Visual Information Processing WANG Haixiao，DING Xu，GUO Min，LYU Zhen 2024, 43(2): 65-74.  DOI: 10.3969/j.issn.1674-0696.2024.02.09 Abstract ( )   PDF (1299KB) ( )   In order to explore the difference in drivers visual information processing modes in each typical driving environment on prairie highway and analyze the driving safety on prairie highway from the visual level, the real vehicle experiment on prairie highway was conducted based on the eye tracker. The eye movement data of drivers in six real traffic environments were extracted, including free driving, vehicle-following, oncoming vehicles, rear vehicles cut-in, roadside risks and intersections. Firstly, the evaluation indicator system was constructed from two dimensions: visual allocation and visual search. The dynamic clustering method was used to divide the drivers visual area of interest into five categories, and the information entropy was combined with the Markov chain stationary distribution theory to construct the information entropy of fixation point distribution to quantify the complexity of the drivers visual attention allocation. Then the saccade amplitude and saccade velocity were introduced to analyze the drivers search process for visual information. Finally, the weighted rank-sum ratio evaluation model based on the CRITIC method was constructed to comprehensively evaluate the visual information processing intensity of drivers in different driving environments. The results show that the distribution of drivers fixation points varies in different driving environments, but the current lane is always the main viewing area for drivers to obtain visual information. The visual evaluation indicators show significant statistical differences with the change in the driving environment. When drivers encounter roadside risks, the visual information processing intensity is the largest, and the driving safety is relatively lower. References | Related Articles | Metrics

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Safe Speed Model of Passenger Cars on Bends in Rainy Days Considering Braking, Load Transfer and Longitudinal Slope XU Jinliang1, ZENG Zhuo1, MU Minghao2, E Guangxun2 2024, 43(2): 75-83.  DOI: 10.3969/j.issn.1674-0696.2024.02.10 Abstract ( )   PDF (655KB) ( )   In order to determine the safe speed of a passenger car on bends in rainy environments, a sideslip speed model considering longitudinal slope, braking acceleration and tire load transfer was established based on the instantaneous axis. The friction coefficients under different water film thickness were collected on the spot, and the regression equation between them was obtained. Combined with the principle of friction ellipse, a comprehensive friction coefficient distribution method considering braking and driver behavior characteristics was obtained. The calculation flow chart for determining the speed on bends was proposed, and the vehicle speed on bends with lateral sideslip and longitudinal parking as indicators under different rainfall intensities was obtained. The research results show that when the water film thickness is 0, the obtained sideslip velocity value is about 35% lower than that of the point mass model. When the water film thickness is less than 2 mm, the friction coefficient decreases fastest and has the greatest influence on the vehicle speed. When the water film thickness is greater than 2 mm, the friction coefficient changes little, and its law is not obvious. Rainfall has a significant impact on the safe speed of passenger cars on curves, and the average speed is reduced by about 15 % when only light rain occurs. When the general minimum radius is used to calculate, the longitudinal parking speed is all smaller than the lateral sideslip speed under different rainfall intensities. References | Related Articles | Metrics

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Safety Test and Evaluation Method for Autonomous Vehicles Based on Ramp Merging Data LI Wenli1,2, LI Chao1, LI Zhongfeng1, YI Fan1, LI An1 2024, 43(2): 84-91.  DOI: 10.3969/j.issn.1674-0696.2024.02.11 Abstract ( )   PDF (1062KB) ( )   Aiming at the problems such as unclear test scenarios of autonomous vehicle and strong subjectivity of evaluation models, the extraction method of typical test scene and objective evaluation method of autonomous vehicle on-ramp import safety under high-speed on-ramp import scenario were studied. The logical scene elements in ramp import function scenario were analyzed in depth. The logical scene elements in natural driving data, such as speed of the ego vehicle, distance between vehicles and front vehicle speed were clustered, and two typical ramp import test scenarios were obtained to carry out the simulation test of autonomous vehicles. At the same time, a multi-level autonomous vehicle evaluation system was constructed. A kernel density estimation model based on natural driving data was introduced to obtain the optimal threshold of indicators, and a gray relevance theory evaluation model was established with the optimal threshold as the reference sequence and the analytic hierarchy process (AHP) and objective weighting method (CRITIC) as the weight input. Objective evaluation of the safety of autonomous vehicle during the import process was carried out. The evaluation results show that the similarity between the evaluation results of grey correlation theory model based on kernel density estimation and the evaluation results of subjective fuzzy comprehensive analysis model is 98.01%, which verifies the effectiveness of the objective model. References | Related Articles | Metrics

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Short-Term Inbound Passenger Flow Prediction of Model Rail Transit Based on Combined Deep Learning LI Shuqing, LI Wei, LIU Yaohong, MA Bo 2024, 43(2): 92-99.  DOI: 10.3969/j.issn.1674-0696.2024.02.12 Abstract ( )   PDF (1854KB) ( )   Aiming at the problem of low prediction accuracy caused by incomplete consideration of factors and feature learning in the short-term inbound passenger flow prediction model of rail transit, a combined deep learning model based short-term inbound passenger flow prediction method for rail transit (CNN ResNet BiLSTM) was proposed by selecting multiple factors such as passenger flow characteristics, weather, air quality and road traffic congestion index. The multi-factor passenger flow time series were automatically extracted based on convolution neural network (CNN), and several residual neural networks (ResNet) were added into the CNN network to deepen the depth of the network. The bidirectional long short-term memory neural network (BiLSTM) was used to capture the time series characteristics of passenger flow in bidirectional directions and obtain the prediction results. The validity of the proposed prediction method was verified by a case study on the inbound passenger flow predication of 80 stations in whole network of Hangzhou city on workdays. The research results show that the root mean square error (ERMS) of the multi-factor CNN-ResNet-BiLSTM combined model is reduced by at least 8.50%, and the mean absolute error (EMA) is reduced by at least 6.74% and the mean absolute percentage error (EMPA) is reduced by at least 6.52%, compared with the several commonly used models. References | Related Articles | Metrics

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Layout of Taxi Comprehensive Service Area Based on Passenger Flow Centrality XIAO Yun，LI Jiaxin, CHENG Xuzhi 2024, 43(2): 100-106.  DOI: 10.3969/j.issn.1674-0696.2024.02.13 Abstract ( )   PDF (876KB) ( )   Taxi comprehensive service area is a comprehensive service platform for cruise and online taxi hailing drivers. The passenger flow centrality reflects the density and importance of regional passenger flow, which is an important basis for the the site selection of comprehensive service areas. Based on the Beidou satellite positioning data of taxis in Huangshan City, the driving track of taxis carrying passengers was analyzed. Through stratified sampling survey, the passenger carrying coefficients in different time periods were calculated, and the scale and distribution characteristics of taxi passenger flow under different spatial and temporal conditions were analyzed. The topology structure of urban passenger transport network was studied. A passenger flow centrality identification model based on the coefficient of variation superiority and inferiority solution distance algorithm was constructed by combining four indexes such as degree centrality, close centrality, betweenness centrality and passenger flow intensity. The layout method for the taxi comprehensive service area was proposed, and the scientificity of the layout was verified according to the principle of maximum passenger flow coverage. References | Related Articles | Metrics

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Reliability Analysis of Urban Rail Vehicle Gear Wear Considering Corrosion XU Xiangyang1, CHEN Qingke1 ,WANG Han1, REN Ziyuan1 2024, 43(2): 107-114.  DOI: 10.3969/j.issn.1674-0696.2024.02.14 Abstract ( )   PDF (1322KB) ( )   In order to solve the problem of wear reliability prediction of gears in urban rail vehicles in corrosive environment, the nonhomogeneous Poisson process and the logarithmic Gaussian distribution were adopted to characterize the initiation and growth of corrosion pits on the tooth face. And then, considering the change of the wear and tear on the depth of corrosion pit, the maximum cumulative wear depth was taken as key parameter to establish the performance margin degradation model based on Archard wear theory, by analyzing the influence of corrosion pit on the Hertz contact stress and the tooth surface roughness. A reliability analysis model of gear wear of urban rail vehicles considering corrosion was constructed, and the reliability sensitivity analysis of parameters involved in corrosion process was also carried out. The results show that with the increase of working time, the uncertainty of cumulative gear wear increases, and the influence of corrosion on gear wear reliability decreases. The sensitivity of the proportion parameter, shape parameter and maximum corrosion depth in the corrosion pit growth process to the reliability increases in turn, and all of them are negatively correlated with the reliable life of gear wear. References | Related Articles | Metrics

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Path Planning Method of Autonomously Driving Vehicle Based on Adaptive A* Algorithm ZHANG Yong, CHENG Haifei, ZHAO Fengkui 2024, 43(2): 115-121.  DOI: 10.3969/j.issn.1674-0696.2024.02.15 Abstract ( )   PDF (1494KB) ( )   When using the traditional A* algorithm for path planning, there are problems such as too many turning points, poor search efficiency and too large turning angle. Therefore, a path planning algorithm for autonomously driving vehicles based on the adaptive A* algorithm was proposed. First of all, in view of the long operation time of the traditional A* algorithm, the exponential growth method was used to weight the heuristic function, so as to improve the search efficiency. Then, the heading angle influence factor was introduced into the heuristic function, so that autonomously driving vehicles could meet the steering characteristics when working. Finally, through the cubic B-spline interpolation function, the inflection point in the path was smoothed, so that the local path with sharp corners at the inflection point is smoother. The MATLAB simulation results show that the performance indexes of the path generated by the improved A* algorithm are better than those of the traditional A* algorithm in terms of length, total heading angle and curve smoothness, so that the autonomously driving vehicle can obtain a high-quality path that satisfies its own constraints. Moreover, under different map environments, the proposed adaptive A* algorithm can adapt to different environments and can effectively maintain its feasibility and superiority. References | Related Articles | Metrics

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A Modeling Method of Three-Dimensional Dynamic Safety Zone for Inland LNG Ships Based on Speed Characteristics CHEN Lijia1,2, WANG Bing1,2, WU Xiaohong1,2, LI Shengwei1 2024, 43(2): 122-130.  DOI: 10.3969/j.issn.1674-0696.2024.02.16 Abstract ( )   PDF (1389KB) ( )   In order to improve the scientificity of LNG ship safety zone setting and ensure the navigation safety of LNG ships in inland waterway, a three-dimensional dynamic safety zone modeling method for inland LNG ships based on speed characteristics was proposed. Based on the characteristics of LNG ship navigation direction and speed changes, the traditional linear distribution model of speed was improved to be a random distribution model. Then, by using the domain decomposition method, the complex three-dimensional geometric region was decomposed into several sub-regions to establish the corresponding boundary equations. Based on the limit between ships, constraint conditions were set, and according to their geometric shape, the safety distance of the internal structure of the safety zone in different directions was numerically solved by using the stopping sight distance theory, the ship drift calculation method and the surplus water depth calculation method. For a certain inland LNG ship, the simulation verification was carried out by setting different speed conditions. The research results show that the proposed model can correctly reflect the difference change of ship safety zone under the influence of speed and play a reference role for inland LNG ship route planning. References | Related Articles | Metrics