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2024, Volume 42,  Issue 3

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A Risk Assessment Method of Multi-aircraft Interaction for Complex Airspace
AI Yi, WAN Qifeng, HAN Xun, LI Yueyang, YU Yingxue, CONG Wei
2024, 42(3): 1-10. doi: 10.3963/j.jssn.1674-4861.2024.03.001
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To assess the interaction risks among multiple aircraft in complex traffic scenarios, a concept of "interac-tion potential fields of multiple aircraft and airspace environment" is developed, which is based on the similarity be-tween traffic risk and potential field theory. The interaction potential fields (IPF) generated by aircraft, critical air-space points (CAPs) and air routes (ARs) are defined, respectively, and the generation functions of IPFs are formu-lated. Considering the short-term effects of historical trajectories on the aircraft, a time-varying historical trajectory IPF is added to the real-time aircraft IPFs; considering the requirement of safety intervals in horizontal and vertical dimensions for aircraft, the parameters of rule-compliant IPFs are found; then, a fusion method is developed to integrate IPFs generated by aircraft, CAPs and ARs. Inspired by the relationship between potential field force and poten-tial energy, a potential energy-based risk index is introduced, denoted as RPE, showing the changes of risk over time in multi-aircraft scenarios from the perspective of energy. To validate the effectiveness of the proposed method, a simulation based on a real airspace section is introduced, and the results show that: ① RPE is much closer to the precepted risk by the air traffic operators (RSE) compared with traditional risk indicators; ② RPE is more sensitive at certain intervals than the conflict time-based index RATSR, with a mean absolute error of 0.077. In brief, the pro-posed risk assessment method could offer more precise decision support for risk management in complex air traffic scenarios in the future.
An Analysis of Safety Influencing Factors for Longitudinal Interaction Between Vehicles in Human-machine Mixed Traffic Driving Conditions
WANG Yiyun, YU Rongjie
2024, 42(3): 11-19. doi: 10.3963/j.jssn.1674-4861.2024.03.002
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Autonomous vehicles are gradually introduced to the existing traffic environment, leading to a mixed flow of both autonomous vehicles and human-driven vehicles. Studies show that the crash rate per-kilometer for autonomous vehicles is 9.1, which is more than twice that of human-driven vehicles (4.1). The ratio of the rear-end crash pattern between autonomous vehicles and human-driven vehicles is 57.5%, which exceeds 27.9% of among human-driven vehicles. Therefore, there is an urgent need to investigate the safety mechanisms of longitudinal interactions of autonomous vehicles and human-driven vehicles. Existing studies typically employ driving simulation experiments to analyze the longitudinal interaction and safety between human-driven and autonomous vehicles in virtual environments. However, the differences between simulated environments and real-world road scenarios make it challenging to accurately capture the interaction behavior between vehicles in mixed human-autonomous traffic flows. In this study, public road-testing dataset of autonomous vehicles are utilized to extract longitudinal interacting scenarios, and the influencing factors and the impact mechanisms of longitudinal interaction behavior and safety are investigated. Specifically, scenarios of human-driven vehicles following the other human-driven vehicle, and following an autonomous vehicle are studied, Structural equation model is applied to construct a chained relationship among driving behavior of leading vehicle, type of leading vehicle (whether it is an autonomous vehicle or not), speed level of vehicles on the roadway, and the safety surrogate measure. The modelling results revealed the type of leading vehicle is identified as an influencing factor in longitudinal interaction safety. When other variables remain constant, the safety of interactions between human drivers and autonomous vehicles as leading vehicles decreased compared to interactions with other human-driven vehicles as leading vehicles.
An Analysis and Adjustment of the Abrupt Change of Vehicle Trajectories in the Entrance area of Freeway Tunnels
YU Liang, BEI Runzhao, DU Zhigang, ZHANG Xing, YANG Yongzheng
2024, 42(3): 20-30. doi: 10.3963/j.jssn.1674-4861.2024.03.003
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Vehicle trajectories would undergo abrupt changes at the entrance area of freeway tunnels. To analyze the reasons behind this phenomenon and quantitatively evaluate the regulating effect of different visual guiding schemes, four simulation scenarios are developed. Scenario 1, based on the guidelines outlined in Specifications for Design of Highway Tunnels Section 2 Traffic Engineering and Affiliated Facilities (JTG D70/2—2014), serves as the control group, while other scenarios incorporate visual guiding schemes on the basis of Scenario 1. Specifically, Scenario 2 introduces a low-position scheme consisting of flexible posts and crash cushions, Scenario 3 introduces a high-position scheme comprising retroreflective arches and warning alignment signs, and Scenario 4 combines both the low and high schemes. Through a simulated driving platform, data such as driving distance, steering wheel angle, and lateral offset are obtained, and an evaluation index system is established considering the occurrence, evolution, and fading of the abrupt change trajectories. The study results indicate that changes of the visual reference system can prompt abrupt changes of driving trajectories, but a continuous and consistent visual guiding scheme can regulate this phenomenon. Specifically, compared to the control group, the low-position scheme significantly reduced the average steering wheel angle before the tunnel entrance (SWAav) by 82%, helping drivers avoid abrupt maneuvers. High-position scheme increased the gradient coefficient (G) by 3.7 times, reduced the expected lateral deviation during the transient stability phase (O1) by 31%, and decreased the difference between O1 and the expected lateral deviation during the stable phase (O1－O2) by 75%. This improved the gradual change in trajectory, reduced avoidance of the tunnel portal and wall, and enhanced adaptation to the tunnel environment. The combined guiding scheme, which integrates both low and high-position scheme, yielded the best results: it increased G by 4.4 times, reduced SWAav by 83%, decreased O1 by 41%, and minimized O1－O2 by 98%. This scheme effectively improved the gradual nature of trajectory changes, reduced avoidance of the tunnel entrance and walls, and enhanced environmental adaptation. Consequently, it is recommended to implement the combined scheme in the entrance areas of highway tunnels, with the exception of special cases where only the high scheme should be applied.
Characteristics of Driving Behavior and Performance Caused by Plateau Environment of Young and Middle-aged Drivers
GUO Weiwei, HU Yuqin, TAN Jiyuan, XUE Qingwan
2024, 42(3): 31-41. doi: 10.3963/j.jssn.1674-4861.2024.03.004
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To analyze effects of a hypoxic environment on driving performance, a driving simulator experiment is conducted in this study. Both drivers' behavioral data and physiological data are collected by simulating a plateau scenario (3 900 m). The driver behavior characteristics in the plateau scenario and plain scenario are analyzed using a radar map, a numerical ranking map, and one-way ANOVA. The probability density fitting distribution differences between the two scenarios for road offset, steering velocity, lateral acceleration, and speed are quantified using the Jensen-Shannon divergence. The difference method is employed to identify time windows when driving performance decreased in the plateau area. The validity of the simulated hypoxic driving environment is verified by comparing the heart rate trend of the pilot test data in the plateau. The results indicated that: ① the standard deviation of road offset, lateral acceleration, steering velocity, and speed in the plateau scenario increase by 0.094 3 m, 0.119 0 m/s2, 0.000 9 °/s, and 0.651 3 km/h, respectively, compared to the plain scenario; ② the fitted probability density distribution differences between the plateau and plain scenarios for road offset, lateral acceleration, steering velocity, and speed are 0.23, 0.11, 0.01, and 0.02, respectively (thus, it could be inferred that vehicle lateral movement is more affected by the high-altitude factor); ③ driving performance decrease significantly after 6 minutes upon entering the plateau area at 3 900 m altitude.
Multi-LiDAR Roadside Intelligent Perception Method Fusing High-Definition Map
HU Zhaozheng, CHEN Qili, MENG Jie, HU Huahua, ZHANG Jianan
2024, 42(3): 42-52. doi: 10.3963/j.jssn.1674-4861.2024.03.005
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In the research of vehicle-road collaborative roadside perception, challenges such as low detection efficiency, unstable target trajectories, and inaccurate tracking arise due to the sheer volume of point cloud data and the inevitable obstruction of targets. To tackle these issues, a method of intelligent roadside perception utilizing multi-LiDAR fused with High-Definition (HD) maps is proposed. The goal is to enhance the accuracy and reliability of perception outcomes by incorporating detailed map information. Leveraging the calibration results of multi-LiDAR, the extraction of the region of interest (ROI) within the three-dimensional point cloud is achieved through HD maps, effectively reducing the quantity of point clouds for processing and enhancing computational efficiency. Employing the polar-image Gaussian mixture model (P-GMM) for background modeling, moving targets are swiftly identified using polar-images to circumvent direct processing of extensive LiDAR point clouds, thereby boosting detection efficiency. By enforcing the alignment between vehicle heading and lane line direction, the lane orientation in the HD map is translated into a linear constraint of vehicle state within the Kalman filter framework, thereby enhancing the efficacy of vehicle detection and trajectory tracking. Experimental validation is conducted using simulated crossroads and real-world roads with double T-shaped intersections. Compared to other methods, the method proposed yielded a 55% reduction in data volume, a 12% increase in target detection accuracy, and a 56% decrease in processing time. The improvements in extreme error, mean error, and root mean square error are also achieved in target tracking. The experimental results show that the method proposed can fuse HD map information effectively, achieving rapid detection and tracking of road-moving targets in a wide range of road scenarios.
An Active Tracking Method for Small Ships in Open Water Based on Fixed/PTZ Camera System
YOU Ji'an, HU Zhaozheng, XIAO Hanbiao, MENG Jie
2024, 42(3): 53-61. doi: 10.3963/j.jssn.1674-4861.2024.03.006
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It is difficult to actively track and capture clear images of inland river ships with the current Closed Circuit Television (CCTV) system. To fill the gap, an active tracking method for small ships in open waters based on the fixed/pan-tilt-zoom (PTZ) camera system is proposed. A three-layer joint calibration model based on a virtual quadrilateral (VQ) is introduced to jointly calibrate the fixed camera and the PTZ camera, which matches the image coordinate with the pan and tilt angle of the PTZ camera one by one; The introduced VQ filters out the targets outside the quadrilateral, eliminating inference and improving the accuracy of detection. The mapping relationship between the image coordinates and the world coordinates can be obtained by using the Perspective-n-Point (PnP) algorithm and the vertices of the VQ; Fourthly, the world coordinates of the points in the VQ are transformed into the Pan-Tilt-Hight (PTH) coordinates via PTH model. Then, by calculating the coordinate of the ship (the centroid of the ship) in the VQ, the pan and tilt angle of the PTZ camera can be derived, achieving real-time active tracking and keeping the target at the center of the PTZ camera image. To validate the proposed method, two real scenes are introduced, namely Chunhui Lake in Xiaogan City and the Sino-French Bridge section of the Han River in Wuhan City, Hubei Province. The results indicate that, ① the F1 -Scores of the proposed method on the fixed camera are 96.82% and 97.62%, respectively; ② when the proposed method is applied to the PTZ camera for tracking the moving ships, the failure rate is 4.63%. In summary, the proposed active tracking method performs reasonably in practice with a high tracking rate of 18.55 fps.
A Layout Method of Guide Signs for Inner and Outer Lanes Integrated Composite Expressway
HU Xinchao, DAI Zhe, XI Kun
2024, 42(3): 62-73. doi: 10.3963/j.jssn.1674-4861.2024.03.007
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The integrated composite expressway has a special road structure and traffic organization mode, which requires the transmission of a large amount of information. In order to enhance the efficiency of guide signs, prevent information overload, and improve safety, research is conducted to optimize the layout of guide signs for this type of expressway. Using the Guangshen expressway as a case study, the research analyzes its characteristics of the inner and outer lanes to clarify layout principles for guide signs. It proposes information guidance methods based on the functions of inner and outer lanes and develops a grading method for guidance information. Through driving simulation technology, experiments are carried out to determine information threshold and layout design for guide signs. Drivers'target search time for different information quantities of guide signs is measured, as well as the lateral offset, speed, acceleration, and sign fixation time during interchange exits. In the information threshold experiment, robust estimation theory is applied to process the target information search time, concluding that the information threshold for guide signs on an integrated composite expressway is 8. In the layout design experiment, two sets of interchange exit guide signs are tested based on the proposed information guidance and grading methods. Both sets can correctly guide vehicles to their destinations. However, the guidance method based on the inner and outer functions proves more efficiency, leading to an earlier lane changes about 250 m, a 5.88% increase in driving speed, a 45.77% reduction in acceleration standard deviation, and a shortened sign fixation time. The research indicates that the proposed information guidance method effectively enhances sign visibility, guides traffic flow, and alleviates driver stress on integrated composite expressways. It is recommended to adopt the information guidance method based on the inner and outer functions for integrated composite expressways.
A Timetable Optimization Method for Urban Train Transit Based on Virtual Coupling
LI Yan, GONG Liang, XU Dejie, PAN Xing, HU Chenhao
2024, 42(3): 74-84. doi: 10.3963/j.jssn.1674-4861.2024.03.008
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To solve the mismatch between train capacity and demand during peak hours, a timetable optimization method for urban train transit based on virtual coupling technical is proposed, incorporating spatiotemporal characteristics of passenger flow, oversaturation of trains during peak hours, and the limitation of the number of rolling stocks. A dynamic passenger flow cumulative demand (PFCD) function is proposed to pedict the passenger flow at different hours. Then, the schedule optimization model for urban rail transit based on the virtual coupling is established, in which, the departure time of trains at the first station and the marshaling scheme of each train are decision variables and the average waiting time (AWT) of passengers and the train travel mileage (TTM) are minimized under constraints such as passenger demand in different hours, departure interval, running time, number of rolling stocks, rolling stock circulation, etc. Lagrangian relaxation is introduced to reduce the complexity of the problem by absorbing the coupling constraints into the objective, and the original problem is decomposed into two independent subproblems. By using a commercial solver and the designed heuristic algorithm, the lower bound and upper bound of the problems are found. A metro line in Shanghai Metro is employed for demonstration, and the results show that: ① the proposed dynamic PFCD function fits the arrival pattern of passengers well during the peak hours; ② compared with the uniform departure schedule, the non-uniform departure (non-UD) schedule under the fixed train composition (FTC) mode can reduce the AWT of passengers by 24.15% and the waiting time of stranded passengers by 51.73%; ③ compared with the non-UD schedule under the FTC mode, the train timetable based on virtual coupling can reduce not only the train running kilometers by 0.33% but also the AWT of passengers and the waiting time of stranded passengers by 16.95% and 6.03%, respectively.
A System Optimization Model of Traffic Divergence for Freeway Reconstruction and Expansion Considering Road Charge
TIAN Long, GUO Yueli, YUAN Xueqiang, FANG Dijiu, ZENG Qiang
2024, 42(3): 85-94. doi: 10.3963/j.jssn.1674-4861.2024.03.009
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Traffic divergence is an important measure to ensure the efficiency of traffic operation during the reconstruction and expansion of freeways. However, currently the expressway reconstruction and expansion projects in China mainly rely on the managers to determine the divergence measures empirically, of which the performance needs to be further improved. Meanwhile, there is lack of systematic and objective divergence methods. According to the road characteristics of regional divergence network, a road impedance function is developed by combining the impact of road toll on travelers' route choice with travel time. From the perspective of traffic managers, taking the minimum travel impedance of the road network as the optimization objective, the system optimization model of traffic divergence for reconstruction and expansion of freeway is established considering the balance of demand and supply, the relationship between path and link flows and the non-negative constraint of route flow. The Karush-Kuhn-Tucker (KKT) conditions of the model is analyzed, and an algorithm based on gradient projection is designed to obtain the divergence path and path flow among origin-destination (OD) pairs in the road network. Taking a reconstruction and expansion project of freeway in Guangdong Province as an example, the traffic operation states of the entire road network and the construction section are modeled under three conditions of no divergence, divergence without road toll and divergence with road toll. The results show that: ①Without considering the road toll, the average traffic volume of the section of reconstruction and expansion decreases by 27.72%, the saturation decreases by 0.09, and the average speed increases by 4.26 km/h. ② Taking road toll into consideration during the diversion, the traffic volume of the section of reconstruction and expansion is reduced by 44.8% on average, the saturation is reduced by 0.4, and the average speed is increased by 12.98 km/h. The road traffic efficiency is effectively improved, and the divergence does not cause deterioration of the traffic operation of other sections in the road network. Such conclusions confirm the effectiveness and superiority of the traffic divergence method proposed in this paper.
A Traffic Behavior Analysis of Food Delivery Workers Based on Knowledge Attitude Belief Practice Model
LYU Hui, YAO Xiaoxia, WANG Chao, LI Jie
2024, 42(3): 95-101. doi: 10.3963/j.jssn.1674-4861.2024.03.010
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In order to alleviate the occurrence of road traffic safety accidents in the process of food delivery, a structural equation model is constructed based on the extended theory of knowledge, attitude/belief, practice (KAP), and the effective questionnaires of 1 610 food delivery workers are taken as samples to quantize the influencing mechanism of factors such as individual characteristics, individual cognition, subjective attitude, labor intensity and traffic behavior of food delivery. A Cronbach's α coefficient reliability analysis is conducted on the questionnaire scale, and KMO test and Bartlett sphericity test are used to determine whether factor analysis can be performed. The exploratory factor analysis is carried out, and the principal factors are extracted by the method of feature root greater than 1. The maximum variance rotation method is used to make the factor variables more interpretable. The structural equation modeling (SEM) is used for studying the psychological attribution of traffic behavior, and the fit test and path coefficient test are carried out on the constructed model. The results show that the individual cognition and subjective attitude of food delivery workers directly influences the traffic behavior, The individual cognition and subjective attitude of the deliverymen directly affected their traffic behavior, and the influence coefficients are 0.284 and 0.209. Moreover, individual cognition can also indirectly affect their traffic behavior by affecting their subjective attitude. The labor intensity of individual distributors has a direct negative impact on traffic behavior and the influence coefficient is －0.390. Specifically, the greater the labor intensity, the greater the risk of traffic safety behavior of individual delivery workers. At the same time, the study found that labor intensity has become an important cause of traffic safety accidents of delivery workers, and the individual characteristics and subjective attitude of delivery workers are the main influencing factors of labor intensity. Due to the differences in individual characteristics of delivery workers, their individual cognition, subjective attitude, labor intensity and traffic behavior will also be different. The punishment measures for enterprises of unsafe traffic behaviors can play the expected effect of standardizing the traffic behaviors of delivery workers, thus reducing the number of traffic violations and the occurrence of traffic accidents. In addition, the traffic safety awareness of the delivery workers themselves will not only affect the individual traffic behavior performance, but also have a negative external impact on the traffic safety cognition of the surrounding delivery workers, which leads to the"herding effect".
A Review about Resilience Evaluation for Urban Multimodal Transportation Networks
ZHANG Jiefei, REN Gang, TANG Lei, DU Jianwei, GU Houyu, SONG Jianhua
2024, 42(3): 102-113. doi: 10.3963/j.jssn.1674-4861.2024.03.011
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To improve the development of research about transportation resilience, this paper, focusing on urban multimodal transportation networks, summarizes the relevant studies on resilience evaluation in the literature. The definition and connotation of resilience are introduced. The indicators for resilience evaluation are summarized from the perspectives of network topology, supply-demand characteristics, and coupling relationships. The research of model-driven and data-driven resilience evaluation methods are introduced. The advantages and disadvantages of these methods are summarized as well. Fourth, measures to improve the resilience of transportation network are discussed from the perspectives of network design, emergency evacuation, and network restoration. The resilience optimization models and algorithms are summarized as well. The research deficiencies and future development directions are discussed. The results show that: ① the resilience evaluation of composite networks fails to fully consider the coupling characteristics. Besides, resilience evaluation is imprecise to depict variable traffic demand and travelers' travel behavior. ② The determination of indicator weights depend more on subjective judgement in model-driven resilience evaluation. Data-driven resilience evaluation focus on data analysis and result display, but lacks in-depth analysis of resilience evolution. ③ The optimization models targeting resilience improvement need to be improved in multi-objective decision making, computational efficiency in large-scale networks, and reproduction of real scenes. From these results, the suggestions for the future research are as follows: ① in the development of the network and the selection of indicators, the dependence of the composite network needs to be fully considered. Besides, and the coupling characteristics between the systems need to be scientifically reflected in evaluation models. ② It is suggested to cooperate with multiple departments to establish a complete and shared database, to explore the network resilience evaluation methods which are driven by both data and model, and to design high-efficient algorithms to support the rapid and accurate calculation of the resilience indicators. ③ The static discrete resilience evaluation should be developed into dynamic continuous resilience monitor, based on which the temporal-spatial evolution of network resilience and the evolution mechanism of traffic network resilience must be analyzed. ④ The refined network resilience decision optimization should be strengthen to reproduce the real event scenarios in data analysis and model development. Besides, it is necessary to further explore the application of AI algorithm to deal with the application of large-scale network optimization.
Vulnerability Assessment and Recovery Strategies for Container Shipping Networks from a Resilience Perspective
ZHANG Di, TAO Jiale, WAN Chengpeng
2024, 42(3): 114-121. doi: 10.3963/j.jssn.1674-4861.2024.03.012
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The existing vulnerability evaluation of shipping networks and recovery strategies are suffering from two limitations. One is using a single assessment method, simplifying the complexity of the shipping network; the other is neglecting actual operational capabilities and spatial distance in recovery strategies, resulting in poor effectiveness in emergencies. To fill the gaps, a comprehensive evaluation of the vulnerability of the shipping network is proposed, considering the topology of the network and its actual operational capacity; multi-dimensional vulnerability evaluation indices are found based on the coefficient of variation method; recovery strategy is designed based on the backup-port rank that incorporates the spatial distance, the capacity of ports, and the number of berths. Several innovations to the model and algorithm are introduced, including a dynamic evaluation framework, adaptive weights for vulnerability indicators, and optimizations for backup port selection and traffic diversion in emergencies. To validate the proposed method, container shipping networks of China-Europe, China-Mediterranean, China-US (East Coast), and China-US (West Coast) in 2020 are introduced, topology maps of these networks are developed, and the vulnerability and dynamic capacity of these networks are analyzed. The findings show that the resilience of the shipping network is improved by 11.6% when a single port backup recovery strategy is implemented, and by 31.5% when a dual port backup recovery strategy is adopted. In summary, the proposed vulnerability assessment method and the recovery strategy based on backup-port ranking provide a novel way to improve the resilience of the shipping networks, highlighting the importance of vulnerability assessment and backup recovery strategies in shipping networks.
Modelling on the Risk Dynamic Evolution of Urban Rail Transit Operation Emergency
FAN Bosong, SHAO Chunfu, ZHAO Dan, MA Sheqiang
2024, 42(3): 122-130. doi: 10.3963/j.jssn.1674-4861.2024.03.013
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In order to analyze the dynamic evolution characteristics of urban rail transit operation emergencies, and to explore risk factors affecting normal operations, this paper investigates a dynamic evolution model for such emergencies. The bow-tie model is used to integrate the causes of operational risks, estimated time margins and the severity of the emergencies, developing a risk dynamic model which reflects the operational risk status of urban rail transit systems at different moments. Based on a complex network model, the degree distribution of nodes is improved by introducing connected edge weights and structural hole theory, leading to the development of a risk dynamic evolution model which characterizes risk dynamic modes and their evolution process. Relying on the data from Beijing urban rail transit emergency operations, the research explores the evolution patterns of operation emergencies and identifies significant risk factors. The results show that the risk dynamic evolution model for Beijing urban rail transit operation emergency network exhibits the characteristics of a scale-free network, where 19.90% of risk dynamic modes account for 77.76% of the dynamic evolution process of the whole system. The risk dynamic evolution model demonstrates both robustness and fragility, with"train fulfillment"and"punctuality"identified as risk factors for the"more severe"and"severe"modes, respectively. These few but critical risk factors have significant consequences for the dynamic evolution of the system. Therefore, it is necessary to focus on risk factors that may bring serious consequences, and carry out targeted risk prevention, control and resilience enhancement, according to the dynamic evolution characteristics of the system.
An Evaluation Method for Safety Resilience of High Slope Construction Based on Bootstrap-matter-element Extension Model
YAO Hongyu, JIN Guobo, PAN Keke
2024, 42(3): 131-138. doi: 10.3963/j.jssn.1674-4861.2024.03.014
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In order to solve the problems of one-sided index system, fuzzy value range, and weak practicability in traditional high slope construction safety evaluation, a method of safety resilience evaluation of high slope construction based on Bootstrap-matter element extension model is proposed. Combined with the concept of safety resilience, the correlation strength method and keyword cluster analysis are used to screen the safety factors of high slope construction. Kaiser-Meyer-Olkin (KMO) test and multicollinearity test are used to deal with index correlation degree and collinearity respectively. The evaluation index system of construction safety resilience of high slope is formed, which takes stability, redundancy, efficiency and fitness as the first index and operator experience and other 20 factors as the second index. The comprehensive matter-element matrix is determined according to matter-element extension principle, and the classical domain is determined by Bootstrap method to deal with the unknown sample distribution hypothesis. Furthermore, the correlation degree function is established and the index correlation degree under each evaluation grade is calculated. The weight of each safety resilience index is determined by entropy weight method, and the construction safety resilience evaluation model of high slope is formed. Based on a highway high slope construction project, the feasibility of the model is verified, and compared with the traditional construction safety risk assessment results, the results show that the safety resilience grade of the high slope is Ⅲ, which is consistent with the risk assessment results of LEC method and expert investigation method. Moreover, the Bootstrap-matter-element extension model provides the overall safety resilience level and traceability analysis results. Compared with the likelihood-exposure-consequence (LEC) method, the mature-element extension model improves the accuracy by 9.68%, the recall rate by 5.51% and the generalization by 12.09%. The construction safety resilience index system of high slope includes construction safety factors in addition to the basic influencing factors such as slope structure, so it has higher practicability.
An Evaluation Method of Safety Resilience for Highway Bridge Engineering Based on an Entropy Weight and Improved TOPSIS Model
WU Xiumei, SHI Zhan, YUAN Xiang, CAI Wenjuan
2024, 42(3): 139-147. doi: 10.3963/j.jssn.1674-4861.2024.03.015
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Targeting to the safety risks in freeway bridge construction caused by inadequate safety management, this paper develops a safety resilience evaluation method for bridge construction considering the full lifecycle of risk-hazard-accident. Based on bibliometric analysis and WBS theory, the concept of resilience is integrated into safety evaluation for traffic engineering. An evaluation system for freeway bridge engineering based on safety resilience theory is proposed, where the safety resilience mechanism of freeway bridge construction is investigated and evaluation index system with"4R"characteristics as primary indicators are developed. Given that traditional technique for order preference by similarity to an ideal solution (TOPSIS) evaluation does not account for the impact of outliers, statistical methods are used to screen and resample the outliers. Meanwhile, entropy weight method is adopted to optimize the weights of indices. By doing so, an entropy weight-improved TOPSIS model is developed for safety resilience evaluation of bridge engineering. Four freeway sections containing bridge construction are selected and their levels of safety resilience are evaluated using the proposed model, whose feasibility is analyzed as well. Results show Sections B and D have a medium level of safety resilience, while Sections A and C have a low level. Comparing to the results from the traditional risk assessment method that Sections B and D are Level Ⅰ and Sections A and C are Level Ⅱ, results from the proposed model align with real situations. Therefore, the validity and feasibility of the model are confirmed. To sum up, the proposed entropy weight-improved TOPSIS model enables sensitivity analysis and risk factor tracing, and further contributes to targeted preemptive improvements for decision-makers.
An Impact Analysis of Willingness to Help Vulnerable Groups under Subway Emergencies Based on SEM Model
HUANG Lihua, CHEN Xiaotong, LYU Shuran, LIU Xuteng, CHEN Kang, WANG Chenshuo
2024, 42(3): 148-157. doi: 10.3963/j.jssn.1674-4861.2024.03.016
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To address the issue of unclear mechanisms influencing the willingness to help vulnerable groups under subway emergencies, a questionnaire survey is conducted. It aims to refine the analysis of the impact of multiple factors, such as passenger evacuation conditions, their own status, and the target of assistance, on the willingness to assist during actual subway emergency evacuations, as well as the structural relationships among these factors. The study finds that elderly group are the most likely to hinder evacuation efficiency (62.92%), followed by young children (25.83%). Among these vulnerable groups, young children are most negatively affected by emergency evacuation (51.25%), followed by elderly group (39.58%). Through variance analysis, it reveals that passengers'willingness to help during evacuation of subway emergencies is significantly influenced by their own conditions, evacuation conditions, and the characteristics of those in need of assistance (p < 0.05). To refine and optimize the influencing factors of assistance willingness, the study conducts reliability and validity tests, and constructs the Structural Equation Modeling (SEM) is used to accurately identify the key influencing factors of assistance behaviors towards vulnerable groups under subway emergencies, while clarifying the quantitative relationships among these factors. The results indicate that unfavorable evacuation conditions have a direct negative impact on assistance behaviors (－0.162), whereas the conditions of those in need have a direct positive influence (0.151). Additionally, unfavorable evacuation conditions have a direct positive impact on the conditions of those in need (0.652). These findings suggest that poor evacuation conditions reduce passengers'willingness to help while unfavorable conditions of those in need increase it. The promise of rewards for assistance behaviors also enhances passengers'willingness to help. Notably, even under unfavorable evacuation conditions, passengers still exhibit a high willingness to assist when encountering those in dire need.
A Method for Safety Resilience Evaluation of Construction of Freeway Tunnels Based on Combination Weighting and Grey Cloud Model
CHEN Xiaowei, ZHANG Xi, WANG Zenglu, HE Junhao, LI Zewei
2024, 42(3): 158-166. doi: 10.3963/j.jssn.1674-4861.2024.03.017
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To avoid the development from safety risk to accident, and to take preventive control before an accident occurs, a safety resilience evaluation method for the construction of freeway tunnel is proposed. Considering that the tunnel construction system itself has the ability to resist, withstand, and adapt to risks, indicators for risk control, hazard tolerance and identification of hidden dangers is put forward under the perspective of safety resilience, and a safety resilience evaluation index system for highway tunnel construction in the three dimensions of personnel, equipment, and management is developed. A gray cloud model with combination weighting is developed to evaluate the safety resilience level of the construction of freeway tunnels, which is applied to a tunnel in a freeway of Ningbo. The results show that the level of safety resilience of the tunnel construction is rated as high and has a good safety state; however, the level of safety resilience of the ability of identifying hidden dangers is low, indicating that the tunnel lacks the ability to intelligently detect various dangerous states during the construction process, and fails to quickly identify the occurrence and evolution of hidden dangers. The safety risk assessment using the Hazard assessment method confirms the results of the combination weighting and grey cloud model, validating the model's effectiveness and reliability. The safety resilience evaluation method proposed in this paper for the construction of freeway tunnels can not only obtain the comprehensive evaluation result of the safety resilience level, but also can sort the influence degree of factors according to the gray clustering coefficient of each factor and then trace back the weak point of safety resilience. Hence, it is easy to find out accurately the constrained factors affecting the construction safety state of freeway tunnels.
An Operational Resilience Evaluation of Subway Station Based on Improved CRITIC-VIKOR Method
DENG Yongliang, GAO Yutong, ZHOU Qi, LI Kewei, GU Tiantian
2024, 42(3): 167-174. doi: 10.3963/j.jssn.1674-4861.2024.03.018
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Abstract:
The operational resilience of subway stations is characterized by its multidimensionality and complexity. To evaluate this resilience accurately and reliably, an improved A CRITIC-VIKOR based evaluation method is proposed. Based on resilience theory and the operational characteristics of subway stations, the concept of operational resilience for subway stations is defined, with a focus on its three core dimensions: pressure, state, and response. Key factors in four domains, including human, machine, environment, and management, are analyzed, leading to the development of 8 primary indexes. Through literature analysis, 26 secondary evaluation indexes are established. To assign more accurate weights to the indexes, the standard deviation coefficient method is applied, improving the CRITIC method through correlation coefficient analysis. By integrating the VIKOR method, a novel evaluation model for subway station operational resilience is proposed. An empirical analysis is conducted on Tongli station, Liuhong station, and Nanmen station of Suzhou subway Line 4. Data is collected using a Likert scale, and weights are calculated for the 26 evaluation indexes, as well as the group utility, individual regret, and decision-making index for each station. This allows for a quantitative ranking of the operational resilience of subway stations. Compared with superiority chart, analytic hierarchy process, and entropy method, the improved CRITIC method showed the smallest bias range, from 2% to 40%, with the cumulative bias of the 26 indexes being the smallest at 553%. The results indicate that the weights for pressure resilience, state resilience, and response resilience are 59.74%, 21.48%, and 18.78%, respectively. Among the three stations, Liuhong station demonstrates the highest operational resilience, followed by Tongli station and Nanmen station. The evaluation model provides theoretical foundation for more accurate evaluation of subway station operational resilience.

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