2022 Vol. 40, No. 6

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A Real-time Detection of Nautical Traffic Events: A Review and Prospect
HUANG Chen, CHEN Deshan, WU Bing, YAN Xinping
2022, 40(6): 1-11. doi: 10.3963/j.jssn.1674-4861.2022.06.001
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Nautical Traffic Event Detection(NTED) methods mostly rely on offline methods using historical data, which are insufficient for real-time traffic supervision. The studies on abnormal behavior detection and incidents detection of ships are collected and investigated, and the findings are concluded as follows: from the perspective of data, the detection data rely on a single source and the environmental information is usually missing; from the perspective of methodologies, classical models that are based on statistical methods, risk assessments, etc., have high efficiency but low accuracy; while, the machine-learning based methods, such as neural networks, image recognition, etc., have high accuracy but low efficiency; and the combination of multi-source data fusion and multi-technology have become new trends.Three key technologies for the real-time NTED are summarized: ① maritime big data technologies, which process ships and environment data efficiently and standardize multi-source heterogeneous data structures, which reduces the false alarm caused by the single data source; ②dynamic behavior modeling, which uses knowledge graph or other technologies to integrate nautical contextual information, and uses deep learning, semantic association, graph neural network or other methods to develop different models for dynamic ship behaviors in different nautical context, which improves the accuracy of the NTED; ③the real-time analysis and visualization techniques combined with parallel systems, which can transfer information between the virtual and real systems, analyze the simulated results, and display the detection process which facilitates human-computer interactions in the supervision. A Nautical Traffic Event Parallel Detection System(NTEPDS) is proposed, which includes three functional modules: ①the data acquisition; ②the backend service; ③the client application. The NTEPDS can receive real-time navigation data, analyze and predict real-time traffic status, dynamically detect and report traffic events and display the simulation results. Finally, the prospects of the real-time NTED are concluded from three aspects: data fusion, traffic state perception, and traffic virtuality-reality mapping, which reveals the development directions of real-time NTED at the practical level.
A Review of Road Safety Evaluation Techniques Based on Traffic Conflict Theories
GE Huimin, ZHOU Lijun, BO Yunyu, DONG Lei, ZANG Wenkai
2022, 40(6): 12-21. doi: 10.3963/j.jssn.1674-4861.2022.06.002
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Road safety evaluation technologies based on traffic conflict theories are considering traffic conflict factors in the road safety evaluation. Based on the analysis of the influencing factors of traffic conflict(TC) and the basic concepts of safety evaluation, the common application scenarios of road safety evaluation technology are listed. The influencing factors of traffic conflict are analyzed from three aspects: intersection, expressway, and specific scene. Besides, the road safety evaluation technology is summarized from the following three aspects: index selection, method selection, and model construction.Analysis of existing literature shows that in the construction of application scenarios, compared with the consideration of single conflict factor, comprehensive consideration of influencing factors of TC will make the constructed TC scenarios closer to the actual situation; in traffic safety evaluation, scientific selection of composite indexes, rational use of fuzzy comprehensive evaluation and analytic hierarchy method to construct safety evaluation methods will make the constructed safety evaluation methods more scientific and rigorous. Based on the issues identified from the existing studies, the future research direction of road safety evaluation technology is concluded, including making full use of video technology and internet technology to develop real-time and efficient safety evaluation models; verifying the applicability of existing road safety evaluation methods under mixed traffic flow; establishing and improving the evaluation technical standards and evaluation system of road traffic safety under mixed traffic flow environment.
A Review of Identification and Analysis Methods for Road Safety Risk
KOU Min, ZHANG Mengmeng, ZHAO Junxue, XIE Qingmin, LI Xin, ZHANG Ronglin
2022, 40(6): 22-32. doi: 10.3963/j.jssn.1674-4861.2022.06.003
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The accuracy and comprehensiveness of road traffic safety risk identification and analysis is the basis and key link to achieve active risk prevention and control, and directly affects the refinement level of road traffic safety management. This paper summarizes and comments on the studies related to road traffic safety risk from two aspects of influencing factors and analysis methods. In a view of the single factor risk such as unsafe behavior of drivers, unsafe state of vehicles, unsafe conditions of roads, and external environmental stimulation, as well as the correlation and coupling risk identification among multiple factors, the road traffic safety risk analysis methods such as safety risk theoretical analysis method, system safety analysis method, big data and artificial intelligence analysis method are sorted out. The study shows that the qualitative analysis methods such as the safety risk theoretical analysis method and the system safety analysis method focus on the comprehensive and systematic analysis of the road traffic safety risk factors, and have the advantages of simplicity, directness, and ease of operation, but there are many limitations in the quantitative analysis of road traffic accidents and the deep excavation of accident causes under the influence of multiple factors. Big data and artificial intelligence analysis methods based on multi-source data mining technology have obvious advantages in massive information perception, efficient computing, and processing, and can comprehensively analyze and accurately mine traffic safety risks based on multiple data, depict accident risk characteristics under the coupling of multiple factors, and explore the rules of accident occurrence, which is the current mainstream research direction. It also points out the shortcomings in the field of road traffic safety risk research and the direction of future research and development, mainly including the dynamic collection and fusion of multi-source heterogeneous data, road traffic safety risk identification under the intelligent network environment, and the research of transplantable road traffic safety risk identification model considering space-time heterogeneity.
An Optimization Method and Evaluation Model for Designing Speed Control Zones of Freeway
YANG Yajun, ZHANG Chi, TANG Xiang, QI Xin, ZHAO Yijing
2022, 40(6): 33-44. doi: 10.3963/j.jssn.1674-4861.2022.06.004
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The problems such as unreasonable determination of the speed limit, invalid rate-limiting way, and improper setting of speed limit range can impact the road safety. These problems can impact driving experience and the credibility of speed limit management. A model is developed based on safe speed and traffic efficiency. Then, the minimum length of speed limit zone, the limit of vehicle speed, and the division of speed limit zone are optimized. On this basis, an evaluation model of speed limit zone of freeway is optimized. The minimum length of the speed limit zone is calibrated according to the driver's vision recognition distance, the pre-setting distance of speed limit sign, and the driver's psychological stability distance. These limitations include the drivers' visual distance, the pre-setting distance of speed limit sign, and the drivers' psychologically stable distance. Then, according to whether the speed is prone to sudden change, a road segment is divided into six different types of combination by the method of variable length. On this basis, the speed limit prediction models of different combination roads are determined. The method based on partition and hierarchy in cluster analysis is used to optimize the partition of speed limit zone from two aspects. The minimum length of speed limit zone and the minimum traffic delay are optimized.At the same time, the traffic conflict rate is chosen as the index of traffic safety. And the traffic delay time is chosen as the index of traffic efficiency. The evaluation index model is established. Then, the validity of the method is verified by the comparison and analysis of the indexes before and after optimization. The simulation experiment of speed limit optimization is carried out on a mountain freeway with VISSIM. The results show that the parameters of the optimized safety evaluation model is reduced by about 29.49%. The parameters of the efficiency evaluation model is increased by about 21.90%. Moreover, the safety and overall traffic efficiency of the optimized freeway are improved. The speed limit zone determination method in this paper is based on the sudden change of the vehicle speed.This method combines the attribute and index characteristics of freeway sections. The proposed optimization method can significantly optimize the length of speed limit zone and the division of the zone.
Switching Control Decision of Lane-changing Model in Interweaving Areas of Mixed Traffic Flow with Human-driving and Autonomous Vehicles
LI Xia, LI Mingye, ZHANG Xiaoming, CUI Hongjun, MA Xinwei
2022, 40(6): 45-52. doi: 10.3963/j.jssn.1674-4861.2022.06.005
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Due to the urgency of forced lane change in weaving areas, lane-changing behaviors occur in the second half of a weaving segment due to a strong desire to change lanes, which will have a certain impact on traffic flow. In a situation of mixed traffic flow with human-driving and autonomous vehicles, different lane change control models can affect the capacity of weaving areas. Based on analyze the characteristics of lane-changing behaviors in the weaving areas with the mixed traffic flow, they are divided into two types: conservative lane-changing and radical lane-changing. Based on an acceptable safety gap model and the cooperative behavior among autonomous vehicles, a cooperative lane changing model for autonomous vehicles in a conservative state is constructed; and the radical lane change model under the influence of the vehicle type behind the target lane in the radical state. By analyzing the track data from the field survey of Jinbao Interchange and the track data of the US-101 weaving area in NGSIM, the distribution functions of switching points of conservative and radical lane changing models are fitted, respectively; Considering the characteristics of different vehicle driving behaviors and their interactions, the logic decision of lane change model switching control under the condition of the mixed traffic flow is proposed. The SUMO simulation software is used to develop an experimental platform. Considering the distribution characteristics of the switching points of the lane-changing model of the manual vehicles, and aiming at optimizing the maximum flow rate, the overall vehicle running speed in the weaving area, and the speed of the lane-changing vehicles, the optimal conservative-aggressive lane changing model switching points of the autonomous vehicles under different penetration rates of the autonomous vehicles are determined. The simulation results show that when the length of the weaving area is 250 m and the penetration rate of autonomous vehicles is 0.2, 0.5, 0.8, the switching point of automatic lane-changing model reach the best at 180, 80, and 50 m respectively, with the increase of the penetration rate of autonomous vehicles, the best position of the lane change switching point will gradually move towards the entrance of the weaving segment, and the change of this lane change switching point is more obvious when the penetration rate of autonomous vehicles is low; At higher permeability, due to the increased frequency of cooperative lane-changing, the proportion of autonomous vehicle forced lane changing behavior decreases, and the impact of lane-changing model switching points on the capacity of weaving area gradually decreases. This study provides a basis for lane change control decisions of autonomous vehicles in freeway weaving areas under the condition of mixed traffic flow.
A Study of Configuration Model and Safety Analysis for Ship-to-ship Transfers of Liquefied Natural Gas
SHI Feng, TAO Kejian, HUANG Liwen, XIE Cheng
2022, 40(6): 53-62. doi: 10.3963/j.jssn.1674-4861.2022.06.006
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To address the problem of equipment selection and configuration for LNG ship-to-ship barge operation, a configuration model is systematically developed based on the multi-level fuzzy comprehensive evaluation analysis.A quantitative analysis method is proposed to calculate the stability of LNG ship-to-ship transfer equipment. Taking145 000 m3 and 60 000 m3 LNG ships as test objects, simulation analysis of the assembly configuration system is carried out based on the Computational Fluid Dynamics(CFD) method. The goodness of fit analysis under the simulated conditions are carried out based on the configuration model of LNG ship-to-ship transfer operation. According to the results, the goodness of fit of the selection and configuration of LNG ship-to-ship transfer under the simulated working condition is 0.85, whose error between the optimal value is 15% that is within the allowable range of 20%.It verifies the proposed LNG ship-to-ship transfer select and configuration model. Meanwhile, the LNG ship-to-ship transfer operation is restricted by the visibility greater than 1 000 m, a wind speed of less than 10.8 m/s, a flow rate of less than 2.5 n mile/h, and a safety zone radius of 1 210 meters. The configuration model can not only be used to provide quantitative safety analysis of the configuration for LNG ship-to-ship transfer equipment, but also to set up the environmental restriction conditions of LNG ship-to-ship transfer operation.
A Coordinated Green-wave Control Method on Arterial Roads Considering Critical Path Sequence
WANG Houyi, ZHANG Cunbao, CAO Yu, CHEN Feng, CENG Rong
2022, 40(6): 63-71. doi: 10.3963/j.jssn.1674-4861.2022.06.007
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Traditional coordinated control method on arterial roads usually takes the maximum efficiency of the coordinated flows as the optimization objective. However, uncoordinated flows may be comparable to or even higher than the coordinated flows during certain periods, which can significantly deteriorate the overall efficiency of road operation in the actual fluctuated traffic flow environment on arterial roads. To solve this problem, a coordinated green-wave control method for arterial roads considering critical path sequence is proposed. The identification of the critical path sequence on the arterial road is calculated by the systematic clustering algorithm, and two indexes of traffic sharing rate of its path and travel time index are used as clustering parameters. On this basis, a coordinated green-wave control model for arterial roads considering critical path sequence is established. Firstly, the coordinated relationship among the signal phases of each critical path is considered, the signal phase matrix based on 0-1 variables is developed, and the constraints underlying the model are proposed. Secondly, the indicators for invalid bandwidth existence and the minimum importance are set, respectively, and a bandwidth allocation strategy for green wave considering the path importance is developed to ensure that the bandwidth of green wave is allocated to the critical path with a high importance in priority. Finally, the objective function of the model is established with the maximum weighted sum of green-wave-bandwidth of critical path sequences as the optimization objective. The simulation environment is developed using VISSIM simulation software where an arterial road section consisting of four intersections on Zhongshan Road in Wuhan City is used as a case study. The experimental results show that compared with the traditional coordination control methods for arterial green wave and arterial multi-path green wave, the proposed method results in a 12.1% and 4.8% reduction in the average arterial delay, 13.6% and 7.6% reduction in the average queue length, and 16.5% and 9.7% reduction in the average number of stops, respectively. Besides, the proposed method makes the average travel time of each critical path be strictly inverse proportional to its own importance, which avoids the waste of bandwidth of green wave.
Attentional Characteristics of Pilots for International Exempting Flights Based on Signal Detection Theory
LI Jingqiang, ZHANG Xining, HU Chao, ZHOU Yanru, LIU Annan
2022, 40(6): 72-80. doi: 10.3963/j.jssn.1674-4861.2022.06.008
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Exempting flights are those without providing overnight rest to the pilots, which follow the policy: Implementation Measures for Exempting Crew Members from Duty Period and Flight Time Requirements during COVID-19.Pilots of exempting flights should have a high level of ability to detect various signals The signal detection ability represents the accuracy and efficiency of the crew's information processing and decision making, which are effective in ensuring flight safety. A high level of selective attention, tonic alertness and phasic alertness of pilots are of great importance for flight safety. Based on the principle of signal detection, a test method is designed to assess pilot's sensitivity(d') and bias(β) of the 3 types of signals. The results of 18 pilots' in-flight judgement outcomes of three types of signals are collected, pilots are all on domestic exempting and non-exempting flights to North America. Three types of signals' sensitivity and bias are calculated, receiver operating characteristic curves(ROC) are drawn. Finally, the following conclusions are conducted. The difference of self-reported fatigue degree between exempting and non-exempting flights is most significant after the outbound flight landing(karolinska sleepiness scale's difference = 2.333, samn perelli scale's difference = 1.222). Sensitivity and bias regarding selective signal show no significant difference between exempting and non-exempting pilots(sig =0.337, sig =0.200). The sensitivity to tonic signal of exempting pilots(d'=4.149) is higher than that of non-exempting pilots(d'=3.137), and bias of tonic signal of exempting pilots(β =0.616) is lower than that of non-exempting(β =0.629). The sensitivity to phasic signal of exempting pilots(d'=3.916) is higher than that of non-exempting pilots(d'=2.994), while bias has no significantly different(sig =0.262). Overall, exempting pilots have higher ability to perceive the three signals than non-exempting pilots, while their bias and average reaction time show no significant difference between the two flight modes. The signal detection ability of pilots on exempting flights does not negatively affect flight safety.
A Study of Integrated Scheduling of Automated Container Terminal Based on DDQN
YIN Xing, ZHANG Yu, ZHENG Qianqian, TANG Kexin
2022, 40(6): 81-91. doi: 10.3963/j.jssn.1674-4861.2022.06.009
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The interactive operations of quay cranes, artificial intelligent robots of transportation(ARTs), and yard cranes during automatic container terminal unloading are studied. A three-stages integrated scheduling model of automated container terminal based on hybrid flow shop scheduling problem is proposed, with the criterion of minimizing the makespan. In addition, the scheduling environment requires high real-time response. A deep reinforcement learning algorithm, namely double deep Q-network(DDQN), is used to solve the problem of dynamic characteristics of the automatic terminal scheduling environment. The input of the model is the real-time status data of the equipment at each stage. The neural network is used to fit the value-action function. The model is trained by experience playback mechanism. The single heuristic rule with the compound heuristic rule is taken as the equipment candidate behavior. By strengthening the learning action selection and action evaluation mechanism, the optimal container equipment combination strategy is obtained. According to the actual survey data of Tianjin Port Automation Terminal, different scales cases are designed for experimental comparison and analysis. The results show that: the total operation time of the proposed method is reduced by 7.84% on average compared with the current advanced particle swarm optimization algorithm, and the gap with the theoretical lower bound value is 6.0%, 5.6%, and 4.6%, respectively. In addition, the equipment loading in the three stages is relatively balanced. And the average utilization rate of equipment is 89%, which can meet the actual application requirements. In small-scale examples, the average error of the total completion time obtained by DDQN is 1.99% compared with Gurobi. With the increase of the size of the example, the solving time is increased by 59% at most, which verifies the feasibility and efficiency of the proposed method for improving the operation efficiency of the automated container terminal.
An Evaluation method for the Suitability of Three Visibility Graphs in Analyzing the Fluctuation Characteristics of Arrival Flight Flows
ZHANG Xie, XIAO Enyuan, LIU Hongzhi, ZHAO Yifei, WANG Mengqi
2022, 40(6): 92-105. doi: 10.3963/j.jssn.1674-4861.2022.06.010
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Understanding the fluctuation characteristics of air traffic flows plays a leading, essential, and key role in many aspects of their control and management, such as airspace configuration optimization, efficiency promotion, and safety assurance. This paper aims to evaluate the suitability of the visibility graph(VG), horizontal visibility graph(HVG), and limited penetrable visibility graph(LPVG) in analyzing the fluctuation characteristics of air traffic flows. A complex network based on the multi-scale time series data extracted from the same arrival flow is developed and the suitability of three visibility graphs is evaluated from the global and local structure perspectives. From the global perspective, a concept of details loss rate is proposed by considering the characteristics of the network structure-dependent matrix. Then a k-core cluster is used to analyze the suitability of quantifying the strength of flight flow fluctuations. From the local perspective, a transfer probability of fluctuation patterns is calculated using the sequential motifs method, and the suitability of the sequential motif with different lengths in characterizing fluctuation characteristics of flight flows is evaluated. The results show that: ①the loss rate of detail can be limited within 0.5 when the proportion of N value of the LPVG in network nodes ranges from 0.48% to 1.442%;②VG and LPVG(N=1~3) can effectively describe the intensity of fluctuation of flight flow time series data and the suitability value is 2.665, 4.810, 6.973, and 9.883, respectively; ③a long sequential motif would reduce the number of sequential motifs and result in the similarity of transition probability among different types of the sequential motifs, while a short sequential motif is useless for prediction due the chaotic characteristics of traffic flow. Thus, it is recommended to use the sequential motif with the length of 4, 5, 6, and 7 for VG and LPVG(N=1~3). In conclusion, the k-core cluster and the motifs method provide an in-depth analysis of the transfer characteristics among the fluctuation modes and the evolution of time dimension in air traffic, which offers support for delay prediction and plays a leading role in the actual operation management of flights.
A Path Optimization Method for Sea-Rail Intermodal Container Transport Under Random Transit Time
YUAN Xueli, YANG Juhua, REN Jinhui
2022, 40(6): 106-117. doi: 10.3963/j.jssn.1674-4861.2022.06.011
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In the process of sea-rail intermodal transportation, containers are subject to various uncertainties, resulting in time fluctuation, which affects cargo delivery punctuality. To effectively reduce the impact of uncertain transportation time, the economics and green sustainability of the transportation process are considered to optimize the container flow path of sea-rail intermodal transport. A multi-objective model with the least total transportation costs and the lowest carbon emissions is established by stochastic chance-constrained programming. Rail and ocean expected arrival times are introduced into the constraint conditions. And the paths that exceed the expected arrival times are penalized to ensure the superiority of the transportation paths. Consider two modes of transportation organization: one-stop direct delivery and intermediate loading, to overcome the shortcomings of existing studies that do not consider the adequacy of cargo sources. The uncertainty constraints are transformed into linear constraints using the knowledge of uncertainty and probability theory-related theories. The NSGA-Ⅱ algorithm is used to solve the problem of container cargo outbound route optimization from Xi'an to Los Angeles. The initialization population is improved by the greedy algorithm and the elite selection operator is improved by the probabilistic selection operator based on logistics distribution. The following results are obtained through comparative analysis: ①The total costs of transportation are reduced by ＄231 500 and carbon emissions by 6.69 t after algorithm optimization, while the speed of algorithm solution is increased by 75.36%. ②By comparing the fuzzy programming with the stochastic programming chosen for the model in this paper, it is found that the number of stochastic programming solution sets is more than the fuzzy programming. The total transportation costs and carbon emissions in the same transport path for both are optimized by 10.65% in the stochastic programming. Therefore, the model and algorithm in this paper have positive optimization effects. Finally, sensitivity analysis is performed to observe the impact of confidence level as well as time influence coefficient on the objective function and cargo delivery punctuality. The results show that: ①Higher levels of confidence in rail and sea transport will increase the total costs of transporting goods.② Time impact factor and cargo delivery on-time rate are negatively correlated. The higher the impact factor, the lower the cargo delivery on-time rate.
An Energy-saving Method Based on Optimized Timetable for High-speed Trains Considering Driving Strategy
GE Xin, ZHANG Yuzhao
2022, 40(6): 118-126. doi: 10.3963/j.jssn.1674-4861.2022.06.012
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In order to reduce the traction-energy consumption for high-speed trains running from the origin station to the destination station, an energy-saving optimization method for train timetable was proposed considering synchronous allocation of the travel time between stations for multiple trains. Firstly, a set of driving strategies are developed based on the "four-stage" maneuvering strategy adopted by high-speed trains. In addition, taking traction distance and cruising distance as change factors, traction energy consumption and travel time between stations are divided into calculation objectives, and the linear relationship between traction energy consumption and travel time between stations in the optimal driving strategy set was solved. Finally, with the goal of minimizing the traction-energy consumption, an energy-saving timetable model for high-speed trains is developed based on the optimal allocation of travel time between stations. The model considers the constraints of the multiple trains' total travel time, variable value range constraints and safety interval time constraints of the train timetable. In terms of model estimation, Lagrange relaxation algorithm is used. The original problem is decomposed into several sub-problems that could be solved independently in each section by relaxing complex constraints into the objective function. Therefore, the exact solution is obtained by subgradient optimization, and the model achieve the goal of synchronous allocation of travel time between stations for multiple trains. In the end, the validity of the proposed model is further examined by a case study of Baoji-Lanzhou high-speed railway corridor. The results show that the 10 trains totally saved 595.958 traction-energy and the average energy-saving rate reached 1.2% by re-allocating the travel time between stations. From the perspective of timetable, the energy saving method by adjusting the travel time between stations is of great practical significance with the reason that it has a small impact on the magnitude of the adjustment of train timetable. In addition, the calculation time of the proposed model and algorithm is 10 s, which can effectively improve the solving efficiency for the high-speed railway with a large number of trains
An Overview on Research Progress of Sensors for Detecting Safety of Lithium Batteries
ZHAO Xing, WANG Peng, CHAO Peipei, LI Ning, LIANG Xinmiao, DONG Honglei
2022, 40(6): 127-136. doi: 10.3963/j.jssn.1674-4861.2022.06.013
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In recent years, due to the frequent occurrence of lithium-battery accidents caused by thermal runaways, it is particularly important to apply the battery-safety monitoring systems. To improve the performance, extend the cycle life of lithium batteries and avoid the occurrence of those accidents, it is necessary to use sensor technique to monitor the working states of batteries in real-time. Based on the changes of physical variables in the batteries' working states, the commonly used safety detection signals include stress-strain, temperature, and gas. At present, safety-detection sensors for monitoring the signals are widely used in battery-state detection system. However, traditional sensors have some disadvantages, such as large volume, low sensitivity, and poor resistance to electrolytic corrosion. After outlining the working principles of the new fiber Bragg grating sensor, flexible film sensor and semi-conducting gas sensor, this paper summarizes the applications of the above three sensors in detecting stress-strain, temperature, and gas, and discusses the shortcomings of current studies from the perspectives of stability and sensitivity.The shortcomings include the poor applicability of the fiber Bragg grating sensor, the negative impact of the flexible film sensor on battery performance, and the low accuracy and short life of the semi-conducting gas sensor. The questions how to install the sensors into the battery cells in an economical, safe and practical way, how to reduce the influence of the sensors on the cycle performance of batteries in practice, and how to improve the stability, accuracy and sensitivity of sensor-signal transmission are crucial for the development of sensors for safety detection system of lithium-battery, which still need massive research on the sensor and battery design.

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