2021 Vol. 39, No. 1

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2021, 39(1)
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Abstract:
A Performance Analysis of Mixed Platoon Control under Communication Delay
XU Qing, WANG Jiawei, WANG Jianqiang, LI Keqiang, GAO Bolin
2021, 39(1): 128-136. doi: 10.3963/j.jssn.1674-4861.2021.01.015
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Based on technologies of automatic control and wireless communication, e.g., vehicle-to-vehicle(V2V)communication, intelligent and connected vehicles(ICVs)are believed to improve traffic performance significantly. This paper investigates the performance of mixed platoon systems consisting of ICVs, adopting cooperative adaptive cruise control(CACC), and human-driven vehicles(HDVs)under the influences of communication delay in vehicular networks. From microscopic car-following behaviors, the minimum time headway for string stability is obtained based on the frequency-domain transfer function and increases as time delay grows up, verified by numerical calculation. Large-scale traffic simulations under multiple penetration rates are conducted from traffic shockwaves, with three cases under consideration, including CACC without delay, CACC with delay, and adaptive cruise control(ACC), which degrades from CACC at an extensively considerable delay. Given the same headway for the three cases, extensive simulation results show that CACC without delay or with a communication delay of 1 s can reduce traffic perturbations and dampen traffic shockwaves, with no evident performance gaps. By contrast, ACC achieves a much worse performance compared to CACC.
A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic
HU Jia, AN Lianhua, LI Xin
2021, 39(1): 137-144. doi: 10.3963/j.jssn.1674-4861.2021.01.016
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A capacity model is developed to study freeway merging areas of a novel mixed traffic with human-driven vehicles and connected automated vehicles equipped with cooperative adaptive cruise control. The interaction mechanism of factors, such as road traffic characteristics, road structure, and mainline traffic state before the merge, is considered. The probability and statistics theory is used to analyze coupling relationships between penetration rate and platoon length. Furthermore, based on the gap acceptance theory, reduction effects of ramp merging traffic on the capacity of the merging area is analyzed. The capacity model of freeway merging areas with partially connected automated traffic is established to quantitatively describe how the capacity changes with the penetration rate and platoon length of connected automated vehicles under various road conditions. The parameters of road traffic characteristics, road structure, and part of the traffic state before the ramp merge are calibrated according to the actual traffic condition, which improves versatility and transferability of the model. A Vissim simulation platform with an embedded vehicle dynamics module is developed to evaluate the model. The results show that the accuracy of the model is generally over 80%. The model performed well under various penetration rates and platoon lengths of connected automated vehicles.
A Cooperative Control Model of Continuous Signal Intersections for Connected Vehicles
WANG Pangwei, FENG Yue, DENG Hui, WANG Yunfeng, WANG Li
2021, 39(1): 145-154. doi: 10.3963/j.jssn.1674-4861.2021.01.017
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Intelligent traffic signal control is an essential means to alleviate traffic congestion. A continuous traffic signal control model based on the upper and lower neural networks is proposed to solve the limitation of the traditional reinforcement learning algorithm at continuous multiple intersections. In this model, the local optimal control strategy in the current state is selected by the lower neural network. Then, the secondary adjustment can be made by the upper neural network according to the delay of vehicles at intersections. A global control strategy is applied to the phase timing of multiple intersections. The model is verified by the SUMO simulation platform, taking three typical continuous intersections as case studies. The average vehicle delay reduces by 23.6% and 26% under low and high saturation, and the queue length reduces by 8.4% and 9.4%. The results show that the road capacity of continuous intersections can be improved based on the proposed model, which provides an effective technical method to alleviate urban traffic congestion.
A Simulation Evaluation of Traffic Flow Efficiency of Urban Expressways under Cooperative Vehicle-infrastructure Scenarios
SUN Lishan, CHEN Yingda, KONG Dewen, ZHANG Tong, SONG Yongchang
2021, 39(1): 155-163. doi: 10.3963/j.jssn.1674-4861.2021.01.0018
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This paper collects and extracts vehicle trajectory data on the road section of Sifang Bridge in Beijing during the morning peak hour to study impacts of the cooperative vehicle-infrastructure system(CVIS)on expressways under different levels of information interaction between vehicles. Driving behaviors of vehicles are analyzed under the vehicle-road collaboration scenario to calibrate parameters of the conventional driving scenes and information interaction scenes for driving models. The ratios of vehicles running at desired speed, transverse vehicle distance contraction, longitudinal vehicle distance contraction, and traffic capacity expansion are selected to evaluate operating efficiency of the vehicles, and the ratio of vehicle lateral offset distance reduction is selected as an index to evaluate space occupancy rate in the vehicle-road collaboration scenario. A simulation model is developed to analyze the impacts of different levels of information interaction on traffic flow. The results show that vehicle operation efficiency increases with an improved level of information interaction, and improvement of road capacity is the most significant. When the level of information interaction increased from level 4 to level 1, the traffic capacity is expanded by 19.42%, 28.06%, 46.48%, and 74.62%, respectively, and the rest of the index values are slightly improved during the simulation period. The vehicle lateral offset distance under the information interaction scenario is reduced, and the reduction ration is 17.33% under the scenario of level 1 information interaction. It indicating that the lateral safety of the vehicle under the same lane width is improved.
Lane-change Control for Unmanned Vehicle Based on REINFORCE Algorithm and Neural Network
YAN Hao, LIU Xiaozhu, SHI Ying
2021, 39(1): 164-172. doi: 10.3963/j.jssn.1674-4861.2021.01.0019
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For lane change and overtaking of unmanned vehicles, the paper studies the lane change control strategy of unmanned vehicles based on the REINFORCE algorithm and neural network. The feedback, control input, and output limit requirement of the vehicle dynamics model are determined. The REINFORCE algorithm is used to design the structure of the neural network controller and the training plan of the controller. For too large data value and variance of the experience pool, a preprocessing method of the experience pool data is proposed to improve the controller training plan. Besides analyzing sparse reward distribution in the reinforcement learning process, a reward shaping solution based on logarithmic function is proposed combined with the running condition of unmanned vehicles. Compared with PID and LQR controllers, the experiment is carried out. The results show that the proposed control strategy has smaller maximum error compared with PID, with a safer lane-change process. The performance of the control strategy is similar to LQR, which proves its feasibility for the lane change control task of unmanned vehicles. Also, the execution time of the control strategy in different platforms is recorded to prove its real-time performance and feasibility in lightweight platforms.
Invited Contribution
Coupling Coordination Degree of Transportation, Logistics, and Tourism: A Case Study of Wuhan City
GE Xiurun, TANG Hua, LI Kunyao, CHU Duanfeng
2021, 39(1): 1-6. doi: 10.3963/j.jssn.1674-4861.2021.01.0001
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Abstract:
It is significant to study the coordination between urban traffic and other systems.The paper constructs the indicators system reflecting development levels of three systems, transportation system, logistics industry, and tourism industry, to study their coordination degree.A coupling coordination model is introduced to analyze the coupling coor- dination of the systems.The development data of the transportation system, logistics industry, and tourism industry in Wuhan city from 2010 to 2017 is taken as a case study for a comprehensive empirical analysis.The results show that the overall evaluation value continues to grow.The coordination coupling degree of the transportation system and logis- tics industry increases from 0.0841 in 2010 to 0.9301 in 2017, and that of the transportation system and tourism indus- try from 0.1197 in 2010 to 0.9314 in 2017.The coordination degree of the three major systems successively experienc- es from severe imbalance to high coordination.The results are consistent with the actual development of Wuhan city, which proves the effectiveness of the proposed method.
Overview
A Visualization Analysis and Development Trend of Intelligent Ship Studies
ZHANG Di, ZHAO Yinxiang, CUI Yifan, WAN Chengpeng
2021, 39(1): 7-16, 34. doi: 10.3963/j.jssn.1674-4861.2021.01.002
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This paper conducts a comprehensive literature review of intelligent ship based on the studies published on the China Knowledge Network (CNKI) and Web of Science databases to investigate the status quo and the cutting, edge issues in development of intelligent ship.The knowledge graphs are used to systematically present the trends, frontiers, and hot spots in intelligent ship from time, author, institution, and keywords.On this basis, the research trends and hot issues of intelligent ship are analyzed from intelligent situational awareness, collision avoidance, intelligent control, network communication, and the rule of law study. Besides, three key research directions are proposed, including human, machine integration and decision, making technology for intelligent ship, risks of formation navigation, and risk evaluation of mixing navigation of traditional/intelligent ships. The results show that since 2015, published papers related to intelligent ship have increased more rapidly than which between 2010 and 2014, with an average growth rate of 58%(more than 14 articles per year). Key research institutions in China contributing the most to this field include Wuhan University of Technology, Dalian Maritime University, and Shanghai Jiaotong University. Major foreign research institutions include Norwegian University of Science and Technology and Delft University of Technology. Research hotspots in intelligent ship refer to situational awareness, intelligent collision avoidance, intelligent control, network communication security, and legal security.
Transportation Safety
Driving Risks of Interchange Ramps Based on Vehicle Acceleration Data
DING Rui, LIU Jun, JIANG Yan, XU Jin
2021, 39(1): 17-25. doi: 10.3963/j.jssn.1674-4861.2021.01.0003
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Abstract:
More than 30 participants are tested in actual passenger-car driving test at Nanshan Interchange and Jiangnan Interchange in Chongqing to clarify the operating characteristics and driving risks of interchange ramps. Using high-precision equipment such as Speedbox and Mobileye, the continuous running data of passenger cars on four roundabout ramps are collected, including driving speed, lateral acceleration, and longitudinal acceleration. The running statuses of vehicles on roundabout ramps are specified. Besides, the G-G diagram, characterizing the relationship between lateral and longitudinal acceleration, is used to analyze the driving risk during ramp driving. The danger levels at different positions of the interchange ramps and the high-risk sections of dangerous driving behavior are determined. The results show that: ① The lateral acceleration and speed of the passenger cars on the interchange ramps are distributed in a triangle, and the longitudinal acceleration and speed are distributed in an elliptical shape. ② The proportion of dangerous driving behaviors on small radius curve ramps is higher than that on large radius curve ramps. ③ By counting the proportions of dangerous driving-behavior points of different sections, the dangerous sections of the ramps are divided into low risk, medium risk, and high risk. ④ Male drivers have a higher proportion of dangerous driving behaviors on the interchange ramps than female drivers, and adventurous drivers have a higher proportion of dangerous driving behaviors than that of drivers of other driving styles. ⑤ The dangerous high-incidence road sections of interchange ramps are usually located in the sections with drastic speed changes, namely the deceleration section of the turn and the acceleration section of the exit.
An Acceptance Model and Risk Analysis of Automated Vehicles Based on SEM
LI Jipu, HE Yi, SUN Changxin, PENG Jianhua, CHEN Tao
2021, 39(1): 26-34. doi: 10.3963/j.jssn.1674-4861.2021.01.0004
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Abstract:
A model is developed to accept automated vehicles based on the TAM model to study public acceptance of automated vehicles and its influencing factors. The relationship among external variables, latent variables, cognitive variables, and social acceptance of automated vehicles assumed in the model is verified by Pearson and Kendall correlations. A linear regression model and an acceptance-based structural equation model are established to explore the relationships of relevant factors, various variables, and public acceptance of automated vehicles. The results show that the cognition of legal ethics positively affects the acceptance intention of automated vehicles(E =0.038, and P < 0.001). Driving age and driving frequency negatively affect the acceptance of automated vehicles(E =-0.044, and P < 0.001). Educational background has a significant positive impact on the acceptance of automated vehicles by promoting the public's positive cognition and suppressing the negative cognition(E =0.172, and P < 0.001). Functional cognition has a significant positive impact on the acceptance intention of automated vehicles(E =0.444, and P < 0.001)
Text Mining for Causes of Ship Accidents Based on PMI and BTM
YU Weihong, FU Piaoyun, REN Yue, WANG Qingwu
2021, 39(1): 35-44. doi: 10.3963/j.jssn.1674-4861.2021.01.0005
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Abstract:
The paper proposes a method of semantic mining for ship accident investigation reports from words and topics to automatically extract knowledge of water traffic safety from massive ship accident investigation reports. Moreover, 100 investigation reports on the self-sinking accidents of ships are used as corpus for specific excavations. At the word level, the PMI algorithm is used to mine frequent co-occurrence word patterns from the texts describing the causes of the accidents, and relationships between accident-causing factors are revealed through the co-occurrence of text feature words. At the topic level, the BTM algorithm is used to model the texts describing the causes of the accidents, and the modeling results are evaluated by topic log-likelihood and coherence. The feature words representing the causes of foundering accidents are clustered through topic modeling, and the occurrence probability of each cause is preliminarily quantified according to the distribution of topics in the corpus. According to the results on the predictive ability of the topic model using 500 new data sets, the topic model can recognize 100% of the domain-independent words and automatically ignore them. For 85.6% of the words in the corpus, the topic model can attribute them to a certain topic representing a specific cause. For about 14.4% of the words, the topic boundary is not obvious, so it is not easy to attribute them with a high probability.
A Traffic Impact Analysis of Urban-road Traffic Accidents Based on Coupling Influences of Accident Characteristics
HE Yaqin, ZOU Jiacui
2021, 39(1): 45-51, 63. doi: 10.3963/j.jssn.1674-4861.2021.01.006
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Abstract:
After an urban road traffic accident, the number of lanes for the vehicle to pass and the capacity of urban roads are reduced due to lane occupation by accident vehicles. It causes queuing and traffic congestion, which affects traffic operations. A two-way six-lane urban road is taken as a case study. The traffic operation under traffic accidents is simulated by Vissim simulation software, with the traffic impact under four factors analyzed: traffic flow, occupation type, incident duration, and overtaking on the lane. The results show that greater traffic flow means longer incident duration, more occupied roads, and greater traffic accidents. When the traffic volume reaches 3 400 veh/h(level-D service), the delay of vehicles occupying one lane increases significantly until the traffic volume reaches 4 000 veh/h; the delay of occupying lane 2 is greater than that of occupying lanes 1 and 3. When the traffic volume reaches 1 900 veh/h(level-B service), the delay of vehicles occupying two lanes increases significantly until the traffic volume reaches 2 700 veh/h, which gradually stabilizes. Under the same occupation situation, vehicle delays with the traffic flow under different incident durations are generally the same. When the service levels of the accident road are D, E, and F, with the service levels A, B, C, and D of the opposite road(the accident occupies one lane inside)and the service levels A, B, and C of the opposite road(the accident occupies two lanes inside), tailgating and overtaking can reduce the vehicle delay on the accident road section.
Transportation Information Engineering and Control
A Coordinated Control Method of Longitudinal Ship Speed Based on Model Predictive Control
WU Wenxiang, CHU Xiumin, LIU Chenguang, MAO Wengang
2021, 39(1): 52-63. doi: 10.3963/j.jssn.1674-4861.2021.01.0007
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Abstract:
Multi-vessel cooperative navigation has significant advantages in maritime search and rescue, resource exploration, and polar shipping. Cooperative control of longitudinal speed is the key to realizing cooperative navigation of ships. A longitudinal dynamics model of the ship considering influences of wind is constructed by analyzing the relationship among ship propeller speed, acceleration, and speed. A ship spacing model based on the variable time-distance strategy is invoked to realize the correlation between the acceleration and following distance of the front and rear ships. After designing the multi-ship speed-control objective function considering multiple constraints such as speed and acceleration, the optimization problem is solved in real-time using the method. Finally, the simulation is verified by Matlab. The results show that the proposed cooperative control method of longitudinal ship speed, based on the model predictive control method, can stably follow the front ship under the working conditions of acceleration, deceleration, and uniform speed. Its distance tracking errors are 0.092 5, 0.192 8, and 0.166 2 m, respectively. Compared with the PID method, the proposed method has better convergence, tracking accuracy, and anti-interference ability.
An Estimation Model of Section Traffic Parameters Based on Connected ADAS Spatiotemporal Data
MA Tianyi, WEN Jiaqiang, WANG Liyuan, LYU Nengchao, WANG Yugang
2021, 39(1): 64-75. doi: 10.3963/j.jssn.1674-4861.2021.01.008
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Abstract:
Real-time acquisition of traffic parameters is an essential basis for road traffic control. A method for estimating section traffic parameters using the connected ADAS data is studied for the limited observation range of fixed detectors and the great demand for floating vehicles. A traffic parameter-estimation model under unsteady traffic conditions is established by analyzing the relationship between forward target parameters perceived by on-board ADAS and traffic parameters, the definition of generalized traffic volume, and the relative motion characteristics of the ADAS vehicle and its neighboring vehicle in a multi-lane environment. According to the simulation, the calibration data set and the verification data set are obtained to complete the parameter calibration and verification of the model. Also, the paper discusses the influences of time and space resolutions, and ADAS vehicle penetration rates on the estimation accuracy of the model. The analysis shows that when the time resolution is reduced by 5 min, the estimation error is reduced by 3.4% on average; reducing the time resolution can improve the estimation accuracy of the proposed model. When the space resolution is reduced by 500 m, the estimation error of flow and density is reduced by 1.68% on average; however, it may lead to an average increase of 5.19% in speed estimation error. The increased penetration rate of ADAS vehicles can enhance the overall fit between estimated traffic parameters and observed traffic parameters in the time-space area of the road sections. In the context of the gradual application of ADAS, the proposed model of traffic parameter estimation can quickly obtain the traffic volume information in the continuous time-space range of the road sections.
A Multi-vehicle Cooperative Control Algorithm Based on Data-Driven Adaptive Control Strategy for Heterogeneous Human-driven and Autonomous Vehicles
WANG Huixian, LI Bo, ZHENG Hongjiang, CHEN Wei
2021, 39(1): 76-86. doi: 10.3963/j.jssn.1674-4861.2021.01.009
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Abstract:
Traditional model-based control methods need to obtain parameters of driving behaviors of drivers and system dynamics of vehicles in a multi-vehicle cooperative control system. However, these parameters cannot be obtained accurately in actual transport systems. A data-driven adaptive dynamic programming control algorithm is proposed to solve the problem. Under the environment of mixed manned and unmanned vehicles, the horizontal and vertical control models of the multi-vehicle cooperative control system are analyzed to derive its state equation. A recursive numerical method is used to approximate an optimal solution. Optimal control inputs are obtained by optimizing a feedback control matrix. The proposed algorithm simplifies control input parameters of the system. Besides, the optimal control of unmanned vehicles can be realized only using two parameters of basic safety messages of vehicles in real-time as the controller's inputs: steering the angel of the fore wheel and expected longitudinal acceleration. A co-simulation is conducted based on CarSim and Simulink. The results show that the proposed algorithm has simple control parameters, fast convergence speed, high control accuracy, and strong adaptability. It ensures the stability of the multi-vehicle cooperative control system and controls unmanned vehicles in platooning to maintain the desired velocity and desired heading. Moreover, its lateral error between the actual trajectory and expected trajectory tends to zero during driving on the road with arbitrary curvature.
Test Scenarios of Automatic Emergency Braking System at Intersections Based on NAIS
ZHANG Shibo, HE Zhijian, LIAO Jingqian, LI Pingfei, XIAO Lingyun, XU Qianyuan
2021, 39(1): 87-96. doi: 10.3963/j.jssn.1674-4861.2021.01.010
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Abstract:
An intersection test scene of automatic emergency braking systems is established for roads in China. A total of 582 vehicle-to-vehicle accident cases are obtained from the National Automobile Accident In-Depth Investigation System(NAIS). The number of accident samples and the level of accident casualties are used to cluster the accident data and extract typical parameters of the clustered categories. Then 17 typical scenes of vehicle-to-vehicle accidents at intersections are obtained. Based on typical accident scenarios, three key parameters of maximum collision speed, collision angle, and collision type are added so that the final test scenario can reflect the actual accident statistics more accurately than existing studies.
Transportation Planning and Management
Impacts of Environmental Concern on the Approval of Low-carbon Traffic Policy
LIU Lihua, WANG Wei, LIU Jianrong, HUA Xuedong
2021, 39(1): 97-102. doi: 10.3963/j.jssn.1674-4861.2021.01.011
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The government should formulate transportation policies to encourage low-carbon travel, thereby reducing automobile exhaust pollution. Designing effective policy requires a thorough understanding of the psychological factors that influence low-carbon travel. The structural equation model(SEM)is used to study the impacts of environmental concern on the approval of the low-carbon transportation policy. Based on the basic principles of SEM, a model hypothesis is established, and the data is analyzed by Mplus. The results show that environmental attitudes directly influence environmental behaviors and public transportation preference. Meanwhile, environmental behaviors directly affect public transportation preference, and public transportation preference directly influences the approval of the low-carbon traffic policy. However, environmental attitudes and behaviors do not directly influence the approval of the low-carbon transportation policy. At the 95% confidence level, gender, marital status, private car ownership, house ownership, and whether or not drive to work have no significant effect on the SEM. However, at the 90% confidence level, gender and education level have significant effects on SEM.
Travel Characteristics and Influencing Factors of Bike Sharing Based on Spatial Lag Model
YU Erze, ZHOU Jibiao
2021, 39(1): 103-110. doi: 10.3963/j.jssn.1674-4861.2021.01.0012
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The paper aims to investigate the spatial-temporal characteristics of the bike sharing system(BSS)and quantify factors affecting BSS usage from the urban spatial environment. The spatio-temporal analysis is conducted to investigate the mobility pattern of BSS using the massive IC-card data in central urban area of Ningbo, China. By considering the spatial autocorrelation of pick-up and drop-off, a spatial lag model is established to identify the internal relationship between BSS usage and spatial variables from population density, road distribution, public transportation, station infrastructure, and built environment. The results show that: ①The global Moran's I for pick-up and drop-off on weekdays and weekends is 0.294, 0.281, 0.272, and 0.271, indicating the spatial correlation is significantly positive. ②The goodness of fit is 0.431, 0.424, 0.412, and 0.401, showing that these models have good fitness and explanatory. ③There are also significant temporal differences between road distribution and built environment variables influencing BSS usage. The length of bus lanes is negatively correlated with the usage demand during weekends, and the POI mixing degree positively affects the demand for pick-up and drop-off on weekdays.
An Analysis of COVID-19 Propagation Model in Public Transportation Networks and Effectiveness of Epidemic Prevention Strategies
MOU Zhenhua, LI Xiang, YAN Kangli, GUO Jijie
2021, 39(1): 111-117. doi: 10.3963/j.jssn.1674-4861.2021.01.0013
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Public transportation system is a critical potentiality space where airborne viruses have to spread between people. The study of the spread of viruses in the public transport system can accurately guide public transport epidemic prevention strategies. The two-layer public transportation network model, particle travel rules, and SEIR model are used to establish a public transportation network propagation model. Based on the background of virtual regional space and bus line network, characteristics of the two-layer network model are used to analyze the process of virus transmission on the bus and at the bus station. Both macro and micro epidemic prevention strategies are developed to analyze their effects. Public transportation causes the virus to spread on a large scale, and buses and bus stops are the most critical transmission links. For the public transportation epidemic prevention strategy, when the macro-control strategy cuts off the proportion of public transportation lines φ1 >0.5 or stops the proportion of public transportation stations φ2 >0.4, the final proportion of the immunized population will drop to below 0.3. The micro-adjustment strategy needs to control the departure interval td < 4 and the full load rate simultaneously α < 50%, so the final immune population ratio is less than 0.4, with the optimal prevention and control effect.
A Dynamic Service Network Design for Railway Container Transportation and Benders Decomposition
JIANG Yuxing, NIU Huimin, GAO Ruhu
2021, 39(1): 118-127. doi: 10.3963/j.jssn.1674-4861.2021.01.014
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A method of dynamic service network design for railway container transportation is studied, considering the transfer schemes of containers. A linear programming model of the dynamic service network design for railway container transportation is constructed to minimize the total cost.In accordance with the characteristics of the problem, a solution approach based on Benders decomposition is developed. Then, the formulation is decomposed into a master problem of service network design and subproblems of container flow allocation. The cuts of the master problem are constantly generated by utilizing the solutions of dual subproblems to solve them iteratively. Some valid inequalities are used to tighten the master problem, thus overcoming slow convergence. The effectiveness of the model and algorithm is demonstrated, taking the network constructed by railway container terminals in Beijing and Zhengzhou as a case study. The numerical results indicate that for the design of large-scale dynamic service network, the improved algorithm spends 46 s to obtain an optimized solution, and the Gap is 1.56%. The unimproved Benders decomposition takes the same time, and the Gap is 45.17%. The application of improved strategies can improve calculation. The total cost of the optimized service network is reduced by about 20% compared to the service network with direct transportation organization. Compared with the existing plans for container train service, the optimized departure time and operation frequency of container trains can meet the transportation demand, ensuring that each container flow can be delivered to the destination within the specified transit period.

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