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A Review and Prospect of Urban Public Transit Level-of-Service Research MAO Bao-hua , WANG Min , HO Tin-kin , CHEN Hai-bo 2022, 22(1): 2-13.  DOI: 10.16097/j.cnki.1009-6744.2022.01.001 Abstract ( )   PDF (2428KB) ( )   PDF(English version) (803KB) ( 310 )   This paper summaries the evolution of the concept of level- of- service (LOS) in transportation system and describes the characteristics of LOS in different stages. The implication of LOS has expanded from merely focusing on road design to incorporate multi-modal and wide operational areas. The LOS of public transit include two major components: transport efficiency and passengers' comfort, which are respectively associated with transport product design and passengers' perception to the services. The paper further reviews the LOS evaluation and classification research in the public transport system. These evaluation methods are relevant to the LOS elements and can thus be divided into the objective evaluation that are based upon transport efficiency and the subjective evaluation that focus on passengers' perceptions. Because of the differences in each country, the LOS classification of the Transportation Research Board may not be applicable to all countries and situations. The study then analyses the research and practice of public transit LOS in China and suggests that the existing regulations in China can be improved to clearly define the connotation of public transit LOS and include a systematical classification standard that applicable to China. The challenges in improving the LOS are discussed from the aspects of the formation of LOS, the complexity of evaluation factors, multi-links involved in a trip, and the need for government support and investment. Based upon the practices inurban public transit in China, the following three topics are worthy of in-depth study in the future: define and evaluate public transit LOS in consideration of full travel chains; Measure and evaluate the public transit LOS considering the uneven distribution of transit service quality; Satisfaction survey methods focusing on passenger perception differentiation and LOS evaluation methods based on advanced information technology. The paper also provides suggestions on taking LOS improvement as a starting point to promote the enhancement of public transit operation quality and efficiency. References | Related Articles | Metrics

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Risk Propagation Dynamics Simulation on Multimodal Transport Network for Oversize and Heavyweight Cargo ZHANG Ying-gui , XIAO Yang, LEI Ding-you, LU Qiang 2022, 22(1): 14-23.  DOI: 10.16097/j.cnki.1009-6744.2022.01.002 Abstract ( )   PDF (1954KB) ( )   Multimodal transport organization for oversize and heavyweight cargo has the characteristics of high risk. To uncover master the risk propagation law and improve the ability to prevent and control risks of the multimodal transport network for oversize and heavyweight cargo(MOHC), the overall consideration for the characteristics of MOHC and the influencing factors of risk propagation was used to analyze the risk propagation process. The risk propagation function for MOHC was constructed to establish the risk propagation modal without time delay and with time delay and external factors, respectively, so that its dynamic propagation process is clarified. The simulation results indicated that the loading reinforcement factor had a greater impact on the risk propagation of MOHC in comparison to the path decision factor and a safer loading reinforcement scheme could efficaciously reduce the initial risk propagation peak of MOHC; Reducing the risk propagation rate and increasing the cure rate could effectively control the risk propagation scale in MOHC; The degree of time delay had a significant effect on the risk propagation of MOHC, which is nonlinear and positively correlated; The random interference of external factors can weaken the propagation of risk to a certain extent; Before the risk diffusion equilibrium point in time of MOHC became unstable, appropriate measures could have been taken in time to prevent the MOHC from collapsing due to the uncontrolled risk. References | Related Articles | Metrics

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Energy Consumption Measurement and Energy-saving Potential Analysis of Freight Corridors from Perspective of Life Cycle ZHU Li-chao , ZHEN Wei , LIU Zhao-ran 2022, 22(1): 24-29.  DOI: 10.16097/j.cnki.1009-6744.2022.01.003 Abstract ( )   PDF (1336KB) ( )   Systematic energy consumption measurement and energy-saving potential analysis of freight transportation are crucial to formulating energy-efficient strategies. An analysis framework for energy consumption measurement and energy- saving potential of freight transportation is constructed from life cycle perspective to quantify the impact of various supply-side and demand-side factors and to identify the key influencing factors. Given that the differences in resource endowments and supply- demand characteristics in different regions, this framework is applied to the YiwuNingbo container freight corridor. The results show that: ignoring life cycle and secondary activities of transportation chain, especially the former, would underestimate the energy consumption, which would lead to inaccurate evaluation of the contribution of each energy-saving strategy; the direct energy consumption of road transportation for embodied energy consumption elasticity is 0.67, which is much higher than that of other influencing factors of the supply- side and demand-side, and it should be given the top priority for freight transportation energy-saving in the short-/mediumterm; under the current conditions, the energy-saving effect of road-to-rail strategy is limited if without other strategies, and the energy-saving strategies for direct energy consumption are recommended in the short-/medium-term, and the energy-saving strategies for indirect energy consumption are recommended in the medium-/long-term. References | Related Articles | Metrics

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Pricing and Ordering Decisions of China Railway Express Considering Capital Constraint ZHANG Xiao-ming , XU Fang , JIANG Wen-hui , JIANG Chao-zhe 2022, 22(1): 30-36.  DOI: 10.16097/j.cnki.1009-6744.2022.01.004 Abstract ( )   PDF (1539KB) ( )   In view of the financial constraints of small and medium-sized enterprises for China Railway Express, this paper considers the demand characteristics of transportation price and service quality, and develops a two-echelon logistics service supply chain game model which considers China Railway Express and an international freight forwarding agent. The pricing solutions and profit functions are analyzed under four scenarios without financial constraints, with bank financing, China Railway Express financing, and centralized decision. With the goal of maximizing the profit function, this study examines the influence of the freight forwarding agent's initial funds and transportation service quality on the pricing and financing decisions for China Railway Express and the freight forwarding agent, verifies the feasible condition of different financing modes selection, and then performs numerical analysis. The research shows that capital constraints would result in an increase of the transportation price of China Railway Express; the China Railway Express financing mode can provide lower transportation price than bank financing. In the China Railway Express financing, the profits of both parties are significantly affected by the freight forwarding agent's initial funds. Only when the initial funds are less than a certain critical value, both parties would choose the mode of China Railway Express financing. The overall performance of the supply chain under China Railway Express financing is higher than the mode of bank financing. References | Related Articles | Metrics

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A Molecular Dynamics-based Car-following Model for Connected and Automated Vehicles Considering Impact of Multiple Vehicles ZONG Fang , WANG Meng, HE Zheng-bing 2022, 22(1): 37-48.  DOI: 10.16097/j.cnki.1009-6744.2022.01.005 Abstract ( )   PDF (1927KB) ( )   The car- following control of connected and automated vehicles (CAV) is studied under mixed traffic flow with regular vehicles. Considering the factors of velocity, headway, and the velocity and acceleration difference of multiple front and rear vehicles, this paper constructed a car- following model for CAVs by using the molecular dynamics to express the impacts of different surrounding vehicles on the host one. The car-following process of CAVs was then described when driving in the traffic mixed with CAVs and regular human- driving vehicles. The results of stability analysis show that, compared with the full speed difference model, the proposed model is more conducive to improving the stability of traffic flow due to the consideration of multiple front and rear vehicles' information. The simulation results indicate that, compared with the Cooperative adaptive cruise control (CACC) model provided by PATH laboratory, the average maximum error of our model is reduced by 0.19 m/s, the average error is reduced by 26.79%, and the fitting accuracy is improved by 0.91%. Besides, in the traffic flow mixed with CAV and RV, with the increase of CAV penetration, the average velocity of the platoon and volume increase gradually. The results of Hysteresis loops show that compared with the Full Velocity Difference (FVD) model, the stability of traffic flow under the CAV model in this paper is better. The proposed model can serve as an effective method for CAV control under both homogeneous traffic flow or heterogeneous flow mixed with CAVs and human- driving vehicles. Under the situation that it is difficult to carry out the field test of heterogeneous flow mixed with CAVs and human-driving vehicles, this study provides a theoretical basis and model support for vehicle control as well as infrastructure planning and design. References | Related Articles | Metrics

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Video-based Vehicle Speed Measurement Method Using Multiple Intrusion Lines TIAN Hui-juan, LIU Jia-wei, ZHAI Jia-hao, DENG Lin-lin 2022, 22(1): 49-56.  DOI: 10.16097/j.cnki.1009-6744.2022.01.006 Abstract ( )   PDF (3025KB) ( )   To improve the accuracy of vehicle speed detection in videos, this paper proposes a video- based vehicle speed detection method based on multi-intrusion lines. In the method, the multiple intrusion lines with known relative distance in the video are established, and the frames is detected when the vehicle passes through each intrusion line. The vehicle speed is calculated by the probability density function model which is generated by combining the frames, the sampling time of the camera, and the distance among intrusion lines. The performance of the model is verified by building simulation environment. The results show that the performance of the model can be improved by reducing the sampling time of the camera and increasing the number of intrusion lines and the distance among the intrusion lines. The method can decrease the error rate of detecting vehicle speed under different detection conditions. The Deepsort+ YOLOv5 target tracking algorithm is used to realize the speed detection of the vehicle in the video. At the same time, the method is compared with the mainstream video-based vehicle detection methods on the BrnoCompSpeed comprehensive dataset. The results show that the average error rate obtained by the method is 1.40%, which is lower than the mainstream video-based vehicle speed detection methods. References | Related Articles | Metrics

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A Calculation Method of Vehicle Collision Probability Based on Roadside Millimeter Wave Radar MA Xiao-long , YU Qiang , LIU Jian-bei 2022, 22(1): 57-66.  DOI: 10.16097/j.cnki.1009-6744.2022.01.007 Abstract ( )   PDF (2628KB) ( )   The purpose of this research is to study the collision risk of the following vehicles in the same lane on the freeway. A new method for calculating the collision probability between leading and following vehicles was proposed by vehicle deceleration. The minimum deceleration speed required by the leading vehicle was deduced by considering three different collision cases. Furthermore, a large number of real vehicles driving state data were obtained based on roadside millimeter- wave radar. Trajectory, velocity, and deceleration were included. The Generalized Pareto Distribution (GPD) was used to develop the distribution model of deceleration. Based on the GPD model, the occurrence probability of minimum deceleration was calculated, and the probability was determined as the collision probability. The results showed that about 99.10% of vehicle acceleration fluctuated within the range of [-1, 1] m·s-2 . The acceleration of most vehicles in this study section was very small. The distribution of deceleration showed the feature of a "long tail". The proportion of large braking deceleration was very small. The acceleration distribution of lane 1 and lane 2 on the inside was more concentrated than that of lane 3. The acceleration distribution of large trucks was more concentrated than that of small vehicles. Furthermore, based on the actual and simulated dangerous scene data, the calculation results of the proposed method were compared with those of the traditional method. It is shown that the calculation results of this method are continuous, especially it can quickly identify all kinds of dangerous scenes. References | Related Articles | Metrics

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Commuting Mode Choice Behavior in Rail and Bus Composite Network Based on Smart Card Data WANG Zi-jia , JIA Hui-hui, ZHU Ya-di , CHEN Feng 2022, 22(1): 67-73.  DOI: 10.16097/j.cnki.1009-6744.2022.01.008 Abstract ( )   PDF (1526KB) ( )   Rail transit networks and bus networks are the main components of the public transportation system. The study on the mode choice behavior of passengers on the composite network of rail transit and bus is helpful to improve the cooperative operation of the public transportation system. In previous studies, the travel integrity of different modes is overlooked with considering only rail or bus. In order to solve this problem, based on the traffic card data fusion and the topology fusion of rail and bus networks, a complete travel extraction method for passengers on the composite network is proposed. The essence of mode choice in the composite network is route choice. Therefore, based on the composite network of public transportation, five multinomial Logit choice models considering the combination of multiple factors are established to analyze the combination of factors that have the most significant impact on passenger travel behavior in the composite network. Finally, the model is applied to the public transportation network of Beijing with the credit card data in a working day. The results show that the choice model based on the complete trip is better than the choice model based on the trip stage. The mode selection behavior of commuters in the composite network is significantly related to the fare and the total travel time considering the bus time, waiting time, transfer time, and transfer times, and the total travel time has a greater impact. The influence of transfer and waiting time on the modeselection of passengers in the composite network is relatively low, and commuters prefer the route with a short total travel time. The research results can provide technical support for improving the degree of coordination between rail and bus. References | Related Articles | Metrics

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Estimating Truck Spontaneous Platoon Fuel-saving Potential Based on Trajectory Data TAN Er-long , LI Hong-hai , ZHONG Hou-yue , HUO En-ze , MA Xiao-lei 2022, 22(1): 74-84.  DOI: 10.16097/j.cnki.1009-6744.2022.01.009 Abstract ( )   PDF (2341KB) ( )   PDF(English version) (973KB) ( 210 )   This study explores the influence of the maximum truck platoon size and the number of trucks on a spontaneous platoon and evaluates the fuel-saving potential in the real world. A dynamic spatiotemporal search scope was proposed to ensure a certain degree of exploration and prevent vehicles from spending much waiting time caused by the excessive pursuit of a larger-sized platoon. Moreover, we used the truck trajectory data of Liaoning Province to mine the Longest Common Subsequence (LCSS) of trucks, and an integer programming model was built to get the platoon schedule under the maximum fuel saving. The results show that: (a) The platoons' fuel- savings will increase with the increase of transportation missions and the maximum platoon length; the average driving distance and fuelsavings of vehicles in the platoons will eventually converge to a range; (b) The platoon traveled distance does not necessarily rise with the increase about maximum platoon length, i.e., the maximum fuel- saving strategy is not the maximum driving distance strategy for a spontaneous platoon; (c) More fuel-savings can be achieved by continuously increasing the spatial search scope without considering the temporal search scope; while increasing the temporal search scope cannot receive more fuel-savings when the spatial search scope is not considered; (d) 4000 trucks' missions could save up to 2026.21 L per day if they form platoons spontaneously; the average fuel-saving in the situation of platoons with five trucks can be improved by up to 13.92% compared with those of platoons with two trucks. Suppose this algorithm is applied to a larger-scale truck data set, the number of spontaneous platoons will increase significantly, and correspondingly, more fuel consumption and pollutant emissions can be reduced, which has excellent application potential References | Related Articles | Metrics

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Car-following Decision-making and Model for Connected and Autonomous Vehicles Based on Safety Potential Field JIA Yan-feng, QU Da-yi, ZHAO Zi-xu, WANG Tao, SONG Hui 2022, 22(1): 85-97.  DOI: 10.16097/j.cnki.1009-6744.2022.01.010 Abstract ( )   PDF (3372KB) ( )   To improve the safety and efficiency of Connected and Autonomous Vehicles (CAV) following behavior, this paper investigates the characteristics of CAV autonomous decision making when perceiving the surrounding environment. A safety potential field model is proposed to describe the safety risk of CAV in driving, which includes lane marking potential field, road boundary potential field, and vehicle potential field. In the model, the existing vehicle potential field function has independent gravitational and repulsive expressions. A unified function of vehicle potential field based on Lennard Jones potential is also included considering the relationship of intermolecular interaction, and the parameter of vehicle's acceleration. The statistical analysis of the parameter reveals that the change of acceleration directly affects the distribution of vehicle potential field and reflect the dynamic trend of vehicle's safety potential field under different driving states. The safety potential field is applied to the car- following behavior of CAV, and the model's parameters are calibrated by Shanghai natural driving data-set. Compared with the existing classic Intelligent Driver Model(IDM)and Variable Time Headway (VTH) models, the simulation results show the proposed model produces smoother response curves in the three car-following scenarios designed to improve the safety and efficiency, which proves the effectiveness of the model. The research results can provide theoretical support for the upper control design of CAV, and this study provide a unique way for CAV safety technology research. References | Related Articles | Metrics

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Optimization Strategy of Lane-changing Trajectory Based on Vehicle Powertrain and Steering System LIAO Peng, TANG Tie-qiao 2022, 22(1): 98-105.  DOI: 10.16097/j.cnki.1009-6744.2022.01.011 Abstract ( )   PDF (2066KB) ( )   Most of the existing researches on lane-changing trajectory are separated for lane-changing trajectory planning and lane-changing trajectory tracking. This kind of trajectory normally produces some errors in the implementation. To eliminate this type of error and alleviate or solve the traffic problems caused by improper lanechanging behavior, this paper proposes a lane-changing trajectory optimization strategy considering vehicle powertrain and steering system. First, the Next Generation Simulation (NGSIM) data is used to obtain the main driving tasks in the lane-changing process, and the highD data is adopted to verify the tasks. Then, the lane-changing motion characteristics of the vehicle are analyzed based on the two- degree- of- freedom vehicle model. The lane- changing trajectory were realized by the powertrain and the steering system. The results show that the proposed strategy can achieve an economic, comfortable, and efficient lane- changing process on the premise of ensuring driving safety. The proposed strategies that consider economy, comfort and efficiency individually can reduce the fuel consumption per unit distance by 35.71%, the angular speed of front wheel angle by 94.58%, and the time required for lane-changing by 70%, respectively. The result indicates that the proposed lane-changing trajectory optimization strategy can alleviate the traffic problems caused by improper lane-changing driving behavior from a micro perspective and provide theoretical basis and methodological guidance for the design of driving assistance system. References | Related Articles | Metrics

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A Vessel Trajectory Reconstruction Method Based on Low-rank Minimization Matrix Denoising LIU Wen , WANG Wen-bo 2022, 22(1): 106-114.  DOI: 10.16097/j.cnki.1009-6744.2022.01.012 Abstract ( )   PDF (2335KB) ( )   The operation of (Automatic Identification System) AIS shows some frequent error data and missing data. This paper proposes a vessel trajectory reconstruction method based on low-rank minimization matrix denoising. This method realizes the trajectory reconstruction by denoising and the trajectory denosing and missing data become complete through a union method. In this method, the trajectory matrix is constructed and the corresponding longitudes of the points in the same column are ensured to be the same via linear interpolation to complete the missing values in the trajectories. Due to the large error in the completion results, the PLR (Patch-Based Low-Rank Minimization) algorithm is used to denoise and reduce bias. To further improve the completion effect, the trajectory matrix is decomposed into the IMFs (Intrinsic Mode Functions) with different frequencies by the 2D-VMD (Two-Dimensional Variational Mode Decomposition) and then denoised by the PLR algorithm. The reconstructed trajectories were obtained by combining the denoising results. The trajectories in the AIS of Wuhan section of Yangtze River were studied as an example. This method is robust and stable to the trajectories with different missing rate under two missing scenarios: random missing and continuous missing. In addition, the proposed method is tested and compared with the High- Accuracy Low- Rank Tensor Completion (HALRTC) Temporal Regularized Matrix Factorization (TRMF) and other methods. The results show the proposed method has higher accuracy especially when the trajectories have a high missing rate. References | Related Articles | Metrics

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Robust Train Operation Plan Based on Uncertain Passenger Demands for High-speed Railway Corridors ZHANG Chun-tian , QI Jian-guo , YANG Li-xing , GAO Yuan , GAO Zi-you 2022, 22(1): 115-123.  DOI: 10.16097/j.cnki.1009-6744.2022.01.013 Abstract ( )   PDF (2246KB) ( )   To minimize operating costs for the railway operation company, this paper formulated a robust optimization model to generate the train operation plan completely with considering the uncertainty of passenger demands (including deterministic passenger demand and fluctuation passenger demand), in which the light robustness technique was particularly applied. Specifically, the proposed model only needs the relevant parameters of the railway corridor and the distribution of passenger demands. Since it does not require an alternative set of lines, the proposed model can avoid the negative impact of the unreasonable alternative lines on the quality of the train operation plan. In addition, for computational convenience, we introduced linearization techniques to formulate an integer linear programming model. Finally, a series of numerical experiments were carried out on Wuhan-Guangzhou high-speed railway corridor to verify the effectiveness of the proposed model, where the MATLAB software with GUROBI solver was applied to obtain the optimized train operation plan. The optimized scheme can deal with the uncertainty of passenger demands and can be a reference for generating the high-speed railway train operation plan. References | Related Articles | Metrics

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Collaborative Optimization Strategy of Short-turning Plan and Passenger Flow Control in Urban Rail Transit JIA Bin , ZHU Ling, LI Shu-kai, LIU Jia-lin 2022, 22(1): 124-132.  DOI: 10.16097/j.cnki.1009-6744.2022.01.014 Abstract ( )   PDF (1770KB) ( )   In urban rail systems, the high passenger flow demand in peak hours would cause a large number of passengers stranded at platforms, which will not only bring potential safety risks to the system but also reduce the comfort of passengers. Meanwhile, the imbalance of passenger flow spatial distribution leads to the mismatch of supply and demand capacity, which reduces the utilization of train resources. This paper studies the collaborative optimization of train timetables combined with the full-length and short-turning routes and passenger flow control strategy. Considering the uncertainty of passenger flow, the passenger arrival rate is set as an uncertain variable. Then, based on the dynamic relationship between passenger flow evolution and train operation, an optimization model is established to minimize the number of stranded passengers, the number of passenger flow controlled, train operation time, and to maximize the measurement value of train resources utilization. A scenario- based chance- constrained optimization algorithm is designed to solve the model. Numerical experiments are carried out to verify the effectiveness of the model based on an urban rail line in Beijing. The results show that compared with the regular strategy, the collaborative optimal strategy proposed in this paper has greatly reduced the expected number of stranded people and train operation time, and better realized the balance between passenger cost and enterprise operation cost. References | Related Articles | Metrics

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Flexible Cooperative Scheduling Optimization of Multiple Rail Mounted Gantry Cranes in Railway Container Terminals ZHOU Yong , ZHANG Jie , ZHONG Ling-chong, LI Wen-feng , WANG Guo-dong 2022, 22(1): 133-141.  DOI: 10.16097/j.cnki.1009-6744.2022.01.015 Abstract ( )   PDF (1762KB) ( )   This paper proposes a mathematical model of mixed integer programming for Rail Mounted Gantry Crane Collaborative Scheduling (RMGCS) in railway container terminals. The objective of the model is minimizing the completion time and the operation interference and safety distance constraints between multiple RMGs are considered in the modeling. Based on the characteristics of the RMGCS problem, an Improved Sparrow Search Algorithm (ISSA) is proposed considering the flexible cooperative operation of multiple RMGs. A task allocation strategy and an interference judgment method are used to solve the conflicts between multiple RMGs. An adaptive nonlinearity dynamic safety value is designed to balance global and local search. The joiner's update movement method is improved to make it closer to the optimal solution in all dimensions. The largest-order-value (LOV) rule was introduced to map individuals from the real number vector to the container operation sequence. To verify the effectiveness of the problem and algorithm, the ISSA and other algorithms are used to solve container task examples with different sample sizes. The results show that the ISSA has better optimization effect in solving RMGCS problems with different sample sizes. In addition, the proposed flexible collaborative scheduling mode reduces the total completion time of loading and unloading operations with a sample size of 45 by 15.5% compared to the existing fixed- range sequential loading and unloading scheduling mode. References | Related Articles | Metrics

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Scheduling Optimization and Operation Mode Analysis on Ro-ro Tractor-and-trailer Transportation JIN Zhi-hong , YAN Hong , WANG Xiao-han , XING Lei, XU Qi 2022, 22(1): 142-151.  DOI: 10.16097/j.cnki.1009-6744.2022.01.016 Abstract ( )   PDF (2703KB) ( )   This paper focuses on a new operation mode of "loading while unloading" under the condition of "straight in and straight out", and compared with the traditional operation mode of "unloading before loading" under the condition of "stern in and out". A mixed integer programming model was developed for the scheduling optimization on tractorand-trailer inside the ro- ro terminal. The genetic algorithm was used to solve the model. The CPLEX solver and the algorithm were applied for the example analysis of different scales to verify the effectiveness of the model and the algorithm. Results show that, compared to the traditional operation mode of "unloading before loading", the new ship "loading while unloading" operation mode can reduce the operating cost by about 15%. For the new operation mode, when loading and unloading tasks are relatively heavy, the operation cost of unloading tasks close to the bow is higher; when loading and unloading tasks are relatively light, the operation cost of unloading tasks far from the bow is higher. Overall, the operating cost of the "loading while unloading" operation mode is lower than that of the "unloading before loading" operation mode. The study results provide references for the operation scheduling optimization of the ro- ro tractor-and-trailer transportation. References | Related Articles | Metrics

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Utility Simulation Evaluation of Dynamic Fines Strategy for Illegal Parking Based on Evolutionary Game MOU Zhen-hua , WANG Han-bing , LIN Ben-jiang , CHEN Yi-qun, JIN Cheng-cheng , CHEN Yan-yan 2022, 22(1): 152-162.  DOI: 10.16097/j.cnki.1009-6744.2022.01.017 Abstract ( )   PDF (2120KB) ( )   This paper aims to study the inhibitory effect of the improved dynamic fines strategy on illegal parking and obtain the optimal solution of the strategy. In this paper, the drivers and law enforcers are the two groups of players in the game. Based on the improved copy dynamic equation, the dynamic fines optimal control model is established with the goal of minimizing the total social cost. Then the equilibrium point and stability of the model are discussed, and the optimal solution of the model is solved by the Pontryagin principle of minimum. Finally, simulation tests were carried out on the violation restraint effect and the strategy cost of the dynamic fines strategy before and after the improvement. The simulation results show that: (1) The improved dynamic fines model can find a reasonable evolution direction of the parking violation problem, which can reduce the intensity of law enforcement while continuously reducing the probability of violation; (2) In a critical state, that is, the dynamic fine coefficient tends to a stable value, and the law enforcer maintains a short-term continuous law enforcement state. The improved dynamic fines strategy can reduce the amount of fines by changing the commonly used fine methods to realize the governance of illegal parking problems; (3) In terms of the efficiency of governing illegal parking, the critical state is compared with the most sensitive state, that is, continuous law enforcement is twice as fast as dynamic law enforcement; (4) Compared with the dynamic fines strategy before the improvement, the improved dynamic fines strategy has stronger violation restraint, lower strategy cost, and longer-lasting law enforcement effectiveness. The required enforcement is lower andthere will be no recurrence of illegal parking cycles in a short period of time References | Related Articles | Metrics

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Shared Parking Behavior Analysis Under Government Encouragement Based on Evolutionary Game Method JIA Fu-qiang, LI Yin-zhen , YANG Xin-feng, MA Chang-xi, DAI Cun-jie 2022, 22(1): 163-170.  DOI: 10.16097/j.cnki.1009-6744.2022.01.018 Abstract ( )   PDF (2749KB) ( )   : To better describe the effect of the traveler and parking space owner' strategies on the matching results of shared parking spaces, this paper develops an evolutionary game model with traveler and parking space owner involved and further analyzes the evolutionary stable state. The effects of different benefits, costs, and strategies on shared parking are illustrated by simulation analysis. The results show that both the traveler and the parking space owner can evolve to a stable equilibrium state through continuous learning, but the rate of evolution and the volatility of evolution are restricted by the benefits of both parties. The analysis also shows that a high initial ratio is needed to evolve to an ideal state. Both travelers and parking space owners can be encouraged to use shared parking by increasing revenue and reducing costs. At the same time, when the initial proportion is high, the proportion of income distribution also has great impact on the evolution process. It is found that the government incentive policy promotes the development of shared parking when the sharing platform provides reasonable revenue and expenditure. References | Related Articles | Metrics

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Dynamic Allocation Method for Shared Berth Considering Immediate and Reservation Demands LIU Yong-hong, LUO Xia , HU Jian-peng 2022, 22(1): 171-181.  DOI: 10.16097/j.cnki.1009-6744.2022.01.019 Abstract ( )   PDF (2616KB) ( )   This paper focuses on the dynamic parking spaces allocation of multi- residential shared parking lots with both immediate and pre-booking shared parking demands. The paper proposes a single period parking spaces allocation method, which includes the supply and demand of shared parking in the future. The results of berth matching in the current period are extended to the next periods, and then the shared parking spaces dynamic allocation process is proposed. The principle of priority berth matching for immediate shared parking demand is established with the goal of minimizing user costs. For pre-booking parking demand, the principle of uniformly allocating berths at the end of the current period is established with the goal of maximizing system revenue. The study defined four indicators to evaluate the effect of the model. Data from one day shared parking APP containing three residential communities in Chengdu were used to conduct empirical study and sensitivity analysis. The results indicate that: (a) when the proportion of immediate shared parking demand and pre-booking shared parking demand is between 0.4 and 0.6, the total objective performance reaches the desired value; (b) the berth allocation performance is better when the supply and demand of the future time intervals are considered at the current time interval. The more future periods are considered, the better of the overall target; (c) it often leads to the deterioration of the overall target in order to ensure the immediate parking demand can be allocated to parking spaces in priority. References | Related Articles | Metrics

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Individual and Household Commute Travels on Parallel Bottleneck Road Network DAI Qing, LIN Zheng-kui , QU Yi, ZHANG Jia-jia 2022, 22(1): 182-194.  DOI: 10.16097/j.cnki.1009-6744.2022.01.020 Abstract ( )   PDF (2698KB) ( )   The travel behavior of commuters is critical to determine the appropriate congestion strategies in the morning peak hours. This paper develops an equilibrium travel model for the mixed travel of individuals and households based on the bottleneck model in a parallel bottleneck road network. The user equilibrium, user costs, and system performance are analyzed with consideration of the impact of travel demand of two classes of commuters, the capacity at two bottlenecks, and the school-work start time difference. The results show that: (1) In a parallel bottleneck road network, the user equilibrium patterns of mixed travel are not unique. (2) Regardless of the changes in the capacity of the two bottlenecks, increasing the school-work start time difference is beneficial to individual commuters. However, due to the impact of the bottleneck capacity, the impact of increasing the school-work start time difference is uncertain for household commuters. (3) Adjusting the school- work start time difference provides an option to improve the efficiency and reduce the total travel cost of the system at certain circumstances but it is not effective for all situations to improve system efficiency. References | Related Articles | Metrics

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Risk Recognition of Older Pedestrian Traffic Crashes Based on XGB-Apriori Algorithm YUAN Zhen-zhou, GUO Man-ze, PENG Yong-xin, YANG Yang 2022, 22(1): 195-208.  DOI: 10.16097/j.cnki.1009-6744.2022.01.021 Abstract ( )   PDF (2568KB) ( )   In order to provide a recognition system for the safety features associated with older pedestrian traffic crashes severity levels. This paper applies Extreme Gradient Boost-Apriori (XGB-Apriori) to recognize the features of older pedestrian crashes in the road network. First, the methodology optimizes the weight of those crashes associated features by implementing the Select From Models(SFM) function from the XGBoost algorithm in scikit-learn. This process trains an XGBoost model to select important features by a pre-set threshold, then calculates a relative feature score (F- Score) for those selected features and set up a directional constrain to achieve an applicable data mining program for the causality analysis of traffic crashes which proposes a multi-dimensional interaction Apriori algorithm. This algorithm in this study recognizes the associated features, selects the highly frequent features, outputs association roles with relatively high confidence and lift. Moreover, this study evaluates the proposed SFM function and XGBApriori algorithm, the accuracy of the SFM function is 78.31% and the XGB-Apriori can increase 91% accuracy of the traditional algorithm, which indicates that the proposed algorithm and system can accurately predict the correlations among the causes and features leading to the severity of traffic accidents of older pedestrians. This study provides insights on the influence of the demographic features of driver and pedestrian, the features of vehicle and road structure on the severity of older pedestrian crashes; among them (1) more fatal crashes happen with male drivers compared with female drivers; (2) SUV, pickup truck and utility vehicles involved in more fatal pedestrian crashes than passenger cars; (3) and when the older pedestrian crash happens on the grade curve road, it is more likely to be a fatal crash. This paper proposes an accurate prognostic method for the comprehensive identification of the coupling factors of older pedestrian crashes and the implementation of targeted risk prevention and control, providing the necessary theoretical support for the effective protection of vulnerable groups on the road. References | Related Articles | Metrics

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Analysis of Children Behavior in Unidirectional Collective Movement XUE Shu-qi , LIU Yu-han, CHEN Qing-hua 2022, 22(1): 209-216.  DOI: 10.16097/j.cnki.1009-6744.2022.01.022 Abstract ( )   PDF (2179KB) ( )   Most of the existing researches and norms on pedestrian flow are based on the adult populations. There are relatively few researches on the theories and empirical results relevant to children pedestrians. As a result, it is necessary to refer to those adult related theories and empirical data for children related collective movement management and walking facilities design. In this study, unidirectional children collective movement experiments were conducted under different scenarios, namely, normal situation and emergency. With the experimental data, several basic characteristics of children unidirectional flow were investigated, such as the density- flow(speed) relationships, scatter of speed, and individual overtaking behavior. The experimental results reveal that the flow (speed)-density relationships of children unidirectional flow are scattered, and the coefficient of variation of speed of children is close to 4 to 6 times of the speed variation in adult experiments. In addition, compared with the orderliness of adult experiments, children are inclined to overtake others during the experiments and the strength of the change of ranking for children is close to 3 times that of adult experiment. It is expected that the datasets and findings from this research could help to increase the understandings of children behaviors in unidirectional collective movement and their differences with the adult populations, then help to guide the collective movement management of children and to provide valuable resources for the design and evaluation of children related walking facilities. References | Related Articles | Metrics

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Recognition Model of Distracted Drivers When Approaching Signalized Intersections ZHANG Yu-ting , CHEN Bo-you , ZHANG Shuang-yan, YAN Xue-dong , LI Xiao-meng 2022, 22(1): 217-224.  DOI: 10.16097/j.cnki.1009-6744.2022.01.023 Abstract ( )   PDF (1776KB) ( )   To reduce the traffic accidents caused by distraction when approaching signalized intersections, this study developed a driver distraction detection model based on bi-directional long short-term memory (BILSTM) method. A series of experiment scenarios approaching intersections were performed using a high- driving simulator. The longitudinal and horizontal behaviors of 45 drivers were analyzed to determine the impacts of driver distractions on driving behaviors using the analysis of variance (ANOVA). The results indicate that the distracted driver needs longer braking response time, operates the braking in shorter time and exerts less pressure on the pedal. Meanwhile, the districted driver shows deteriorated stability when operating the steering wheel. Six indicators that have significant impacts on driving behavior were selected as the input to the distraction recognition model. The results show that the recognition accuracy of the model is 92.6% and the F1-scores is 88.7%. Compared with the long short-term memory (LSTM), support vector machines (SVM) and decision tree 5.0 distraction recognition models, the proposed model shows the best performance in terms of accuracy, recall, the F1-scores, the area under the curve (AUC) and the receiver operating characteristic (ROC) curve. The BILSTM model can effectively distinguish the distraction driving status when the driver approaching signalized intersections, which provides basis and guidance for the optimal design of the driver distraction warning assistance system at the intersection. References | Related Articles | Metrics

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Innovative Design of Transportation Organization for Left-turn Non-motor Vehicles at Continuous Flow Intersection SONG Lang , WANG Jian , YANG Bin-yu , AN Shi 2022, 22(1): 225-233.  DOI: 10.16097/j.cnki.1009-6744.2022.01.024 Abstract ( )   PDF (3553KB) ( )   In order to resolve the conflict between left-turn non-motor vehicles and straight- going motor vehicles at continuous flow intersections, an innovative design scheme is proposed for the left-turn non-motor vehicles crossing streets. Considering the conventional design and the two- step street crossing scheme, the three schemes were integrated into a unified optimization model. Taking the maximum vehicle throughput at the intersection as the optimization objective, a mixed-integer nonlinear programming optimization model was established, which was transformed into a nonlinear model. And the operational benefits of the three schemes were verified through VISSIM simulation. The result indicates the two-step street crossing scheme and the innovative design scheme can improve the traffic capacity of vehicles at intersections. The improvement can be more significant in high- flow scenarios, which reduce the vehicle delay by 55.58% and 57.18%, respectively. The conventional design is not suitable for the scene with the large straight-going motor flow, while the two-step street crossing scheme and the innovative design are not suitable for the scene with large left-turn motor vehicle flow. The increase of left-turn non-motor vehicle flow in the two- step street crossing scheme and the conventional design will lead to a rapid decline of the vehicle capacity. The innovative design is less affected by the left-turn non-motor vehicle flow and it has good applicability in various traffic scenarios. References | Related Articles | Metrics

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Analyzing Spatiotemporal Characteristics of Ridesourcing Emissions Based on Trajectory Data HAN Yin , LI Yuan-yuan , LI Wen-xiang , LIU Xiang-long , QI Hao , WAN Dong-qi 2022, 22(1): 234-242.  DOI: 10.16097/j.cnki.1009-6744.2022.01.025 Abstract ( )   PDF (2527KB) ( )   Ridesourcing has gradually become one of the most important transportation modes in cities. Because the travel characteristics of ridesourcing are significantly different from other transportation modes, the environmental impacts of ridesourcing are worthy of detailed study. To reveal the emission characteristics of ridesourcing, this paper collected the parameters of average speed and mileage of ridesourcing vehicles in each trajectory segment using the Global Positioning System (GPS) trajectory data of ridesourcing services in Chengdu. The vehicle emission model COPERT is applied to quantify the CO, HC, NOx, and CO2 emissions of ridesourcing in the study area. The spatial and temporal distribution characteristics are also analyzed for the emissions. The results show that the CO, NOx, HC and CO2 emissions of ridesourcing are respectively 151, 41.5, 8.93, 125497.6 kg, in the study area on November 18, 2016. The peak hours of the ridesourcing emissions occurred at 9:00-10:00 am, 2:00-3:00 pm, and 5:00-6:00 pm. Areas with high emissions of ridesourcing are mainly distributed near the Second Ring Elevated Road, the Second Ring Road, and Shudu Avenue, with even more emissions at the intersections of some sections. The regional average speed significantly affects the average emission factors of ridesourcing in the region. Therefore, the authorities can take measures such as traffic demand management and vehicles speed limit control to reduce traffic emissions in the central city for high emission periods and areas of online hailing. The study provides a scientific method for the environmental impact assessment of ridesourcing, and serves as a decision basis for the formulation of policies related to ridesourcing management in the city References | Related Articles | Metrics

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Traffic Network Equilibrium Analysis with Multi Modes Based on Motorcycle Prohibition Scheme XU Guang-ming, CHEN Yan-qin, HAN Chun-yang , ZHONG Lin-huan, SHI Si-jia , DENG Lian-bo 2022, 22(1): 243-255.  DOI: 10.16097/j.cnki.1009-6744.2022.01.026 Abstract ( )   PDF (2519KB) ( )   At present, some domestic cities have implemented a "motorcycle prohibition" scheme in some areas, and the different motorcycle prohibition scheme will have different impacts on the mode split and route choices in the transportation system. To quantify the user's multi-mode travel choice behavior under the motorcycle prohibition scheme, this paper considers the different travel characteristics of private cars, public transport and motorcycles, and develops a multi-mode equilibrium model based on the motorcycle prohibition scheme. First, a composite network with the three modes of mixed traffic is designed, and according to the different characteristics of the road sections capacity the congestion in the public transport, and the route selection, the travel cost functions are established for three modes in prohibited areas and non-prohibited areas. Then, the corresponding mathematical programming model is constructed based on the user equilibrium and Logit mode split. The model is solved by a path allocation algorithm based on successive averages, and the user travel efficiency and crash risk under the motorcycle prohibition scheme are analyzed quantitatively. The result shows that with the increase of prohibited areas, the number of motorcycle users transferred to private cars and public transportation gradually increased, the total travel cost of users has gradually increased, and the travel efficiency and crash risk cost have gradually decreased. The implementation of the motorcycle prohibition scheme on the key road sections can effectively reduce the total crash risk while has less impact on user's travel efficiency. References | Related Articles | Metrics

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Track Planning Model for Logistics Unmanned Aerial Vehicle in Urban Low-altitude Airspace ZHANG Hong-hai , ZHANG Lian-dong, LIU Hao, ZHONG Gang 2022, 22(1): 256-264.  DOI: 10.16097/j.cnki.1009-6744.2022.01.027 Abstract ( )   PDF (2649KB) ( )   To improve the delivery safety and public acceptance of logistics unmanned aerial vehicle (UAV) in urban low-altitude airspace, and ensure the transportation economy, this paper proposed a track planning method for logistics UAV in urban low-altitude and considered the operational risk, noise level and transportation cost. The airspace was characterized by the grid method, and a risk-based urban airspace model was developed. A multi-objective and multiconstraint model of logistics UAV track planning was established combined with the requirements of logistics distribution. The improved A* algorithm was used to solve the problem. The evaluation function was designed to estimate the costs. The safety protection area was introduced to ensure separation and flight safety. To improve the search efficiency, a dynamic step length method was adopted to speed up the search process. The simulation results show that the proposed model and algorithm can achieve multi-objective optimization with low operational risk, low noise level, and low transportation cost. By analyzing the model parameters, when the cost weights of each sub-target are respectively 0.6、0.1 and 0.3, the planned flight track is optimal. If the remaining parameters remain unchanged and the safety separation is improved, the risk cost and transportation cost would generally increase, and the noise cost would decrease. In the planning environment of this paper, with reference to the parameters of DJI Matrice200, the comprehensive cost is minimum when the safety separation is set at 15 meters. References | Related Articles | Metrics

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Evolutionary Game and its Stability for Joint Distribution Alliance of Rural Logistics ZHOU Xiao-xiang, HUANG Cheng-feng 2022, 22(1): 265-272.  DOI: 10.16097/j.cnki.1009-6744.2022.01.028 Abstract ( )   PDF (2048KB) ( )   Under the decentralized and insufficient demand in rural logistics, an evolutionary game of a joint distribution alliance for rural logistics under self-organized was constructed, and a system dynamics simulation model was built to simulate how the different factors affect the stability of the alliance. The result shows that the operation of a rural logistics joint distribution alliance is influenced by many factors such as excess profit, default fine, reputation loss, construction, and operation cost. The excess profits of the alliance are the key factor of the foundation for the alliance, the cost-sharing mechanism and the interest's distribution mechanism of the alliance will be directly related to the enterprises' decisions, the maintenance cost of the alliance is an important factor for the logistics enterprises to deviate from the alliance, while the penalty and reputation loss have very good incentive restraint effect for the alliance. Preferential fiscal and tax support and reasonable alliance incentive and restraint mechanism are effective measures to promote the rapid development and stable operation of rural joint distribution alliance. References | Related Articles | Metrics

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Joint Optimization of Vessel Scheduling and Refueling for Container Liner Shipping in Emission Control Areas LI De-chang, YANG Hua-long , ZHAO Shuai-qi, ZHENG Jian-feng 2022, 22(1): 273-281.  DOI: 10.16097/j.cnki.1009-6744.2022.01.029 Abstract ( )   PDF (2117KB) ( )   This paper investigates the vessel scheduling and refueling for container liner shipping in emission control areas. The relationship between the terms of cooperation agreements was analyzed including multiple time windows, multiple start/end times, multiple loading/unloading rates, and the time of vessel sailing, loading/unloading, and arrival/ departure. In accordance with the factors of fuel price differentiation and its discount at different ports, the vessel scheduling and refueling problem with emission control was formulated as a mixed integer non-linear programming model, which has the goal of minimum total weekly route service cost of liner shipping. The linear secant approximation was also designed to solve the model. Taking the AWE1 route served by China COSCO Shipping Corporation Limited as an example, the paper verified the applicability and effectiveness of the model and the solution method by numerical experiments. The results show that the joint optimization of vessel scheduling and refueling of liner shipping would reduce the total weekly route service cost by 7.41%. The total weekly route service cost and the average vessel sailing speed in emission control areas would decrease with the increase of the length of vessel arrival time window. The result indicates that the terms of cooperation agreement would not only help shipping companies to adjust vessel sailing speed and schedule with more flexibility, but also help reducing vessels’greenhouse gas emissions in emission control areas. References | Related Articles | Metrics

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Recognition of Abnormal Driving Behavior of Key Commercial Vehicles ZHAO Jian-dong , CHEN Qin , JIAO Yan-li , ZHANG Kai-li , HAN Ming-min 2022, 22(1): 282-291.  DOI: 10.16097/j.cnki.1009-6744.2022.01.030 Abstract ( )   PDF (2465KB) ( )   To strengthen the supervision and detection of key commercial vehicles' abnormal driving behaviors, we proposed a combined model for recognizing abnormal driving behavior of key commercial vehicles based on a time series symbolization algorithm (TSA) and a multi- scale convolutional neural network model (MCNN). Firstly, we pre- processed the Beidou data. The commercial vehicles have the characteristics of multiple models, different speed limits, and various abnormal driving behaviors, which can be used to define four abnormal driving behaviors. And a sample data set was constructed. Secondly, we constructed a TSA-MCNN model to identify the sample data set. The process can be divided into two stages. In the first stage, we introduced a time series symbolic algorithm that can coarsely process data features and a multi- scale convolutional neural network that is capable of multi- channel parameter input to build the TSA-MCNN model based on the Keras library. In the second stage, we used the sample data set as the input variable to complete the training, testing, and identification of the model. Finally, we verified the performance of the TSA- MCNN model by key commercial vehicles' BeiDou data of Guanghe Expressway and compared it with the traditional convolutional neural network (CNN) model and the DTW- KNN model. The results show that the recognition accuracy of the TSA-MCNN is 97.25%, which is 20.50% and 5.63% higher than that of the CNN model and DTW- KNN model. And the recognition accuracy of the TSA- MCNN model for different behaviors including normal driving, speeding driving, emergency stopping, temporary stopping, and low-speed driving is 26%, 26%, 23%, 28%, and 0 higher than the CNN model, and 13%, 6%, 5%, 3%, and 0 higher than the DTW-KNN model. In conclusion, the proposed model has good performance for the recognition of abnormal driving behavior of key commercial vehicles. References | Related Articles | Metrics

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Predicting Remaining Useful Life of Electric Vehicle Battery Based on Real Vehicle Data HU Jie, HE Chen, ZHU Xue-ling, YANG Guang-yu 2022, 22(1): 292-300.  DOI: 10.16097/j.cnki.1009-6744.2022.01.031 Abstract ( )   PDF (2336KB) ( )   Predicting the battery remaining useful life (RUL) of electric vehicle (EV) is a hot topic in the field of battery research. Most of the existing RUL prediction models are based on a single prediction index, with low prediction accuracy and poor generalization. In this paper, a Stacking model of Gray Prediction model and Long-term Memory Neural Network model was developed to predict the RUL of electric vehicle with high accuracy based on real vehicle operating data. First, the movement and environmental parameters of the vehicle were extracted according to the influencing factors of the RUL of the battery, and the optimal features was selected as the model input based on the Random Forest Algorithm. Then, the study used the Auto Regressive Integrated Moving Average model to extend the selected features to overcome the limitation of time dimension. Based on the data characteristics, the Gray Prediction model and Long-term Memory Neural Network model were proposed to predict the battery RUL, and the prediction error was further reduced by the Stacking model fusion. The results show that the average relative error of the fusion model is 1.6%, and the average absolute error is 0.013, which proves a stable and reliable prediction of the RUL with the proposed model. References | Related Articles | Metrics

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On Driving Load of Super-long Tunnel Adjacent to Interchanges BAI Jing-rong , TANG Bo-ming, SUN Zong-yuan , BI Hui-yun , XIANG Tian-jun 2022, 22(1): 301-310.  DOI: 10.16097/j.cnki.1009-6744.2022.01.032 Abstract ( )   PDF (2915KB) ( )   To analyze the operation characteristics and driving behaviors of the super-long tunnel adjacent to interchanges, this study carried out the real vehicle test with 10 drivers operating in the Erlangshan Tunnel of the Yakang Expressway in China. The data of vehicle position, time, driving speed, and driver's pupil diameter and concentration were selected using Tobii eye tracker, Mobileye forward collision warning system, and Cirelet singleguide EEG system under real traffic conditions. The feature zones of the super-long tunnels adjacent to interchanges are divided. Given the distribution characteristics and variation curves of the driving speed and pupil diameter in front of the entrance of the Erlang Mountain Tunnel and adjacent interchange diversion points, a linear model of pupil diameter in the entrance and exit area of Erlangshan Tunnel was established, and the concentration level of the landscape belt in the tunnel was evaluated. The driving behavior changes from the directional lane change influence point to the interchange diversion point were analyzed. The results show that the landscape belt in the cave can relieve the driver's visual fatigue, and the effect of the national flag area of the scenery belt is better than that of the starry sky area. When the driver sees the white dashed line of directional lane change marking, the pupil diameter gradually decreases to 3.65 mm, and the driving speed is maintained at 71~73 km·h-1 . During the lane change operation period, the visual load and psychological tension are the highest, and the concentration is the highest in the conditional observation period. The driver needs to give rapid feedback and conduct lane change or not according to the acceptance gap. References | Related Articles | Metrics

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Invulnerability Simulation Analysis of Chinese Iron Ore Imports Shipping Network SHAO Fei , ZHANG Yong-feng , ZHEN Hong 2022, 22(1): 311-321.  DOI: 10.16097/j.cnki.1009-6744.2022.01.033 Abstract ( )   PDF (3194KB) ( )   PDF(English version) (616KB) ( 174 )   To assess the resistance of the shipping network of Chinese iron ore imports and the effectiveness of different safeguards, an invulnerability simulation model was established to fill the gap that traditional evaluation methods fail to consider the overall flow and nodes load state of the network. The data of a state-owned enterprise, major export ports in the world and major import ports in China were used to build the initial network. The network with different numbers of import ports was attacked in particular ways. The simulation results show that the network has a certain self- healing ability after the network is attacked, because of the adjusted ability of ship routes and redistribution of cargo load, but the network invulnerability will suddenly change after the key nodes are affected. The improvement of overload capacity has obvious marginal changes in improving network invulnerability if the overload capacity reaches a critical point, and improving the network survivability may aggravate network congestion. Therefore, it is necessary to strengthen the protection of key nodes, increase the number of import ports, and enhance the overload capacity of the ports, to enhance the invulnerability of the Chinese iron ore import shipping network under the COVID-19 and other critical events. Meanwhile, resources such as wharf yards and equipment should be reasonably allocated to prevent and deal with network congestion. References | Related Articles | Metrics

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Shipping Network Design for Waterbuses of Domestic and Foreign Trade in Yangtze River Economic Belt PENG Zi-xuan , YU Bin 2022, 22(1): 322-331.  DOI: 10.16097/j.cnki.1009-6744.2022.01.034 Abstract ( )   PDF (2506KB) ( )   This paper optimizes the waterbus network in the Yangtze River Economic Belt with waterbuses engaging in domestic and foreign trade. The model of a hub-and-spoke network for waterbuses is developed to minimize the total transportation cost. The constraints include service frequency, multiple voyages, time window, and deadweight capacity. An adaptive large neighborhood algorithm including 5 removal operators and 2 inserting operators is proposed to solve the model. The domestic and foreign trade container transportation between Shanghai and the 19 ports of the Yangtze River of China are selected for empirical analysis. The results show that 23.6% of total transportation costs can be saved if waterbuses could engage in both domestic and foreign trade. Meanwhile, the average utilization of the waterbus capacity would increase to 87%. Waterbuses engaging in domestic and foreign trade increases the direct routes by 17%, which affects the network structure and turn round time. Establishing Nanjing Port and Taicang Port as hub ports in the downstream of Yangtze River Economic Belt would help to transfer domestic and foreign trade containers in the upstream and midstream of the region and save the total transportation costs by 6%~17% compared to only using one hub port. References | Related Articles | Metrics

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Spatiotemporal Travel Patterns and Demand Prediction of Shared Bikes in Beijing SUN Qi-peng, ZENG Kai-bang, ZHANG Kai-qi, YANG Yi-chen, ZHANG Shi-hang 2022, 22(1): 332-338.  DOI: 10.16097/j.cnki.1009-6744.2022.01.035 Abstract ( )   PDF (1854KB) ( )   Using the Mobike data on workdays in Beijing, this study explores the patterns of bike- sharing behavior through the non-negative matrix factorization(NMF) algorithm from the spatial and temporal dimensions. A reverse population stability index was proposed to improve the selection of the k- value. Then, based on the revealed travel patterns information, the BP neural network prediction model with a non- negative matrix factorization (NMF) algorithm was built by MATLAB to predict the travel demand of shared bikes. The prediction results were compared with other two prediction models, i.e., the BP neural network model without NMF and the long and short term memory (LSTM) neural network model. Results show that the share of bicycle travel can be divided into five basic travel patterns, and the travel demand in each area can be represented by a linear combination of these five travel patterns. The coefficients represent the intensity and temporal fluctuation of each travel pattern. Based on the spatial and temporal characteristics, the five travel patterns can be regarded as cycling from residences to subway stations in commuting travel, cycling from subway stations to workplaces in commuting travel, non- commuting travel such as shopping or recreational travel, cycling from workplaces to subway stations in commuting travel and cycling fromsubway stations to residences in commuting travel. The results also show that the NMF-based BP neural network model proposed in this study is superior to the other two prediction models in both prediction accuracy and practical operational convenience. References | Related Articles | Metrics