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Review of Service Network Design for Express Freight Transportation ZHANG Yu-zhao 2021, 21(3): 1-12.  Abstract ( )   PDF (1418KB) ( )   Service network design is an important content of express freight operation management, and as well as a key scientific problem in the field of transportation. In this paper, the connotation of service network design for express freight is analyzed firstly, and then, the state of the art is discussed in detail from research content, optimization models, and solution algorithms. In terms of research content, different transport modes and multimode transport are classified and summarized, the service network design of express freight covers path planning, flow distribution, and scheduling optimization under either a single transport mode environment or integrated transportation system. Meanwhile, the connotation and extension of the research contents are constantly expanding. In the aspect of model construction, there are node-arc formulation and path formulation, and the space-time network has been widely used in dynamic service network model design in recent years. The considered modeling background is mainly based on deterministic conditions, while most models under uncertain conditions only consider the uncertainty of demand, and do not reveal the influence mechanism of various uncertain parameters on network structure and flow distribution. The factors considered include the total demand volume, service cost, service frequency in the initial stage, and gradually increasing capacity constraints, time impact, equipment utilization, et al. Heuristic algorithm is the main solution method, and there are many methods based on intelligent algorithms. With the improvement of computer operation efficiency and the powerful function of commercial software, the proportion of algorithms based on column generation and model relaxation or decomposition is on the rise in recent years. Finally, combined with the changes of internal and external conditions of express freight, the further research direction of express freight service network design in the aspects of considering uncertain conditions, low-carbon factors, and evolution mechanism is discussed. References | Related Articles | Metrics

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Development of a New Town Planning Method Using an Integrated Land Use-transport Model ZHONG Ming, DONG Yi-, HUNT John-douglas, SUN Jiang-tao, MA Xiao-feng, LIU Shao-bo, WU Ning-ning 2021, 21(3): 13-25.  Abstract ( )   PDF (2992KB) ( )   With the massive development of new towns in China, a large number of new towns have been planned with traditional planning methods, which usually plan“old town”and“new town”independently and lack the considerations of integrating land-use and transportation systems, and have resulted in many issues within the two (such as traffic congestion at“old town”and“new town”corridors and“ghost town”). Therefore, based on the strong interaction between the land use and transportation system of the“old town”and the“new town”, this paper proposes an integrated land-use transport modeling method for closing the gap within the existing new town planning process. By developing a macroeconomic forecasting module, Activity allocation (AA) module, and Space Development (SD) module independently for the two counterparts, the activity totals and its allocation, required land/space supply are predicted and simulated for the old town and the new town area separately, whereas the transportation demand of the two is simultaneously modeled. Such a method has achieved a more objective simulation of the path- dependent characteristics of the new town development process, while taking into account the socio-economic development target and land space constraints in the development of the new town and the old town. This paper takes the Yangtze River New Town (YRNT) of the City of Wuhan as the case study and an integrated land use transport model for the entire City of Wuhan (including both new and old town) is developed and applied to the case study. The coordination of the land use and transport system of the new town is also numerically accessed from the year 2015 to 2035. Study results clearly show that the proposed modeling method is feasible and practical. References | Related Articles | Metrics

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Structural Evolution of China's Air Transport Network Across 2000—2018 CAO Wei-wei,LI Zheng, FENG Xiang-nan 2021, 21(3): 26-33.  Abstract ( )   PDF (2150KB) ( )   Air transport network plays an important role in connecting regions and facilitating the development of the social economy. China has the second- biggest aviation transport scale in the world, which brings time- space compression and accelerates socio-economic development steadily. By utilizing social network methods, this paper investigates the structural characteristics and evolution of China's air transport network (CATN) from 2000 to 2018 based on the flight schedule data. Firstly, CATN presents an allometric growth pattern. Network density decreases firstly and then increases, while flight density presents an inverse pattern. CANT has been characterized by small-world properties. The characteristic path length is reduced from 2.115 to 1.965, indicating an enhancement of accessibility, while the clustering coefficient shows an inverse“U”change pattern. Secondly, both the average degree and closeness of cities increase, implying an improvement of connectivity and global accessibility. Degree and closeness have the biggest correlation among different centrality measures, but the correlation coefficient has no obvious fluctuation over time. Furthermore, the correlation coefficient between betweenness and degree and the correlation coefficient between betweenness and closeness both tend to increase. Finally, the spatial distributions of flights are extremely uneven and heterogeneous. Flights between cities in the eastern region have the highest proportion, but it shows a downward trend. The eastern region has the highest proportion of inter-city flight connections but presents a descending trend. Meanwhile, the proportions of flights between cities in the east- central and east- western regions are increased. The development center of CATN is shifting westward. References | Related Articles | Metrics

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Port Supply Chain Integration under Node Disruption and Demand Uncertainty ZHAO Xu, ZHANG Hui-yan, HUANG Rui 2021, 21(3): 34-39.  Abstract ( )   PDF (1369KB) ( )   To identify the impact of uncertain risk on the integration of logistics resources, this paper develops a bilevel programming model from the perspective of the entire port supply chain which considers the logistics service requester, logistics service provider and port enterprises. The upper model optimizes the integration strategy of multiple ports on the chain to the upstream and downstream enterprises under the given confidence level of the decision maker and the risk of node interruption and demand uncertainty. The lower model optimizes the integration strategy from the port supply chain enterprise nodes and aims to minimize the total cost of transportation and achieve an equilibrium flow of goods. The hybrid genetic algorithm is designed to solve the model. The study results show that, in the risk situations, the logistics service provider would have more benefits if they participate in the port integration than not participate. The different confidence levels of the decision makers on the two risk situations would affect the integration strategies of each port on the chain, and the risk of node interruption has more impact on the benefit of the port supply chain. References | Related Articles | Metrics

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A Study on Cooperative Game of Metro and Bus Lines ZHOU Yu-yang, LIU Guo-peng, CHEN Yan-yan, YAN Hui-ya 2021, 21(3): 40-46.  Abstract ( )   PDF (1382KB) ( )   To maintain the cooperative transportation alliance between subway and bus lines, it is necessary to fairly distribute the profits generated from the cooperation. This paper proposes a cooperative profit allocation model based on the cooperative game theory. The cooperative transportation mode is divided into the intermodal transportation and the shared transportation based on the topological relationships between lines. And the profit distribution models are established respectively. For the intermodal transportation, considering the connection sequence of different routes on the travel path, the contribution parameter is introduced into the profit function to redistribute the cooperation benefits on the path. Based on Shapley's value, a correction factor is introduced to redistribute the profit generated in the Shared Transportation. The correction factor is influenced by the operators' contribution, cost, and risk in cooperation. Finally, the model is applied to a specific case through the allocation step of first Intermodal Transportation and then Shared Transportation. The results show that the model can allocate the profit of cooperation fairly and rationality, maintain the cooperative transportation alliance between metro and bus lines. References | Related Articles | Metrics

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Vehicle Trajectory Reconstruction and Anomaly Detection Using Deep Learning HUANG Shi-chen, SHAO Chun-fu, LI Juan, ZHANG Xiao-yu, QIAN Jian-pei 2021, 21(3): 47-54.  Abstract ( )   PDF (1815KB) ( )   The uncertainty and the existence of outliers of vehicle trajectory data makes it challenging to be used in the digital transportation systems. In this paper, we propose the LSTM-AE-Attention deep learning model for vehicle trajectory reconstruction and anomalous trajectory detection. To realize the data augmentation, the trajectory dataset is expanded in the sample size and sample type using the Generative Adversarial Networks and the Bezier Curve. The trajectory features are extracted by the Autoencoder and the Long Short-term Memory networks, and the trajectory reconstruction is completed. An anomaly detection model is then developed using the AE Pre-training and the Attention networks. The experiment has been performed based on a practical trajectory dataset. The results show that the proposed model produces several evaluation indicators that are better than the Support Vector Machines, Random Forest and Long Short-term Memory networks results. In the trajectory reconstruction section, the decision coefficient of the model is 0.968. In the anomaly detection part, the F1 score is 9.8% higher than the average score of the other models. The LSTM- AE- Attention model is an effective method for smoothing the vehicle trajectory and correcting abnormal trajectory. References | Related Articles | Metrics

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Signal Coordination Timing and Delay Model for Continuous Flow Intersection SONG Lang, ZHU Yong, WANG Shao-fei, SHEN Jian-bo 2021, 21(3): 55-63.  Abstract ( )   PDF (2309KB) ( )   To reduce the stopping of vehicles at continuous flow intersection and the conflicts between pedestrians and vehicles, and to prevent vehicle queue overflow from destroying the stable operation state of continuous flow intersection, a coordinated optimal control strategy of pedestrians and vehicles signal is proposed. According to the characteristics of traffic flow, the main pre-signal timing is coordinated, the signal phase scheme is optimized, the delay calculation model is established, and the optimization model is constructed to minimize the average vehicle delay. The simulation results show that the delay estimation error of the delay calculation model is less than 5%. Through the case analysis, the average vehicle delay and vehicle stopping in the current scheme are more than 2 times longer than the optimization scheme, which shows that the optimization scheme avoids the secondary stops of vehicles. From the perspective of the whole intersection, the average vehicle delay of the optimization scheme in the two traffic scenarios is reduced by 27.8% and 18.5%, respectively, which improves the operational efficiency of the intersection. Through sensitivity analysis, it is found that the comprehensive benefit is the best when the length of the shifted left turn lane is 100 m. References | Related Articles | Metrics

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Priority of Dedicated Bus Arterial Control Based on Deep Reinforcement Learning SHANG Chun-lin, LIU Xiao-ming,TIAN Yu-lin, DONG Lu-xi 2021, 21(3): 64-70.  Abstract ( )   PDF (2293KB) ( )   Due to the differences in operating characteristics of the social vehicles and dedicated buses and the poor performance of the coordination control, this paper proposes a comprehensive arterial line coordination control method that integrates social vehicle arterial coordination control and public transportation arterial priority control. With the analysis of the dedicated bus non-stop probability of the upstream and downstream, the associated state spaces and the corresponding action decisions were determinded by analysing the difference in the travel time distribution of the social vehicle and dedicated bus. We combined with the influence of signal adjustment strategy on vehicle delay loss and bus priority gains to determine the reward and punishment mechanism. And a deep reinforcement learning framework is proposed to solve the best signal adjustment strategy in real time. Finally, the simulation experiment indicates that the proposed method can reduce the per-capita delay by 38.63% and 27.43%, and the stop times of bus at intersections can decreased by 52.17% compared with the social vehicle arterial coordination, which proves that the method can effectively increase the efficiency of buses and social vehicles. References | Related Articles | Metrics

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Intersection Signal Timing Optimization Model Considering Pedestrian Protection Strategies YANG Zhen,MA Jian-xiao,WANG Bao-jie,LI Gen 2021, 21(3): 71-77.  Abstract ( )   PDF (2112KB) ( )   To promote pedestrians' safety at intersections, this paper establishes a signal timing optimization model based on the NEMA dual-ring standard by incorporating three pedestrian protection strategies, i.e., exclusive pedestrian phase (EPP), concurrent yet protected phase (CYPP), and leading pedestrian interval (LPI). The model aims at minimizing the cycle length and the conflicts between right-turn vehicles and pedestrians. By supposing that the traffic users obey the signal rule, the model can eliminate most of the conflicts, leaving only the conflicts between far- side pedestrians and right-turn vehicles under LPI control. The model belongs to Binary-Mix- Integer- Linear- Program (BMILP) and can be solved by the branch-and-bound method. Two intersections in the city of Nanjing are selected for a case study. The results show that when the intersection size is small and the traffic volume is low, the EPP is more likely to be obtained; the CYPP or LPI is otherwise. When the shared through-right lane is set in the intersection arm or the right-turn phase is not easy to meet the maximum volume-to-capacity ratio, LPI is more likely to be obtained. References | Related Articles | Metrics

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Rail Transit Trip Sharing Rate Model Combining Mobile Phone Signaling Data LIU Hai-zhou, WANG Li-lei, ZHOU Jian-yao,LIU Yi,YANG Fei 2021, 21(3): 78-85.  Abstract ( )   PDF (2008KB) ( )   The transportation behavior model is widely used in urban travel demand analysis and other fields. The traditional behavior model's parameter setting is usually dependent on empirical judgment, with large sample data verification lacking. This paper's research object is the travelers' corridor travel choice behavior between the Jie Fangbei and Guanyin Bridge group in Chongqing. The mixed Logit model with different random parameters is constructed based on the mobile phone signaling data, AFC data, and questionnaire survey data. Meanwhile, the random parameters include normal distribution, uniform distribution, and γ distribution. Then the analysis of cellular data and AFC data are used as benchmark data to optimize the mixed Logit model. The one-day inter-group railway travel sharing rate identified by big data is 37.13%. And the mixed Logit model accuracy reaches the highest (39.5%) when the mixed Logit random parameter is a normal distribution. The result shows that it is practical to use extensive data analysis to verify traditional behavior models' accuracy, quantify and optimize the best parameter distribution. This paper provides ideas for improving the prediction accuracy of the traditional behavior model. References | Related Articles | Metrics

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Passengers' Hot Spots Identification of Online Car-hailing Based on Network Kernel Density LONG Xue-qin, ZHOU Meng, ZHAO Huan, ZHANG Xue-yu 2021, 21(3): 86-93.  Abstract ( )   PDF (4059KB) ( )   In order to analyze temporal and spatial distribution characteristics of online car-hailing hot spots, data of trip orders is used to build a hot- spot identification model based on network kernel density estimation, in which a regression model is used to cluster and classify the hot spots. Through the delineation of the research area, data cleaning, and screening, the network kernel density estimation method measured by road network distance is introduced. Based on the heterogeneous network direction extension and network distance attenuation effect, the kernel density of pick-up and drop-off points at specific periods during working days and weekends are estimated. The zeroexpansion negative binomial regression model is used for kernel density clustering, and the distribution of hot road sections is identified and classified. By comparing with the results of kernel density estimation, the network kernel density estimation method reflects the distribution characteristics of passenger hot-spots on road sections and intersections, and characterizes the relationship between actual traffic demand and road network structure. The conclusions help to optimize the operation and management of online car-hailing and improve the travel efficiency of urban residents. References | Related Articles | Metrics

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Closed-loop Feedback Speed Guidance Method Considering Driving Style LI Hao-ran,CHU Duan-feng,LIANG Dong-cai,ZHOU Tu-qiang 2021, 21(3): 94-100.  Abstract ( )   PDF (1545KB) ( )   At signalized intersections, unreasonable speed control may increase the vehicle fuel consumption and may even cause a rear-end collision. Speed guidance systems can improve the efficiency of vehicle speed control. However, drivers cannot accurately follow the speed guidance during driving. This study proposes a closed-loop feedback vehicle speed guidance system by considering the driving styles of drivers. Firstly, the probability distribution of vehicle maximum acceleration with different driving styles is analyzed. The closed-loop feedback approachis then proposed for drivers to follow thespeed guidance more accurately. A chance constraint model is further developed to consider different driving styles. Finally, a simulation is conducted in MATLAB/Simulink to validate the proposed speed guidance models. The simulation results show that the model with different driving styles in this study is more effective and reliable compared with the traditional model. The aggressive and moderate speed guidance models can make vehicles get through signalized intersections efficiently, and the cautious speed guidance model can increase the probability of getting through signalized intersections in green light phases. This speed guidance model can improve the traffic efficiency at signalized intersections. References | Related Articles | Metrics

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Highway Traffic Flow Prediction Model with Multi-features LI Tao-ying,WANG Ting, ZHANG Yu-qi 2021, 21(3): 101-111.  Abstract ( )   PDF (2997KB) ( )   In order to accurately predict highway traffic flow and thus alleviate traffic congestion of highway, a highway traffic flow prediction model with multi- features is proposed in this paper. Firstly, the traffic flow of the section with the upstream and downstream sections, and the weather data are transformed into a two-dimensional matrix, and the sliding window model is employed to obtain the optimal size of input samples. Then these samples are input into a hybrid depth deep learning model to extract the features of traffic flow data, and then output the prediction results. Finally, the traffic flow data of a real highway is used to do two experiments on weekdays and holidays. The results indicate that the hybrid deep learning models perform better results than single models for forecasting highway traffic flow. The prediction accuracy of highway traffic flow on weekdays is higher than that on holidays. The proposed model reduces the mean absolute error from 6.40 Cars · (20 min)- 1 to 5.450 Cars · (20 min)- 1 , which shows that the prediction accuracy of highway traffic flow can be improved by considering multiple related factors. References | Related Articles | Metrics

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Traffic Network Speed Prediction via Multi-periodic-component Spatial-temporal Neural Network YANG Jian-xi,YU Chao-shun,LI Ren, DU Li-fang,JIANG Shi-xin,WANG Di 2021, 21(3): 112-119.  Abstract ( )   PDF (2569KB) ( )   To overcome the drawbacks of current traffic network speed prediction methods, such as the lack of accuracy and stability for medium and long period prediction, as well as the low capability of self- adaptive traffic network topological modeling, this paper proposes a traffic network speed prediction approach via a novel multi- periodiccomponent spatial-temporal neural network which takes multi-scale convolutional operators and gated recurrent units as its building blocks. Firstly, according to the periodic characteristic of traffic network speed, the raw data is transformed into a three-dimensional matrix corresponded to the weekly period, daily period, and recent period before inputting to the period component of the proposed model. Secondly, the multi-scale convolutional kernels are used to capture the spatial correlation between the multi- factor nonlinear correlation and the traffic network nodes with a different spatial field of view in each period component. And then, the gated recurrent units are employed to extract the long-term dependency of traffic data. The residual learning framework is also utilized to improve the training efficiency and prevent gradient dispersion. Finally, the traffic speed prediction results related to each period component via the prediction convolutional unit are adaptively weighted and fused. In order to verify the effectiveness of the proposed model, two public datasets are used for experimental analysis, while the mainstream deep neural network models related to the task are compared. The experimental results show that the average absolute error, the average square error and the average absolute percentage error of the proposed model are 2.55, 3.94 and 10.75%, 1.57, 3.52 and 3.44%, respectively. The proposed model outperforms other baseline models in terms of prediction accuracy and long- term prediction stability. References | Related Articles | Metrics

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Safety Characteristics of Exit Section of Multi-lane Expressway LV Neng-chao, DU Zi-jun,WU Chao-zhong,WANG Yu-gang 2021, 21(3): 120-130.  Abstract ( )   PDF (2275KB) ( )   This paper investigated the relationship between traffic safety and the factors of exit opening length and traffic flow rate on the multi-lane expressway. Three different opening lengths were designed for two types of expressway exits and three different traffic flow conditions. 18 driving simulation scenarios were designed and the experiment was performed with 30 subjects for driving simulations. The driving behavior parameters that collected in the experiment included driving trajectory, deceleration, lane change gap, and other driving behaviors of the expressway exit. Then, a comprehensive evaluation of the driving risks was performed for different traffic sign design schemes. The results indicate that the exit opening length has a significant impact on the choice of lane changing points on the opening section under two cross- sectional scenarios. The opening length of 1500 meters would meet the lane changing needs of most drivers. The most common choice of lane changing gap ranging from 5 to 6 seconds. The length of the opening under the separated section has a significant impact on the frequency of the lane changing gap below the critical gap. The flow rate and opening length have no significant influence on the maximum deceleration, the minimum TTC and the distribution position, but the maximum deceleration rate and minimum TTC of the separated section are smaller than those of the monolithic section. In addition, the driving risk of the inner three lanes in the monolithic section is lower than the driving risk of the inner three lanes in the separated section; while the driving risk of the outer lane in the separated section is lower than that of the monolithic section. References | Related Articles | Metrics

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Risk Discrimination and Conflict Prediction of Vehicle-following Behavior in Multi-lane Weaving Sections XIE Ji-ming,QIN Ya-qin,PENG Bo,XIA Yu-lan,WANG Jin-rui 2021, 21(3): 131-139.  Abstract ( )   PDF (2557KB) ( )   Intelligent Vehicle Infrastructure Cooperative Systems(IVICS) is one of the emerging technologies to ensure travel security and efficiency. Combining high- precision vehicle trajectory data with machine learning method, a potential risk identification and conflict prediction method for multi-lane interweaving zones is proposed, which can be applied to IVICS. First, the information about the traffic vector position and speed in the interweaving area was extracted from the wide-area perspective based on UAV video. Several partitions were divided, such as the upstream and downstream sections, and the interweaving influence area. Then, the risk discrimination model was constructed by considering the decision behaviors (vehicle- vehicle edge distances, approach rates) and vehicle behaviors (the transverse and longitudinal velocity, acceleration, velocity angle). Risks were evaluated from the number of conflicts per unit area, duration of conflicts, conflict density and other indicators. Finally, traffic conflicts are predicted according to the Naive Bayes model and the Logistic regression model. Compared with the measured data, the prediction accuracy rates of the two models were 74.86% and 87.10% respectively, and the AUC were 0.84 and 0.88 respectively. It showed that the Logistic regression model has better prediction performance. The corresponding results are helpful for traffic management departments to formulate and optimize traffic control schemes and can be applied to IVICS dynamic early warning. References | Related Articles | Metrics

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Evolution of Metro Network Stability Based on Weighted Coupled Map Lattice HUANG Ai-ling, XU Xiao-han, GUAN Wei, DUAN Meng-yuan 2021, 21(3): 140-149.  Abstract ( )   PDF (2873KB) ( )   PDF(English version) (1298KB) ( 126 )   In order to explore the revolution of the metro network's resilience, this paper constructs a series of indexes for assessing the stability of metro flow-weighted network from the perspectives of network connectivity, selfadaptivity, and availability, and proposes a method of analyzing cascading failures based on coupled map lattice model with the consideration of the impact of OD flow distribution on the network. Taking two metro networks of Beijing in 2014 and 2018 as examples, this paper constructs the dynamic stability analysis model based on the P-space weighted complex network and carries out the simulation attacks with different interferences on three nodes with different importance in these two networks to compare the evolution of network's stability. The numerical results show that with the topological structure of the Beijing metro network evolved from a small-world to scale-free network, the stability and invulnerability of the network in 2018 were significantly improved compared with 2014. The greater the attack on the stop with the larger flow, the more the cascading failures, the higher the probability of network paralysis, and the faster the paralysis speed. The research results can provide scientific theoretical basis for optimizing the network structure and site location and strengthening the safe operation and management of metros. References | Related Articles | Metrics

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Urban Rail Transit Passenger Volume Control Station Identification Method Based on Exact Controllability XIAO Zhong-sheng,XU Qi,FENG Xu-jie,LI Jia-jie 2021, 21(3): 150-155.  Abstract ( )   PDF (1684KB) ( )   This paper extends the applications of the controllability theory in the field of urban rail passenger volume control. The relationship of incoming, outgoing and the cross-sectional passenger flow were analyzed and the urban rail transit network was proven to be a linear time-invariant system, which demonstrated the applicability of the complex network controllability on urban rail transit network. Based on the exact controllability framework and the subnet generation strategy the paper proposed the method to identify the stations to apply passenger volume control measures. The effectiveness of the proposed method was verified by drawing on relevant evaluation metrics in machine learning. The results show that the controllability is 0.043 in Beijing rail transit network during off-peak hours, which indicates the network is stable and the control scheme is unnecessary. During the peak periods, the control schemes recommended passenger volume control on central stations of the network from the generation to dissipation of the congestion. The control schemes generated by the proposed method can match the actual control scheme to the degree of 70%. When the number of control stations are the same for both schemes, the scheme generated by the proposed method recommended controlling the stations in the western and central part of the city References | Related Articles | Metrics

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Collaborative Optimization of Urban Rail Transit Operation and Passenger Flow Control at Stations Using Skip-stop Pattern Strategy MENG Fan-ting,YANG Li-xing, LU Ya-han,GUO Rong-ge 2021, 21(3): 156-162.  Abstract ( )   PDF (1571KB) ( )   To relieve severe traffic congestion and the over- saturation of rail transit system, this study integrates the service and demand from the perspective of system optimization, and considers the continuous arrival characteristics of passenger flow in the analysis. A collaborative optimization method is developed for the train operation schedule and passenger flow control at stations using the skip-stop pattern strategy. By introducing the train schedule and passenger flow control decision variables, a bi-objective integer nonlinear collaborative optimization model is formulated to improve the train operation efficiency and to reduce the number of delayed passengers. Then, the nonlinear constraints are linearized by time reconstruction and big-M method with 0-1 variables to solve the proposed model. The model is reconstructed into an integer linear programming model, which can be easily solved by the CPLEX solver. The numerical examples are executed to verify the effectiveness of the proposed model. The results show that compared to the single objective optimization method and only with the train service time，the proposed model significantly reduces the number of delayed passengers. Compared to only considering number of delayed passengers, the train running time is reduced by 2% to 3%. References | Related Articles | Metrics

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Maintenance Arrangement Optimization for Infrastructure Systems of Urban Rail Transit Considering Resource Constraints LIU Ge-hui, CHEN Shao-kuan, LIU Shuang, JIN Hua, WANG Dan-yang 2021, 21(3): 163-169.  Abstract ( )   PDF (2479KB) ( )   PDF(English version) (977KB) ( 70 )   Due to the complex system composition, various maintenance tasks, and limited maintenance resources of urban tail transit infrastructure systems, a long- term maintenance task arrangement method is proposed considering attributions of tasks and constraints from resources. An optimization model based on mixed-integer programming is established to minimize the total cost by arranging the start time and execution period of maintenance tasks with various types. The occupation penalty is imported to reduce the task conflicts and improve the maintenance arrangement. A parallel hybrid algorithm combining the commercial solver and a heuristic method is designed for solving the large-scale problem with complicated constraints. The case study verifies the importance of task occupation on improving the executability of the maintenance arrangement. The proposed method can save the total cost by coordinating various types of maintenance tasks and provide decision support for arranging long- term maintenance tasks on urban rail transit infrastructure systems. References | Related Articles | Metrics

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Collaborative Optimization on Electrical Resolver Location and Track Gradient Design of Railway XU Zhi-yong 2021, 21(3): 170-175.  Abstract ( )   PDF (1600KB) ( )   The position of the railway electrical resolver and the track gradient design are interacted. If the position of electrical resolver and track gradient are designed independently, the energy consumption of train movement and the travel time of users will be increased significantly, and even an unexpected train stop in the neutral zone occurs. To design the position of the railway electrical resolver and the track gradient scheme near the electrical resolver, this paper establishes a collaborative optimization model to minimize the sum of train energy cost, travel time cost, and construction cost, while the railway design specifications and train operation constraints are satisfied. An improved genetic algorithm based on an indirect coding method is developed to solve the proposed model. The case studies show that, in comparison with the actual design scheme of a high-speed railway line, the solution optimized by the proposed model can reduce the speed loss after the train passing through the electrical resolver as well as the energy consumption and time of the secondary traction. The optimized solution also saves the construction cost of the high-speed rail line and the overall saving of total cost reaches 9.2%. References | Related Articles | Metrics

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Scheduling Method for Integrated Plan of Train Operation and Shunting Operation in High-speed Railway Station ZHONG Ming-xuan, YUE Yi-xiang,ZHOU Lei-shan 2021, 21(3): 176-186.  Abstract ( )   PDF (3072KB) ( )   The quality of train operation plan for complex high-speed railway station is an important factor affecting the transportation efficiency of the high- speed railway network. To generate high- quality station operation plans in short time, this paper analyzes the train operation and shunting operation of all types of trains in the station, and establishes the train operation chain. Based on these, the essence of station operation planning optimization problem has been described, which can be taken as a resource optimization problem. Then, considering the station layout and track circuit distribution, the study proposes a microscopic optimization model to create station operation plans. In view of the large number of variables and the complex constraints in the problem, the model is transformed into dual form and then solved by the Lagrange relaxation algorithm without initial feasible solution. A branch and bound method based on symmetry breaking rule is used to make the solution of Lagrange relaxation problem feasible. The case study uses Beijing South Railway Station to test the proposed model and algorithm. The calculation time in the case study is within 20 minutes, the results are feasible and the dual gaps are less than 10%. The results show that this method can generate high-quality train operation plan for complex high-speed railway stations effectively and has good potentials for practical applications. References | Related Articles | Metrics

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Parking Pricing Method Based on Flexible Parking Incentive Mechanism and Risk Perception GAO Liang-peng,ZHENG Yue,JI Yan-jie,FU Cheng-hong 2021, 21(3): 187-192.  Abstract ( )   PDF (2041KB) ( )   This paper applies the flexible incentive parking mechanism to optimize the parking prices and uses the function of conditional value at risk to describe the risk perception characteristics of individual shared parking spaces. The study explores the influence of supply-demand relationship on the optimal rental prices of shared parking spaces, and takes the University of California, Berkeley as an example to analyze the positive and negative guiding effects of key parameters on the efficiency of shared parking policy. The results show that the parking pricing method based on the optimal risk perceived returning can find the appropriate "competitive" price in response to the difference of external parking demand constraints. The optimal pricing ensures the effective use of parking spaces, encourages the individual to actively participate in the shared parking process and avoids the impact of loss aversion on the implementation of flexible parking incentive mechanism. The optimized rental price of parking spaces would have some fluctuations when some parking spaces no longer open to the public. If the shared parking spaces decreased significantly, this method tends to increase the rental price to balance the cost and benefit. On the contrary, the method would suggest reducing some profits of parking spaces and setting a relatively lower rental price to maintain a good utilization efficiency of shared parking spaces. References | Related Articles | Metrics

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Optimal Parking Space Allocation Based on Combinatorial Auction and Uniform Price TAN Bing-qing,XU Su-xiu,XU Gang-yan,ZHOU Yao-ming 2021, 21(3): 193-199.  Abstract ( )   PDF (31486KB) ( )   This paper considers a parking service platform that provides two types of parking modes simultaneously: reservation mode and first-come- first-served mode. An optimal integer programming model is proposed to maximize the overall utility of bidders and the platform. The uniform price is introduced into a one-sided Vickrey-Clarke-Groves (O-VCG) combinatorial auction mechanism. The proposed novel O-VCG combinatorial auction mechanism helps to achieve the goals of incentive compatibility, individual rationality and allocative efficiency. The numerical study demonstrates the effects of the bid distribution and bidder quantity on the parking allocation strategy and the overall utility of the two modes. The results indicate that when the average value of bids is close to the uniform price of single parking time slot, the O-VCG combinatorial auction mechanism can realize the optimal allocation of the two types of parking modes and ensure the system robustness. References | Related Articles | Metrics

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Optimization Model of Electric Bus Fleet Replacement Considering Financial Subsidies MA Xiao-lei, YAN Hao-yang,MIAO Ran 2021, 21(3): 200-205.  Abstract ( )   PDF (1437KB) ( )   To solve the problem of bus fleet replacement and analyze the influence of financial subsidy policy on bus fleet electrification, this paper takes financial subsidy, greenhouse gas emission level, and other factors into consideration, and takes the minimum life cycle cost of bus fleet as the optimization objective, establishes a mixedinteger programming model of bus fleet replacement, and uses CPLEX software to solve the model to obtain the optimal solution. Taking Beijing No.19 bus fleet in 2017 as an example, the optimal vehicle purchase scheme, the charging pile purchase scheme, and the vehicle elimination scheme are obtained. The optimal scheme's life cycle cost is 212897000 yuan, and the greenhouse gas emission is 2488.4 tons of CO2 equivalent. Based on the sensitivity analysis of financial subsidies, the final proportion of electric bus, greenhouse gas emission level, and other parameters, the results show that: financial subsidies have a positive effect on the bus fleet electrification from the perspective of cost but delay the process of the bus fleet electrification; in the short term, the cost advantage of the hybrid bus is obvious, and in the long term, the electric bus has considerable emission reduction potential. References | Related Articles | Metrics

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Impacts of Accessibility to Transit Measures on Inequality Index of Public Transport YAO Zhi-gang，FU Yu-hao，ZHANG Jun-qing 2021, 21(3): 206-213.  Abstract ( )   PDF (2770KB) ( )   The buffer method of measuring bus stop accessibility is the basis to calculate inequity index of public transport. There are two commonly used ways to improve the buffer method: one is estimating the walking distance that passengers take to a bus stop using either a straight-line or passenger walking routes; the other way is estimating the population with a decay distribution around bus stop. The impact of the improvement of accessibility measures on the value of inequality index is still unclear. Using Haining City of Zhejiang Province as an example, this study compared Gini coefficient of linear buffer method with Gini coefficients of three improved accessibility measurements including the road network buffer method, linear decay method, and road network decay method. The Gini coefficient of linear buffer method decreases 13.60% when it is calculated with the improved walking distance estimation (Road network buffer method). The Gini coefficient decreases by 35.75% with the improved passenger distribution estimation (Straight-line decay method). The Gini coefficient decreases by 40.56% with the improved walking distance and passenger distribution estimations (Road network decay method). The improvements all lead to a reduction in the gap in accessibility values between Traffic Analysis Zones (TAZ)s, and the distribution of passengers is more effective than this improvement in the walking distance. The Gini coefficient in rural areas is affected more by the improved measurement than that in urban area, which might be related to different road network density and population distribution in urban and rural areas. Different inequality indices even conflicting conclusions of the equity of public transport between urban and rural areas can be obtained with different accessibility measures. The study shows that the simplified accessibility measure overestimates inequality index and has different impacts on urban and rural areas. The public transport Gini coefficient should be considered with the buffer method in the absent of road network and population data, and the network decay method is recommended when there are more available data. References | Related Articles | Metrics

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Examination of Driver Injury Severity in Urban Crashes: A Random Parameters Logit Model with Heterogeneity in Means Approach SONG Dong-dong,YANG Xiao-bao,ZU Xing-shui,SI Bing-feng 2021, 21(3): 214-220.  Abstract ( )   PDF (1298KB) ( )   Analyzing the factors that are closely related to the driver injury severity in the accident is of great significance to reduce casualties. However, most existing literatures assume that the significant parameters are fixed, which may lead to biased and inconsistent parameter estimates, even erroneous inferences. This paper examines the driver injury severity in urban crashes based on the random parameters Logit model with heterogeneity in means. Using the road crash data of Guiyang city from 2015 to 2019, this study investigates the potential impact factors in terms of drivers, vehicles, roads, and environment characteristics. The average marginal effect is used to quantify the impact of each significant variable on the severity of the crash. The results show that the random parameters Logit model with heterogeneity in means has superior statistical performance. There are some factors that increase the driver's injury severity, for example, women driver, elderly driver, drunk driving, vehicles without airbags, visibility below 50 meters, and no streetlights at night. In the Logit model, streetlights at night and crashes at night are random variables. The streetlights at night variable is co- related with the flexible guardrail and the absence of airbags. Crashes occurring at night variable is co-related with the road segment with roadside trees. References | Related Articles | Metrics

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Commuting Mode Choice Behavior Incorporating Decision-making Process and Latent Heterogeneity ZHANG Yi-yuan, LI Jin-long, LUO Xia,ZHOU Yi-bing 2021, 21(3): 221-228.  Abstract ( )   PDF (1918KB) ( )   Traditional methods pay little attention to the dynamics of the decision- making process and the micropsychological preferences of residents. This paper applies a latent class model to represent the potential heterogeneity in the commuting decision-making process. Then, from the perspective of dynamic decision-making, the decision field theory model is constructed, which can reflect the dynamic evolution of preference. The model sets different attribute attention weights for different subgroups, which can represent the heterogeneities of users' dynamic preferences in different subgroups and the similar but different characteristics in the same subgroup. Meanwhile, it can simultaneously implement user classification, analyze the decision-making process and improve the deficiency of traditional decision field theory in characterizing individual preference heterogeneity, based on which an empirical study of residents near rail transit stations in Chengdu is conducted. The results show that the residents can be subdivided into four types: business demand subgroup, efficiency demand subgroup, economy- preference subgroup, and conservative subgroup. There exist significant differences between subgroups in the initial preference and attention weights for attributes. The simulation realizes the prediction of decision-making results, the demonstration of the evolution process of individual micro- preferences, and the irrational effect in the process of attribute change, thus verifying the effectiveness of the proposed model. References | Related Articles | Metrics

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Operational Factors Analysis for Taxi Speeders Using Mixed Logit Model ZHOU Yue,JIANG Xin-guo, FU Chuan-yun, LIU Hai-yue 2021, 21(3): 229-236.  Abstract ( )   PDF (2052KB) ( )   To classify the types of taxi speeders and estimate the effect of operational factors according to speeding frequency, average speeding severity, and average speeding duration, this study collected taxi GPS trajectories in Chengdu, China. The speeding characteristics and operational factors are extracted from the GPS data. Four types of taxi speeders (Speeder I, II, III, and IV) were identified by the Fuzzy C- means algorithm. Operational factors were processed to be binary indicators by comparing the average values of the whole speeders. Furthermore, a correlated random parameters mixed Logit model was introduced to investigate the influence of operational factor indicators. The results show that Speeder I and II have higher hourly speeding frequency, higher speeding severity, and shorter speeding duration than Speeder III and IV. For the operational factors, if the indicators of daily driving distance, daily income, distance ratio of driving on low-speed limits road, distance ratio of driving at night, as well as speed variances of daytime, nighttime, and peak hours equal to 1 (greater than average values), the possibilities of being Speeder III and IV are increased by 15.39%~77.09% and 42.98%~302.38%, respectively. However, the possibilities of being Speeder I and II are reduced by -0.09%~26.57% and 38.74%~68.34%, respectively. Indicators of daily driving distance, distance ratio of driving on low-speed limits road, and nighttime speed variance are associated with unobserved heterogeneity among speeders. References | Related Articles | Metrics

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Pattern Discovery and Rule Mining of Drivers' Perception and Operation During Lane Changing Process LONG Yan，HUANG Jian-ling，ZHAO Xiao-hua 2021, 21(3): 237-246.  Abstract ( )   PDF (1724KB) ( )   To find the correlation between eye perceiving and hand- foot operating during the process of discretionary lane changing on the highway, and to explore the mechanism of the interaction between perception and operation, a driving simulator was used to carry out a highway driving experiment. Eye movement data and vehicle operation data were collected. Features of eye perceiving and hand-foot operating for an instant and during the whole process of lane changing were extracted. The Aprior algorithm was used to find frequent patterns and mine association rules of eye perceiving and hand- foot operating. For the instantaneous perception- operation, 13 frequent 3-itemset patterns were found in left lane changing and 18 frequent 3- itemset patterns were found in right lane changing. For the whole process, 4 frequent patterns were found in left lane changing and 3 frequent patterns were found in right lane changing. Six valuable association rules were found in the left lane and the right lane, respectively. Through the analysis of frequent patterns and association rules, right lane changing needs more perception time and more complicated handfoot operating behavior than left lane changing. The frequent patterns and association rules describe the characteristics of perception- operation and the association between them in the process of discretionary lane changing, which can provide the reference for safe lane changing and support for lane changing operations of unmanned vehicles. References | Related Articles | Metrics

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Predicting Performance Degradation for Airport Portland Cement Concrete Pavements Based on Data-driven WEI Bao-li，GUOCheng-chao，DENG Miao-yi 2021, 21(3): 247-253.  Abstract ( )   PDF (1566KB) ( )   In order to accurately predict the airport pavement performance degradation, this paper adopts a data-driven predictive maintenance method, analyzes two data sets by means of indicator variables, considers the influence of flight traffic volume and pavement surface thickness, and establishes a two-parameter prediction model for airport pavement performance degradation with taking the nonlinear function of decay of airport PCI(pavement condition index) as the expectation function. Based on the parameter estimation results of the model, a marginal effect analysis combined with the predicted performance curve is used to analyze the prediction of the degradation under different flight traffic levels and different pavement surface thickness classes. The results show that the data-driven method and nonlinear mixedeffects approach with the joint estimation technique can significantly improve the accuracy and effectiveness of airport pavement performance degradation prediction. References | Related Articles | Metrics

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Route Decision-making of China Railway Express Considering Border Delay Risk LV Min, SHUAI Bin, ZHOU Zhao-yu, ZHANG Shi-hang, ZUO Jing, LI Lin-qing 2021, 21(3): 254-259.  Abstract ( )   PDF (1568KB) ( )   PDF(English version) (846KB) ( 83 )   To choose an efficient and safe transportation route and manage the transport risk for China Railway Express (CRE), a Weibull distribution was implemented to measure the probability distribution of delay time, according to the delay time features of different types of borders. And a novel risk value measurement was constructed based on the expected loss theory. Considering the minimum comprehensive transportation cost of risk, time, and cost, a new route utility model was established. A depth- first traversal algorithm was used to solve the route selection of goods with different value of CRE from Chengdu to Berlin. The results show that high-value goods are more sensitive to border delay, and the rate of cargo loss has less impact on the delay cost; the delay risk of the optimal route is high with a 0.46 average delay rate; when the unit value of goods is 3 million yuan, the border delay cost of the optimal route is 1.2 times of the transportation cost. Attentions need to be paid on monitoring delay risk and dealing with an emergency of borders by related stakeholders. References | Related Articles | Metrics

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Forecast of Haikou External Passenger Volume Considering Free Trade Port in Hainan Province ZHANG Ya-nan, XI Yang, YANG Jia-yu, LIU Jian-feng 2021, 21(3): 260-267.  Abstract ( )   PDF (1972KB) ( )   PDF(English version) (1020KB) ( 76 )   This paper predicts the 2020 to 2035 external passenger transport demand of a typical sea island city-Haikou in Hainan Province. A system dynamics model was developed to incorporate multi- dimensional qualitative and quantitative influencing factors such as economy, policy, and infrastructure. The forecast results show that the demand for foreign passenger transport in Haikou will experience a steady increase in the next 15 years. and the total number of foreign passenger transport is expected to exceed 80 million in 2035. After a sensitivity analysis of the Gross Domestic Product (GDP), the result shows that when the growth rate is greater than 9%, the current facility construction plan needs to be further strengthened to proactively improve the supply capacity of transportation facilities. Based on the sensitivity analysis of the introduced population, it is concluded that the maximum economic benefit can be achieved when the scale of talent introduction is controlled at about 1 million people, the benefit is 6.9% higher than 0.6 million talent introduction and 5.1% higher than and the 1.4 million talent introduction. Based on the sensitivity analysis of the construction time sequence of airport and high- speed rail, the result shows that comparing with high- speed rail, the opening of airport can boost the growth of demand by 6.3% , which also indicates that aviation is a major way of external travel in sea island cities. References | Related Articles | Metrics

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Analysis of Weather's Influences on Metro Ridership in Fuzhou JIANG Shi-xiong, CAI Can-huang, LIN Yu-chen, CHEN De-wang 2021, 21(3): 268-274.  Abstract ( )   PDF (1634KB) ( )   Metro is a green travel mode, which is an important approach to mitigate urban traffic jams. Metro ridership is influenced by many factors. Weather changes quickly and can lead to variations in ridership. Understanding the relationship between metro ridership and weather can help to set up the corresponding measures for transportation organization. This paper aims to analyze weather's impacts on metro ridership. Due to the limitation of the traditional weather index, a comfort index is incorporated. The multiple linear regression is built between metro ridership and weather factors (atmosphere pressure, relative humidity, wind velocity, rainfall, wind-chill index, comprehensive comfort index, etc.) to quantify the influence. As the travel patterns are different on workdays and non-workdays, two regression models are developed. Results show that rainfall, wind-chill index, and comprehensive comfort index are significant for metro ridership on workdays, and rainfall, atmospheric pressure, relative humidity, wind-chill index, and comprehensive comfort index are significant for metro ridership on non- workdays. In general, the ridership is more sensitive to weather factors on non-work days. References | Related Articles | Metrics

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Station Operation Simulation and Passenger Flow Optimization at Wanjiali Square of Changsha Metro XIE Jian-ping,YANG Kun,ZHANG Yi-hao,ZHANG Hai-feng,XIE Yi-bin 2021, 21(3): 275-281.  Abstract ( )   PDF (2310KB) ( )   Urban rail transit is an important travel mode for residents. This paper focuses on the passenger flow organization at Wanjiali of Changsha Metro. The study investigates the strategies that efficiently organize the surge of in and out of the station and optimize passenger flow with existing equipment layout and under fixed building area. The goal is to provide a more comfortable travel environment, improve the entrance and exit efficiency, and reduce passenger congestions at the station. Based on the short-term and long-term passenger flow data of Wanjiali Station, this study proposes to re-arrange the entrance and exit directions and locations of ticket checking gates and stairs, and verifies the effectiveness of the proposed method using simulation software. The results show that the new arrangement can meet the practical needs and make the passenger flow organization scheme more coordinated with the station spatial layout. To a certain extent, it eliminates passenger congestions. From a comparison between the simulation results and the theoretical calculation results, it is found that the increase of pedestrian walking time increases first, then decreases and then increases again with the increase of the number of passengers in the station, which provides a theoretical basis for the prediction of pedestrian walking time in metro station. References | Related Articles | Metrics