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Theoretical Integration and Practice of System Engineering and Transportation in the New Era PENG Hong-qin , ZHANG Guo-wu 2022, 22(5): 1-6.  DOI: 10.16097/j.cnki.1009-6744.2022.05.001 Abstract ( )   PDF (1314KB) ( )   Systematic thinking is the foundation for the development of transportation system engineering. It is crucial to re- recognize the characteristics of the transportation system and its central role in the economy and society in this new era. Accelerating the pace of comprehensive transportation legislation can lay an institutional foundation for the construction and development of a modernized comprehensive transportation system. This forum, on the theme of "Theoretical integration and practice of system engineering and transportation in the new era", clarifies the concepts and implications of systematic thinking and system engineering, deeply analyses the characteristics and trends of the new era's development of transportation systems, analyses the technical system of the new generation of shipping systems, and provides recommendations for the focus and direction of high-quality railroad network development while. Moreover, this forum discussed the status, demand, and upcoming priorities for transportation system legislation, as well as the general pathway of building an intelligent civil aviation system. It also presented the content, scenarios, and techniques for integrating system science and intelligent urban transportation, as well as the implications and future research directions of integrated transportation system. Finally, it introduced measures to promote the development of journal in the field of transportation system engineering Related Articles | Metrics

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Review of Impact of High-speed Rail on Urban Economic Spatial Structure YANG Xing-qi, HUANG Hai-jun 2022, 22(5): 7-18.  DOI: 10.16097/j.cnki.1009-6744.2022.05.002 Abstract ( )   PDF (1633KB) ( )   High- speed rail (HSR) is the main framework of a regional rapid comprehensive transport network. As an efficient and fast mode between cities, it plays an important role in improving passenger transport capacity and alleviating existing rail freight pressure. This paper reviews the state-of-the-art results of impacts of HSR on urban economic spatial structure from the aspects of urban accessibility, factor market, and spatial structure, and then summarizes the common conclusions and differences. The direct impact of HSR (network) on intercity travel demand is revealed by analyzing the degree of change in accessibility and whether it is balanced across regions. The improvement of urban accessibility further reshapes the regional spatial distribution of production factors, accelerates the transfer of capital and population, promotes industrial development and employment, and has a profound impact on land and housing markets. The interaction of various market factors brings great opportunities to urban macroeconomy, especially the spatial reconstruction of HSR stations. Systematic evaluation of the impact of HSR on the urban economic spatial structure can provide a reference for the administration to make decisions on HSR investment, planning and construction, and impact assessment. Combined with theoretical research and practical experiences, and based on the background of the new era, this paper reveals some key research directions: the first is to study the economic benefits and revenue distribution of HSR investment and the impact of HSR on economic development andspatial distribution of factors, considering urban agglomeration as a new interest group; the second is to investigate the impact of HSR commuting behavior on capital, population, land, and other factor markets, and analyze the key factors affecting HSR commuting such as station location and ticket price changes; the third is to consider the new changes in the impact of HSR competition and cooperation between cities and the mixed running mode of passenger and freight on urban economic spatial structure; the last is to analyze the impact of HSR on the urban economy at a micro level by utilizing emerging technologies like machine learning and big data. References | Related Articles | Metrics

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Joint Optimization of Car Routing and Train Formation Plan Based on Transfer of Freight Flow from Road to Railway WANG Zhi-mei, YAO Shang-jun, CUI Zan-yang 2022, 22(5): 19-25.  DOI: 10.16097/j.cnki.1009-6744.2022.05.003 Abstract ( )   PDF (1629KB) ( )   Promoting the transfer of more freight flows from roadway to railway is an important strategy to achieve the goal of carbon peaking and carbon neutrality, which is also a key measure to promote railway development. The proposed method takes the freight transfer volume from road to rail, the choice of car flow route and formation direction as the main decision variables. A joint optimization model of the freight transfer volume, car flow route and train formation plan are developed to mini- mize the comprehensive transportation cost of roadway and railway networks. The model describes the transportation cost of transferred freight flow in mathematical formula, and obtains the optimal freight transfer volume, the car flow route and the recombination station through the model solution. For the non-linear characteristics of the model, assistant binary variables are designed to transform the model into a linear model, which can be solved by the optimization solver GUROBI. Through the numerical experiments, it was found that the model can configure a reasonable connection route and train formation plan for the freight flow transfer scheme. Compared with the existing research, the proposed model takes into account the connecting cost of the highway and railway and the cost of train accumulation and recombination, which increases the total logistics cost by about 23.06%, and reduces the transfer freight flow by about 4.91%. The model can accurately describe the process of road to railway freight flow transfer and provides theoretical references for creating the transporta- tion plan and organizational schemes. References | Related Articles | Metrics

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Optimization of Differentiated Fares and Subsidies for Urban Rail Transit WANG Qing , DENG Lian-bo , XU Jing 2022, 22(5): 26-36.  DOI: 10.16097/j.cnki.1009-6744.2022.05.004 Abstract ( )   PDF (2220KB) ( )   PDF(English version) (700KB) ( 44 )   This paper analyzes the fare schemes for different urban rail transitrider groups. Different rider groups include general groups and special groups (i.e., the elderly, the disabled, and students). Preferential fares and service frequency are analyzed to account for the heterogeneity of different groups. An optimization model is developed to determine the optimal fare discount rates and transit headways with the goal of maximizing the transportation equity for different groups. The method based on simulated annealing algorithm is designed to solve the proposed model considering the constrains of transit capacity, total subsidy, and fare discount rates. Taking the Metro Line No. 2 in Changsha city as an example, this paper analyzes and compares the fare discount rates for different rider groups and provides a feasible preferential fare scheme based on train operation plans. The results show an optimal fare scheme would beno discount for general groups, 40% discount for the disabled, 20% discount for the elderly, and 60% discount for students. The travel demand would increases by 1.06% for the disabled, 2.86% for the elderly, and 1.94% for students.When the government implements the subsidy policy, the subsidy amount can be determined by the preferential fare scheme of different groups and the service level of the operator. References | Related Articles | Metrics

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Commercial Premium Effect of Suburban Railroad Station Area from Urban Design Perspective YAO Min-feng, QIN Yu-chen, SHI Lei, ZHAN Xiao-dong 2022, 22(5): 37-46.  DOI: 10.16097/j.cnki.1009-6744.2022.05.005 Abstract ( )   PDF (2049KB) ( )   Station-city integration helps to increase the land value-added effect of rail transit station area. The current research on the effect of station-city integration design on commercial premiums is mainly on the macro level. This paper investigates the mechanism of the premium effect on the rent of commercial facilities in the station area and the effect of joint station-city development on the premium effect from a micro perspective. A spatial panel econometric model is developed to improve the classical characteristic price method and a cost-benefit analysis is performed. The Odakyu Odawara line of a suburban railroad in Japan is used as an example for the analysis. The results show that the premium value-added of suburban railroad station commercial facilities is significantly related to the type of combined station-city facilities, the combination method and the walkability factor, but weakly related to the location factor. The trend of commercial premium value-added within 500 meters of the station fluctuates non-linearly and peaks in the range of 100~200 meters. The results of the cost-benefit valuation analysis based on Kairaomyo station verify that a reasonable design of the combined station-city facilities can effectively enhance the proximity of commercial facilities to the station, thus promoting the premium effect and helping quickly feeding the construction cost of the rail transit station with positive revenue in the short term. The results of the study can provide a quantitative reference for planning and design decisions. References | Related Articles | Metrics

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Optimal Freight Service Analysis Based on Movement Surplus WANG Jia-bin, SUN Qi-peng, WU Qun-qi , YANG Han-xi , MA Fei, ZHENG Ying-ying, REN Wei 2022, 22(5): 47-54.  DOI: 10.16097/j.cnki.1009-6744.2022.05.006 Abstract ( )   PDF (1708KB) ( )   In the demand-driven principle, the independent value of freight demand is emphasized, the difference between movement value and movement cost is taken as the movement surplus of freight demander. The mechanism of freight demander's choice of freight service mode is revealed by maximizing the movement surplus, and it is used as the criterion for optimal fright service. To measure the movement value, the study classifies the freight demand into three categories based on timeliness and establishes the movement value functions based on the expected benefits of the demander. To measure the movement cost, the study defines the cost function of the whole process of movement by integrating quality elements of freight services such as transportation price, time, reliability, convenience, and safety. The movement value and cost functions are then connected, and the optimal freight service analysis model based on the movement surplus is developed with the quality elements of freight service as the core variables. The simulation study was performed to obtain the movement surplus curves of different demanders and also to identify the optimal freight service mode. The results show that the model can effectively analyze optimal freight services based on heterogeneous demand and can be applied to the conditions that potential demand is transformed into effective demand. The study provides a theoretical basis for enterprises and governments to determine transportation supply optimization strategies. References | Related Articles | Metrics

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A Review of Truck Driving Behavior and Safety QIN Wen-wen, LI Huan, LI Wu, GU Jin-jing, JI Xiao-feng 2022, 22(5): 55-74.  DOI: 10.16097/j.cnki.1009-6744.2022.05.007 Abstract ( )   PDF (2527KB) ( )   PDF(English version) (1042KB) ( 66 )   Driving behavior plays the most critical role in the complex environment of human-vehicle-road and it is a core factor in road traffic system. To deeply understand the driving behavior pattern and riskiness of truck drivers, this paper examines the influence of truck driving behavior on traffic safety, and systematically analyzes the research results related to truck driving behavior characteristics, riskiness and its relationship with traffic safety. 38 relevant literatures were screened out by using a proposed literature search strategy, and then a systematic summary by applying a LDA (Latent Dirichlet Allocation) model was given based on four research topics, including truck driving behavior identification, relationship between dangerous driving behavior and driving safety, risk factors associated with truckinvolved analysis, and driving safety assessment. Further, a general research pathway available for any topic was constructed based on the analysis elements such as data sources, feature engineering, and modelling methods, and thenfour topics were summarized with emphasis on data sources, variable selection methods, study site, and modelling methods. At last, several potential challenges on these research topics were refined, and four promising developing trends were proposed from the perspectives of description, explanation, correlation, and application. The analysis of the research indicates that it is necessary to adopt the multi-source information fusion from driving status, vehicle motion status, and road traffic conditions for research on driving behavior based on big data and artificial intelligence. Besides, further research is recommended to enhance the study of the interaction mechanism to crashes between trucks and other types of vehicles in the mountain road environment for exploring risk factors associated with truck- involved crash severity from an overall spatial-temporal view. Furthermore, it will be necessary to further improve the research on the relationship between truck driving behavior and safety under the high-tech intelligent automation environment such as intelligent connected and automated vehicles. The theoretical methodology and application framework for truck driving risk assessment should be developed. This paper provides valuable insights for truck accident management, highway freight platform monitoring, road alignment design and other application scenarios, so as to have a relatively comprehensive understanding of the interaction mechanism between truck driving behavior and traffic safety. References | Related Articles | Metrics

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Speed Distribution and Vehicle Type Classification of Mountain Expressway Based on Electronic Toll Collection Data XU Jin, YANG Zi-miao, CHEN Qin, CHEN Zheng-wei 2022, 22(5): 75-84.  DOI: 10.16097/j.cnki.1009-6744.2022.05.008 Abstract ( )   PDF (3034KB) ( )   In order to study the classification method of mountain expressway vehicles, based on the electronic toll collection data (ETC data) of a section of Baomao expressway in Chongqing, the speed distribution characteristics of different vehicles in gentle sections and continuous uphill sections are analyzed. The speed distribution of some vehicles in different linear sections has obvious characteristics, the speed distribution of type-3 trucks on continuous uphill sections is hump-shaped due to the existence of the speed limit for type-4 passenger cars, and the speed distribution in gentle sections is concentrated on the maximum speed of 92 km· h-1 . The speed distribution of different vehicles in a linear section is obviously different, and the speed distribution of passenger cars is scattered in the gentle sections yet relatively concentrated in the continuous uphill section, whereas the speed distribution of trucks is different; the speed eigenvalues of each vehicle on the continuous uphill section have decreased significantly, but the speed eigenvalues of some vehicles on the same road section are still relatively close. The speed dispersion of continuous uphill sections is greater than that of gentle sections, and the risk of rear-end collision is higher. Based onthe ETC data, the k-medoids algorithm is used to perform a cluster analysis on the vehicles in the gentle section and the continuous uphill section of the mountain expressway. The gentle section vehicles can be divided into 4 categories, including type-1 passenger cars, type-2 to type-4 passenger cars, type-1 trucks, and type-2 to type-6 trucks. The vehicles can also be classified into 4 categories in continuous uphill sections, including type-1 to type-4 passenger cars, type-1 and type-3 trucks without load, type-2 trucks, type-4 trucks, type-3 trucks with a full load, and type-5 and type6 trucks. This study is helpful for the formulation of speed management measures for mountainous expressways and the selection of representative vehicle types in road alignment design. References | Related Articles | Metrics

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Cooperative Weighting Method for Satellite-based Vehicle Positioning Based on Vehicle Infrastructure Information Interaction LIU Jiang, TAN Si-lun, CAI Bai-gen, WANG Jian 2022, 22(5): 85-96.  DOI: 10.16097/j.cnki.1009-6744.2022.05.009 Abstract ( )   PDF (3115KB) ( )   In order to satisfy the performance requirement of vehicle positioning based on the Global Navigation Satellite System (GNSS), the tracking and mapping of the complicated and dynamic vehicle operation environment by the weight assignment to the observable GNSS satellites are concerned. An overall framework for the enhanced collaborative positioning based on information interaction is established. Based on the Weighted Least Squares (WLS) navigation calculation scheme, a cooperative weighting method is designed based on the Light Gradient Boosting Machine (LightGBM) modeling and comprehensive decision-making considering multiple neighboring vehicles. In this method, a modeling solution for the satellite pseudo-range residuals within the learning and modeling channel is proposed using the LightGBM algorithm. In addition, a weight decision strategy for the satellite measurements is presented within the weight calculation channel by involving the calibration by the predictions from multiple neighboring vehicles. Results of experiments show that the established pseudo-range residual model using the LightGBM method achieves an enhanced prediction capability over Support Vector Machine (SVM), Random Forest (RF), and LightGBM constructed by basic characteristics. The Root Mean Square Error (RMSE) is reduced by 62.1%, 29.9%, and 60.4%, respectively. The standard deviation of horizontal position error by the proposed solution with the LightGBM model and cooperative weighting is reduced by 48.5% and 47.6% compared with the equal weight strategy and the elevation/SNR (Signal Noise Ratio) integrated weighting strategy. The results illustrate the great value inguaranteeing the advantage of the information interaction mechanism and optimizing the performance of GNSS-based vehicle positioning under the cooperative vehicle infrastructure scheme. References | Related Articles | Metrics

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Mechanism of Non-recurring Congestion Evolution Under Mixed Traffic Flow with Connected and Autonomous Vehicles MA Qing-lu , NIU Sheng-ping , ZENG Hao-wei , DUAN Xue-feng 2022, 22(5): 97-106.  DOI: 10.16097/j.cnki.1009-6744.2022.05.010 Abstract ( )   PDF (4371KB) ( )   This paper investigates the interference between connected and autonomous vehicles (CAVs) and the traditional vehicles in mixed traffic flow, and proposed a model to describe the evolution of the non-recurring congestions in the mixed traffic flow. The model is developed based on the traditional traffic flow statistical theory model and the first-order continuous medium model, and introduced the intelligent driver model (IDM) and cooperative adaptive cruise control (CACC). The study uses the roadway section from Huatao Interchange to Banan Interchange in Chongqing City as a case study to examine the congestion evolution under different permeability ( Pc ) of CAVs in the traffic flow. The results show that higher penetration rate of CAVs relates to more significant improvement of the flow, occupancy, and speed of the mixed traffic flow. However, the improvement of congestion dissipation by CAVs is more obvious when Pc ≥ 0.2 . When Pc ≤ 0.8 , the duration of the congestion dissipation state with interference measure is approximately 50% of that without interference measure. When Pc = 1.0 , the traffic capacity of CAVs is 2.34 times of that in traffic flow with only traditional vehicles. The traffic congestion evaluation indexes are calculated under noninterference and interference measures and compared with the simulation results. The maximum relative error is within 5.38 %, which verified the model's accuracy. The research results provide important references for traffic congestion evaluations. References | Related Articles | Metrics

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Pyramid-feature-fusion-based Two-stage Vehicle Detection via 3D Point Cloud ZHANG Ming-fang, WU Yu-feng, WANG Li, WANG Pang-wei 2022, 22(5): 107-116.  DOI: 10.16097/j.cnki.1009-6744.2022.05.011 Abstract ( )   PDF (2632KB) ( )   To improve the performance of vehicle target detection in three dimension (3D) point cloud bird eyes view (BEV), this paper proposes a two- stage 3D point cloud vehicle target detection framework based on the pyramid feature fusion. First, the original 3D point cloud is encoded by dimension reduction and voxel occupancy, which results in a two-dimension (2D) feature map. Then, the up-sampling network is used to transfer high-level semantic features, and the down-sampling network is used to transfer low-level location features. A one-stage pyramid network structure is constructed to extract vehicle target features. The candidate regions with different scales are obtained through the region proposal layer. The scale of each candidate region is aligned by the region of interest pooling layer, and the multi-scale features are fused by the full connection layer to extract the vehicle target features under different receptive fields. In addition, in terms of loss function, the sine and cosine angle loss is supplemented and weighted into the total loss function to optimize the prediction of vehicle target heading angle. The experimental analysis based on Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) open dataset shows that the proposed algorithm can effectively supplement the feature extraction of 3D point cloud aerial view compared with the benchmark network, and the average detection accuracy in difficult detection tasks is improved by 5.07% to 8.59%. References | Related Articles | Metrics

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Influence Factors and Coupling Relationship of Traffic Accident Injury Degree Based on a Data-driven Approach HU Li-wei , LV Yi-fan, ZHAO Xue-ting, XUE Yu, ZHANG Cheng-jie, LEI Guo-qing , LIU Fan 2022, 22(5): 117-124.  DOI: 10.16097/j.cnki.1009-6744.2022.05.012 Abstract ( )   PDF (2281KB) ( )   In order to accurately identify the relevant factors affecting the traffic accident injury degree of mountainous expressway (TAIDME), a model named random forest naive bayes-coupling degree model (RFNB-CDM) was constructed. Firstly, 1760 pieces of accident data of mountainous expressway in Yunnan Province from 2016 to 2020 were processed. And 18 factors including accident information, road information, accident motor vehicle information, and driver information were studied as initial features. A RF model was used for feature extraction, and the importance ranking of each factor for the severity of traffic accidents (TASME) of mountainous expressway was obtained. Secondly, the new features are input into a NB model to conduct a single factor analysis on the influencing factors of TAIDME. To improve the shortcomings of the original model that cannot accurately describe the relationship between the influencing factors, this paper introduces the coupling degree model to make an example verification analysis. Eight kinds of factors, i.e., rear-end collision, the period from 18:00 to 6:00 of the next day, the number of accident vehicles, downhill, no street lighting at night, freight, large and medium- sized trucks, and straight uniform are more likely to increase TAIDME. The coupling effect of rear- end collision and straight uniform velocity is more likely to lead tomajor accidents. Road surface dryness, roadside metal protection, and central green belt isolation can reduce TAIDME, and when roadside metal protection and central green belt isolation are coupled, the TAIDME can be reduced. The conclusion of this study can provide a theoretical basis and decision- making reference for the prevention of traffic accidents and the reduction of the injury degree of mountain highway accidents. References | Related Articles | Metrics

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Train Timetable Collaborative Optimization Model Considering Transfer Heterogeneity for Urban Rail Transit System SUN Hui-jun, DAI Pei-ling, GUO Xin 2022, 22(5): 125-134.  DOI: 10.16097/j.cnki.1009-6744.2022.05.013 Abstract ( )   PDF (2113KB) ( )   Under the background of urban rail transit network operation, there exists significant heterogeneity of transfer demand at the transfer stations. This paper develops the indicator of coordination degree to quantify transfer heterogeneity, according to the transit network topological characteristic of the transfer stations, and various transfer demands at different times and directions. Then, a train timetable optimization model is built to optimize the number of train synchronization and improve passenger transfer efficiency. Besides, a particle swarm optimization algorithm based on the beetle antennae search is designed to solve the proposed mixed-integer nonlinear programming model. We then test our approaches by a case study of the Beijing rail transit network. The results show that (1) the presented model can optimize the train coordination for the urban rail transit network based on the indicator of coordination degree, (2) the number of train synchronization can be improved by 33.86% and the average passenger waiting time can be reduced by 22.75%, and (3) the designed algorithm is of better performance than the primary PSO and BAS algorithms in the aspects of the global search ability and solving efficiency. Summarily, our approaches can significantly improve the efficiency of urban rail transit transfer and provide theoretical references for improving the quality of urban rail transit service. References | Related Articles | Metrics

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Impacts of a New Rail Transit Line on Travel Mode Choice LI Jin-hai, YANG Guan-hua, DING Yi, LIU Jian-feng 2022, 22(5): 135-140.  DOI: 10.16097/j.cnki.1009-6744.2022.05.014 Abstract ( )   PDF (1654KB) ( )   This study explores the impacts of opening a new rail transit line on traveler's mode choice. A stated preference (SP) survey focusing on the travel mode shift was conducted, and the Multinomial Logit (MNL) models were proposed to estimate the model choice behavior of daily travel and commuting travel. Moreover, this paper quantitatively analyzes the influence of individual socio-economic attributes and travel mode attributes on travel mode shift. The results indicate that for daily trips with same travel time, the perceived negative utility (PNU) of urban rail transit (URT) passenger is 91.0% of that of bus passenger, and the PNU of commuting trip is 1.89 times of the average level of daily trips. Besides, URT travel time is proved to be the most significant factor affecting URT share. While travel time changes by 50.0%, URT share will change by approximately 10%. The research also reveals that bus is the most competitive mode for URT. The share of URT would increase by 6.80% when the bus travel time increases by 50%. A limited increase of parking fee or travel time cannot significantly shift the travelers using the car to the URT. Traffic demand management would be an effective way to promote mode shift. References | Related Articles | Metrics

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Subway Passenger Flow Characteristics and Network Failure Study for Cold Cities PEI Yu-long, LIU Jing, WANG Zi-qi 2022, 22(5): 141-153.  DOI: 10.16097/j.cnki.1009-6744.2022.05.015 Abstract ( )   PDF (3213KB) ( )   This paper analyzes the passenger flow and network characteristics of subway in cold cities and explores the correlation between passenger flow and cold climate. More than 110000 subway passenger flow data from 2013 to 2020 from the "Multi-modal Public Transport Cooperative Operation Technology and Demonstration Project for Cold Cities" are used for the study. The paper proposes an effect impedance Space L-Space P model to establish the subway abstraction network. The time dimension is divided into week, month and years for the subway passenger flow characteristics and perturbation factors analysis. A failure model of the subway network is established for the cold cities, and the passenger flow distribution of subway stations and lines after the disturbance is analyzed. The subway data of Harbin and Nanjing cities are used to analyze the correlation between subway network passenger flow distribution and climate through the transfer entropy causality. The effect of cold climate on subway passenger flow is then obtained. The result shows that the collected subway passenger flow data can fully show the status and change trend of passenger flow, and meet the requirements of accuracy and quality of passenger flow data analysis. In the past eight years, the subway passenger flow in Harbin has shown an obvious growing trend. The distribution of subway passenger flow has a low peak in February, a gradual increase in March, and a stable and slightly fluctuating flow from March to December. In the summer, the transferring passenger flow decreases from August to June, and in winter, the lowest transferring passenger flow is observed in February. The weekly transferring passenger flow mostly reaches the peaks on Monday and Friday. The key stations were identified by the subway network failure model. It was found that the winter passenger flow in Harbin is slightly higher than other three seasons. And the subway network is more fragilein winter. The simulation analysis combined with the actual data shows that temperature and subway passenger flow have a certain correlation, and the correlation is more significant in Harbin than in Nanjing. References | Related Articles | Metrics

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Integrated Optimization of Train Service Planning and Shipment Allocation for Airport Expresses Under Mixed Passenger and Freight Transportation LI Zhu-jun, BAI Yun, CHEN Yao 2022, 22(5): 154-163.  DOI: 10.16097/j.cnki.1009-6744.2022.05.016 Abstract ( )   PDF (2258KB) ( )   PDF(English version) (860KB) ( 20 )   The airport express has the potential to utilize its surplus capacity to develop freight transportation services. To implement mixed passenger and freight transportation on the airport express, two freight transportation modes, i.e., inserting dedicated freight trains and using the surplus capacity of existing passenger trains, are considered in this study. An optimization model on freight train service planning is developed to determine the train stopping plans, train formation, timetables, and shipment allocation. The objective of the presented model is to maximize the freight profit, which includes freight revenue, loading cost, inventory cost, and train operating cost. To solve the model, a onedimension searching approach is proposed to determine the number of inserted freight trains. The Gurobi solver is applied to produce the train service plans of the linearized model with a determined number of freight trains. The train formation is allowed to be zero to ensure the monotonic increasing of the objective function during the searching process. An experimental study based on the real airport express is performed to verify the effectiveness and efficiency of the proposed model and algorithm. The results indicate that the proposed method could enhance the operation profit by selectively meeting freight demand without disturbing the passenger trains service. Compared to the all-stop mode, allowing flexible stopping patterns of freight trains could increase the freight profit by 5.2% . Compared to the operating mode with fixed train formation, allowing flexible train formation could increase the freight profit by from 5% to 35% with various freight volume and shipping time requirements. The advantages of flexible train formation are more obvious when the shipping time requirements are relatively high. References | Related Articles | Metrics

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Joint Optimization of Ticket Price and Ticket Time Window for High-speed Railway Based on Preference Order Choice YAN Zhen-ying, WANG Yu, HAN Bao-ming, LI Xiao-juan 2022, 22(5): 164-173.  DOI: 10.16097/j.cnki.1009-6744.2022.05.017 Abstract ( )   PDF (2039KB) ( )   This paper proposes a preference order model with flexible form and good applicability to describe passengers' ticket choice behavior and expands the research method of joint optimization of existing high-speed railway dynamic pricing and ticketing control strategies. The study defines the ticket classes based on the price change range. With the preference order model, the ticket sales control is carried out by optimizing the ticket time window, while the ticket price is also optimized within a certain range to realize the joint optimization of ticket prices and time windows. Based on the analysis of elastic passenger flow, this paper uses the preference order choice probability, arrival rate and time window length to calculate the ticket sales. The study also sets the ticket ranking according to the operation needs, take the ticket time window and ticket price of each class as the decision variables, and establishes a nonlinear programming model to maximize the expected ticket revenue. The particle swarm algorithm and linear programming are precisely nested to solve the model. The results from the Beijing-Shanghai High-speed Railway case study show that the joint optimization scheme improves the total expected revenue of high-speed railway tickets by about 4.54% compared with the scheme of fixing the fare of each class and only optimizing the time window. The expected total revenue of the joint optimization scheme under different demand levels is higher than that of the fixed fare scheme. The expected total revenue increases as the probability of transfer purchases increases, and the expected total revenue of the joint optimization scheme under different transition probability values is higher than that of the fixed fare scheme. The proposed method can provide decision support for the dynamic pricing of high-speed railway trains and the formulationof sales control strategy. References | Related Articles | Metrics

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High-speed Railway Express Cargo Flow Allocation and Operation Organization Optimization Under Varying Demand CHEN Xing-han, ZHOU Pei-yu, LANG Mao-xiang, YU Xue-qiao, LI Shi-qi 2022, 22(5): 174-186.  DOI: 10.16097/j.cnki.1009-6744.2022.05.018 Abstract ( )   PDF (3298KB) ( )   This paper proposes the optimization method for cargo flow allocation and organization under the normalization and large-scale network operation for the high-speed railway (HSR) express considering the operational characteristics of the HSR express with one place cargo collection and multiple places for shipment and the variation of the demand of China's express market in the future. The main decision variables are the volume of HSR express between each Origin Destination (OD) pair under the mode of passenger train piggyback transport, reserved carriage and HSR freight train. The objective is to minimize the total operating costs. A mixed- integer programming (MIP) model is proposed for cargo flow allocation, which calculates the allocation of cargo flow in the HSR express network and creates the combination optimization scheme of cargo flow OD transport route and the operation organization mode for each HSR express channel. The method of "three-stage" forecasting of HSR express cargo flow OD is used to forecast the demand for HSR express between cities as the cargo flow input. The numerical experiments based on a network consisting of nine domestic express central cities are conducted to verify the effectiveness of the proposed methods, which are all computed by the Gurobi solver code in the Python programming language. The results show that using the piggyback and reserved modes in the low volume period can accommodate 90.7% of the transport needs. In the peak period, the operation organization mode can be adjusted according to the adaptive relationship between OD pairs of cargo flow and network capacity so as to fully utilize the idle capacity of HSR and improve operational efficiency. References | Related Articles | Metrics

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A Competitiveness Model of Public Transport Based on Travel Time Accessibility WENG Jian-cheng, ZHANG Meng-yuan, JING Yun-qi, ZHANG Xiao-liang, LIU Dong-mei 2022, 22(5): 187-195.  DOI: 10.16097/j.cnki.1009-6744.2022.05.019 Abstract ( )   PDF (5414KB) ( )   In order to achieve quantitative evaluation and analysis of key influencing factors on the competitiveness between regional public transport and private car travel, the information on the whole travel time by public transport and private car were calculated based on dynamic and static public transport data, taxi travel data, travel survey data and route planning data. A competitiveness evaluation model was then built from the perspective of travel time accessibility. Since public transport competitiveness has spatial effects, a spatial Dubin model was developed by using land use and transport facility as explanatory variables to investigate the impact on public transport competitiveness. Taking Beijing City as an example, the relationship between regional public transport competitiveness and its various influencing factors was analyzed with different periods of morning, evening, and peak hours on weekdays. The resultsshow that the average value of public transport competitiveness is less than 1.50 during both the morning and evening peak periods, while around 1.74 during the flat peak. The competitiveness is relatively higher in the city center, along the metro lines, and in the areas around large residential communities. The results also indicate a clear spatial dependence and the existence of typical agglomeration areas of "low-low agglomeration" and "high-high agglomeration". The factors of land use, residential service density and metro station density have significant negative spatial spillover effects, while road network density and bypass coefficient show significant positive spillover effects. The proposed evaluation model could quantitatively assess the competitiveness of public transport, and the model can explain the interrelationship between competitiveness and factors taking into account spatial dependence. References | Related Articles | Metrics

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Dynamic Bus Routing Optimization for Demand-responsive Feeder Transit Considering Stochastic Bus Arrival Time SUN Qian, HU Da-wei, CHIEN Steven, JIANG Jie, GAO Tian-yang, JIANG Rui-sen 2022, 22(5): 196-204.  DOI: 10.16097/j.cnki.1009-6744.2022.05.020 Abstract ( )   PDF (4729KB) ( )   The arrival unpunctuality of demand- responsive bus transit seriously reduced the service level and the passengers' willingness to choose public transit. This paper studies the dynamic bus routing problem of demandresponsive feeder transit (DRFT) considering stochastic bus arrival time. A mathematical model is developed by optimizing bus routes to find the cost-optimal transit service, in which the total cost, consisting of operator cost, passenger travel time cost, and passenger waiting time cost is minimized. The innovation of the model lies in allowing passengers to submit real-time travel demand during the operation and defining the bus arrival time following a known distribution to describe its stochasticity. A heuristic combining genetic algorithm and neighborhood search was proposed. The proposed algorithm hybridizes the global search of a genetic algorithm with the local search of a neighborhood search algorithm. The validity and advance of the proposed algorithm are verified by the experimental test analysis. Finally, the results based on the experiment on Yanpingmen subway station in Xi'an City show that the consideration of stochastic bus arrival time could reduce the passenger waiting time and the total cost. References | Related Articles | Metrics

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Multi-type Conflict Severity Model for Uncontrolled Pedestrian Crosswalks CHANG Yu-lin, WU Zhao-yun, SUN Chao, ZHANG Peng 2022, 22(5): 205-214.  DOI: 10.16097/j.cnki.1009-6744.2022.05.021 Abstract ( )   PDF (2217KB) ( )   To reduce the multi-type conflict and improve the traffic safety at uncontrolled pedestrian crosswalks, this study proposes the traffic conflict index and regression analysis model to analyze the severity and influencing factors of the traffic conflict at the crosswalks. A conflict index (TTZ) is proposed in consideration of the influence of driver's visual field obstacle. The TTZ is combined with the conflict index of post intrusion time (PET) and the safety deceleration (DST) to quantify the severity of traffic conflict. By calculating the conflict index value, the fuzzy C-means clustering method is used to identify serious and non-serious conflicts. Taking the serious and non-serious conflicts as dependent variables, the study develops a multi-type traffic conflict severity prediction model based on binary Logit model. The results show that compared to single conflict, the severity of multi threat conflict is higher, in which 57.9% of multi threat conflicts are serious conflict, while 27.7% of single conflicts are serious conflict. Compared to pedestrian conflict, the severity of non-motorized vehicle conflict is higher, in which 45.7% of conflicts between nonmotorized vehicles and motorized vehicles are serious conflict, while 35.4% of conflicts between pedestrians and motor vehicles are serious conflict. For the influencing factor, the number of motor vehicles, waiting time for crossing the street, crossing speed, legal yield behavior of vehicles and other main factors have a significant impact on the severity of multi threat conflicts. For the severity of single conflicts, the number of motor vehicles, waiting time for crossing the street, crossing speed, yield behavior of vehicles in front and other main factors have a significant impact on the severity of the conflict. References | Related Articles | Metrics

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Pedestrian Crossing Style Recognition Based on Multi-source Parameter Fusion PENG Jin-shuan, ZHAO Liu-chang, YANG Huan-huan 2022, 22(5): 215-222.  DOI: 10.16097/j.cnki.1009-6744.2022.05.022 Abstract ( )   PDF (2263KB) ( )   Pedestrians are the vulnerable group in the urban traffic system. It is of great significance to explore the characteristics of pedestrian crossing behavior to reduce human-vehicle conflict and improve the safety of pedestrian crossing. This paper designed a pedestrian crossing experiment under two scenarios (free crossing and psychological critical crossing) to investigate the coupling relationship among crossing speed, psychological critical time window, visual characteristics, and other major parameters. The risk perception factor and critical safety factor were selected as the representation indexes of pedestrian style under psychological critical crossing state. The crossing style recognition model was developed to analyze the reliability of different styles of pedestrian crossing behavior. The results show that the age of pedestrian significantly affects crossing speed/mental critical time window. The psychological critical time window is negatively correlated with crossing speed/signal light area fixation probability and positively correlated with traffic area fixation probability. In the state of psychological critical crossing, from the result of style recognition, male is more cautious than female. The failure rate of risky crossing behavior is 65.22%. There are significant deficiencies in the assessment ability of moving function and visual exploration features of some elderly pedestrians performing risky crossings. The study results provide reference for the design and optimization of intersection facilities, pedestrian crossing education and training, etc. References | Related Articles | Metrics

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Modeling of Electric Bicycle Behavior in Unidirectional Flow Based on Improved Social Forces WANG Wei-li , LU Xiao-lei, ZHANG Wang, XIONG Hao-ran, YU Mian 2022, 22(5): 223-232.  DOI: 10.16097/j.cnki.1009-6744.2022.05.023 Abstract ( )   PDF (7353KB) ( )   As a convenient and efficient transportation tool, the electric bicycle is widely used in many countries, but the research on its microscopic behavior is still limited. In this study, the observational experiment on the driving behavior of electric bicycles was conducted at Shanghai Maritime University, and electric bicycle trajectories were extracted. Longitudinal spacing, speed difference, lateral spacing, and horizontal spacing are regarded as characteristic variables, and the decision-making behavior rules of electric bicycles are established by using the classification results of the CART decision tree. Then, based on the social force model, overtaking force and following force are introduced to simulate the decision-making behavior of electric bicycles. Three forms of overtaking force are considered. Specifically, the overtaking force is respectively represented by equations, fixed values, and calculated by adding a temporary target point. The model is calibrated and validated through the comparison of the observation data and a series of simulation tests, and the scenario that electric bicycles drive in unidirectional flow is selected for numerical simulation analysis. The results show that the trajectory error of the improved social force model is the smallest, in which the overtaking force is calculated by adding a temporary target point. Moreover, the horizontal spacing required for the electric bicycle overtaking is directly proportional to the horizontal speed and overtaking completion time. Lastly, the best horizontal spacing in overtaking is 2 m. References | Related Articles | Metrics

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Robust Optimization of Carpooling Routing Problem Under Travel Time Uncertainty YUAN Zhen-zhou, CHEN Si-yuan, WU Yue-lin, LI Hao-ran, XIAO Qing-yu 2022, 22(5): 233-242.  DOI: 10.16097/j.cnki.1009-6744.2022.05.024 Abstract ( )   PDF (5904KB) ( )   In order to relieve the negative impact of time uncertainty in carpooling process, the study focuses on the carpooling problem with travel time uncertainty. A budget uncertainty set is used to describe the travel time variable, and a budget coefficient with an adjustable uncertainty level is introduced to build a robust optimization model with the shortest total vehicle mileage and the least number of vehicles as the objective function. A two- stage algorithm is designed. In the first stage, based on the feasible carpooling routes between two passengers, we design a formulation to quantify the matching chance in terms of total vehicle mileage saving rate and the passenger time window matching flexibility, and then the matching chance is used as the weight to construct a passenger graph network and cluster the passengers. In the second stage, we design a Tabu search algorithm to solve the problem by constructing an initial solution with the sequential insertion heuristic method. The experimental results show that the clustering method can ensure the solution quality and improve the computational efficiency by more than 85% while reducing the passenger waiting time and detour distance. The robustness of the solution gradually improves when increasing the budget coefficient, but it increases the number of vehicles by 10%~40% and reduces the mileage saving rate by 1%~10%. The carpooling routes of the large-scale cases and the narrow time window cases are more sensitive to the uncertain time, and the wide time window cases can achieve a high level of robustness without adding too many additional vehicles and total mileage. References | Related Articles | Metrics

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Truck Scheduling Optimization Considering Combination of Multi-size Container Tasks Under Separation Mode JIN Zhi-hong, HUANG Ying, ZHANG Jia-yi, XU Shi-da 2022, 22(5): 243-252.  DOI: 10.16097/j.cnki.1009-6744.2022.05.025 Abstract ( )   PDF (2080KB) ( )   This paper focuses on the truck scheduling problem of multi- size container tasks in a local area near a terminal under separation mode. During the transportation process, the remaining capacity of the truck changes continuously with the tasks performed by the truck. Considering the matching between the container size of the task and the current state of the container truck, a mixed integer programming model is established with the objective of minimizing the total cost during the use, driving, and wait of all trucks. According to the model characteristics, an ant colony algorithm based on an infeasible arc filtering strategy is designed to improve the solution performance. Numerical experiments are carried out by randomly generating numerical examples with different task types, proportions, and sizes from Solomon data sets. The results prove the correctness of the model and the stability and effectiveness of the algorithm, and then the cost of the separation mode is compared with that of the traditional mode. The results show that the total transportation cost of the separation mode is 45.10% lower than that of the traditional mode. When the task scale increases, the difference in the cost between the two modes becomes more obvious, which shows the advantages of the combination of the separation mode and the multi-size container collection and distribution operations. References | Related Articles | Metrics

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Optimization of Truck Platooning Routing with Time Windows ZHANG Ze-xi, ZHONG Wen-jian, LIN Bo-liang 2022, 22(5): 253-263.  DOI: 10.16097/j.cnki.1009-6744.2022.05.026 Abstract ( )   PDF (1958KB) ( )   Truck platooning is an emerging and promising strategy to organize trucks to drive in relatively small gaps using semi- automated driving technologies. The operation mode is also called "road train" with the advantages of reducing fuel consumption and carbon emissions and enhancing traffic safety. From the operational and scheduling perspective, this study focuses on when and where to join a particular truck into truck platooning to facilitate the formation of truck platooning to maximize energy savings based on the multi- commodity network flow theory. The study analyzes the extra waiting time generated during the formation of truck platooning and quantifies the fuel consumption savings due to the reduction of aerodynamic drag by the formation of truck platooning. A truck platooning routing optimization model is developed under the condition of limiting the truck platooning size and considering reasonable detours. The outcomes of the optimization model could reflect the composition of truck platooning for links and directly show the routings of every transportation task by setting decision variables, which represent whether the transportation task passes through a link or not. The truck platooning routing optimization model is solved by commercial software, and 19 truck platoons are formed saving more than 14% of fuel costs. The results show that the proposed method can generate an ideal truck platooning routing plan, and the study provides a theoretical reference for the promotion and application of truck platooning. References | Related Articles | Metrics

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Delivery Method of Living Goods in Controlled Communities Based on Cooperation Between Drones and Truck JI Jin-hua, LIU Ya-jun, BIE Yi-ming, WANG Lin-hong 2022, 22(5): 264-272.  DOI: 10.16097/j.cnki.1009-6744.2022.05.027 Abstract ( )   PDF (1512KB) ( )   Considering the event of public health emergencies that living goods are contaminated by viruses, crossinfection of residents in the communities, and shortage of delivery personnel, this study proposes a method to deliver the living goods using coordinated drones and a truck. Drones are required to return to the parking position of the truck for disinfecting after each delivery. In this process, the optimization objective is minimizing the risk of cross-infection among community residents and the delivery cost, and the constraints are delivery service integrity, payload capacity of drones and timeliness requirements of living goods. A mixed-integer programming model is developed to collaboratively optimize the rated capacity and parking position of the truck, the required number and delivery plan of drones. The improved multi-objective particle swarm algorithm is then used to solve the proposed model. A special particle coding method is introduced, and the mutation operator is coupled to update the particle positions of some code points. The method is applied to the Nanyuan Normal residential area in Changchun city. The proposed method was compared to the truck and manual collaborative delivery mode in safety, delivery cost, personnel working intensity, and consumption of one-off prevention and control material. It was found that the proposed method can reduce the risk of cross-infection among community residents at least 91.8%, diminish delivery cost by 16.9%, decrease human resource input by 50%, and save about 46.1% one-off prevention and control material expenditure. References | Related Articles | Metrics

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Optimal Allocation and Routing of Sanitation Vehicles on Urban Roads Under Multiple Constraints NIE Qing-hui, LONG Xiu-jiang, LIANG Cheng, XIA Jing-xin, OU Ji-shun 2022, 22(5): 273-284.  DOI: 10.16097/j.cnki.1009-6744.2022.05.028 Abstract ( )   PDF (2736KB) ( )   To avoid unreasonable vehicle allocation caused by excessive manual experience in the urban sanitation vehicle dispatching problem, this paper proposes an approach for optimal allocation and routing of sanitation vehicles on urban roads under multiple constraints. First, multiple constraints in sanitation vehicle routing are comprehensively considered, including operation time limit, service time limit on links, driving speed limit, and vehicle exiting of the road network. The travel trajectory of each vehicle is described from time and space dimensions by expanding the physical road network into a time- space network. The optimal allocation and routing of sanitation vehicles are then described as an Arc Routing Problem (ARP) with multiple constraints. A mathematical model for minimizing the total vehicle ownership cost and travel time cost is developed. A branch-and-price algorithm is designed to solve the model accurately. The proposed approach was evaluated using 19 realistic instance networks in Industrial Park, Suzhou, China. The feasibility and effectiveness of the proposed approach were validated from three aspects, including economic cost, operational efficiency, and environmental benefit. The experimental results show that the proposed approach can significantly save the cost of sanitation operation and management while improving the travel efficiency of sanitation vehicles. Meanwhile, it is also capable of reducing carbon emissions effectively, forming good economic and social benefits and therefore providing a potential solution for smart sanitation. References | Related Articles | Metrics

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A Multi-dimensional "Efficiency-Fairness-Capacity" Balancing Method for Demand Splitting Distribution WANG Jian-wei, LIU Xu-xu, FU Xin, YANG Yang, CUI Meng-yan 2022, 22(5): 285-292.  DOI: 10.16097/j.cnki.1009-6744.2022.05.029 Abstract ( )   PDF (1828KB) ( )   This paper focuses on the emergency material distribution in special cases such as in natural disasters and major social and public events. A multi-dimensional method of "efficiency-fairness-capacity" is proposed for the distribution of emergency materials using highway transportation based on the restriction that demand can be split, and the objectives of the shortest distribution time, the smallest weighted time climbing value and the least number of distribution vehicles. An improved Ant Colony algorithm is designed to solve the model. The algorithm is improved in three aspects: choosing splitting points, pheromone updating and introducing variable neighborhood search operators, and implementing the initialization of pheromones when the solution is continuously constant to increase the randomness. The results show that the improved algorithm has higher stability (7.00% lower average deviation rate) and better optimality finding (7.41% higher optimization rate) compared to the traditional algorithm. From the results under multiple scenarios considering tri-objective, bi-objective, and decision makers with obvious preferences, it was found that the three sub-objectives of efficiency, equity, and capacity are paradoxical to each other. Increasing the distribution capacity can significantly improve the efficiency and equity. When the capacity is constant, the efficiency and equity are negatively correlated in the same proportion. The study results provide methodological references and support for the emergency material distribution with multi-factors and uncertain disaster relief objectives. References | Related Articles | Metrics

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Bi-objective Optimization of Ship Dam-passing Appointment Scheduling Considering Green Navigation GAO Pan , LIU Shun , ZHAO Xu , YU Hao 2022, 22(5): 293-299.  DOI: 10.16097/j.cnki.1009-6744.2022.05.030 Abstract ( )   PDF (2064KB) ( )   Navigation congestion of water control project is caused by many reasons, such as unbalanced arrival of ships and uneven distribution of supply and demand. This paper develops a bi-objective appointment optimization model which minimizes the average waiting time and the adjustment rate of ship arrivals. The trade-off relationship between the two objectives is also addressed in the study. Considering the situation that some ship might miss the appointment, this paper designed the rescheduling rules for dam-passing appointment. A non-dominated sorting genetic algorithm is used to solve the model, and the carbon reduction effect of the implementation of the appointment system is discussed. The Three Gorges Project is taken as an example to test the model effectiveness. The results show that the model could generate multiple feasible appointment scheduling schemes and account for the trade-off relationship between average waiting time and adjustment rate. The proposed scheduling scheme resulted in reasonable distribution of appointment quota and ship arrivals. In addition, compared to the original scheduling scheme, the proposed schemes in ideal and missed appointment situations can reduce the maximum carbon emission respectively by 27.51 tons and 20.04 tons. The rescheduling strategy further reduces the mean arrival adjustment rate by 2.7% and alleviate the impact of the ship might miss the appointment in some cases. References | Related Articles | Metrics

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Optimal Position of Trailing Aircraft Based on Hazard Zone in Formation Flight WEN Rui-ying, LIU Wen-han, WANG Hong-yong 2022, 22(5): 300-308.  DOI: 10.16097/j.cnki.1009-6744.2022.05.031 Abstract ( )   PDF (2693KB) ( )   Formation flight is one of the important measures to realize the green development of civil aviation. Based on the analysis of the hazard area of the tail vortex of the lead aircraft, determining the optimal position of the trailing aircraft is the key to formation flight. Firstly, based on the Probabilistic Two-Phase Wake Vortex Decay, the evolution of the induced roll moment coefficient of the trailing aircraft was analyzed by using the Hallock-Burnham vortex model and the induced roll moment coefficient model. Then, based on the safety threshold, the wake vortex hazard area of the lead aircraft was calculated with considering the influence of flight altitude, speed, and wind on the hazard area. Finally, based on the fuel flow reduction rate at different positions of the trailing aircraft, the optimal position of the trailing aircraft in formation flight was obtained. The results show that the induced rolling moment coefficient is first increased, then decreased, and again increased with the increase of the transverse distance between the leading and trailing aircraft. With the increase of longitudinal distance, it decreased slowly first and then rapidly. The higher altitude leads to a lower speed and a higher peak value of the induced rolling moment coefficient, and thus the larger wake vortex hazard area of the lead aircraft. With the increase of the longitudinal distance, the hazard area is decreased continuously, and the altitude is decreased continuously with the sinking of the vortex core. The crosswind diverges thehazard area, and the greater crosswind leads to the greater deviation. A tailwind increases the longitudinal distance of the hazard area, while a headwind does the opposite. When two B737-800 aircraft fly in formation at 12000 m altitude at Mach 0.78, if the longitudinal spacing between lead and trailing aircraft is 3000 m, the optimal position of the trailing aircraft in no wind condition is the transverse spacing of 30 m or negative 30 meters and vertical spacing of 29 m, and the fuel flow reduction rate is 7.01%. Compared with the no wind condition, the fuel flow reduction rate and vertical distance remain the same under the left wind of 20 meters per second, while the lateral distance increases. At the downwind condition of 20 meters per second, the reduction rate of the fuel flow increases, the lateral distance remains unchanged, and the vertical distance decreases. At the headwind condition of 20 meters per second, the reduction rate of the fuel flow decreases, the lateral distance remains the same, and the vertical distance increases. References | Related Articles | Metrics

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Impact of Apron Spatial Configuration on Flight Departure Taxi Time at Busy Airports TANG Xiao-wei, CHEN Zhen, ZHANG Sheng-run, DING Ye 2022, 22(5): 309-317.  DOI: 10.16097/j.cnki.1009-6744.2022.05.032 Abstract ( )   PDF (2561KB) ( )   Flight departure starts from apron pushback, taxiway taxi until runway takeoff. Therefore, the apron space and the consequent spatial relation with runway-taxiway system have significant impacts on flight departure taxi. The prediction accuracy of flight departure taxi time plays an important role in the optimization of flight pushback time and the improvement of runway-taxiway system efficiency under Airport Collaborative Decision Making (ACDM). First, the concept of stand group is proposed to represent the spatial configuration of apron. The new feature variables are introduced, such as real- time and dynamic surface flight flow, unimpeded taxiing time and spatial index of stand groups. Then the prediction model is developed based on the classification and regression tree method to verify the impact of the new features on departure taxi time. The actual operation data of Capital Airport was used for the case study. The prediction results show that: while maintaining a high degree of goodness- of- fit, the new features characterizing apron configuration and spatial relation with runway- taxiway system improve the accuracy of the prediction model for departure taxi time. The number of flights respectively increases by 4.88% and 6.46% when the error between the predicted and actual values are within 3 minutes and 5 minutes. The method also reduces the waste of 2 to 3 takeoff slots per peak hour for Capital Airport. The new features closely relate to the prediction accuracy of departure taxi time. The overall surface flow has larger impact on the prediction accuracy than the surface flow of single runway, and the arrival flight features contribute more on the prediction accuracy than the departure flight features. References | Related Articles | Metrics

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Impact of COVID-19 Prevention and Control Measures on Expressway Transportation in Guangdong-Hong Kong-Macao Greater Bay Area LIN Pei-qun, ZENG Wei-jia, ZHOU Chu-hao, PANG Chong-hao 2022, 22(5): 318-327.  DOI: 10.16097/j.cnki.1009-6744.2022.05.033 Abstract ( )   PDF (2085KB) ( )   Under the background of normalized COVID-19 prevention and control, regional epidemics occur frequently in China. How to quantify the impact of COVID-19 prevention and control measures on economic operation and passenger and freight transportation has become an urgent problem. To this end, we design a calculation method for expressway transportation indicators, propose the level and stage division process of COVID-19 prevention and control measures, and then establish a difference-in-difference model to further analyze their impact on expressway transportation indicators. Taking major cities in the Guangdong-Hong Kong-Macao Greater Bay Area as an example, case studies are conducted based on the expressway toll data and COVID-19 prevention and control information from May 2020 to April 2022. The results show that in the level I (strengthened) stage, the passenger vehicle flow has dropped significantly, the drop in each case is between 8% and 27% , and the freight indicators have not changed significantly. In Shenzhen and Dongguan, both passenger and freight indicators dropped sharply in the level II (strict) stage. Passenger vehicle flow in the two cities dropped by 46.3% and 33.7%, and truck flow by 42.7% and 27.6%, respectively, and cargo and turnover decreased as much as truck flow. The average inter-city distance of expressway passenger cars has a downward trend under the level I stage, but under the level II stage, the average inter-city distance of passenger cars and trucks has increased significantly. This study can provide a certain reference value for the formulation and implementation of COVID-19 prevention and control measures in cities and urban agglomerations. References | Related Articles | Metrics

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Causes Analysis on Severity of Elderly Pedestrian Crashes Considering Latent Classes JIAO Peng-peng, LI Ru-jian, WANG Jian-yu, GE Hao-jing, CHEN Yue 2022, 22(5): 328-336.  DOI: 10.16097/j.cnki.1009-6744.2022.05.034 Abstract ( )   PDF (1524KB) ( )   The aging population is becoming more and more prominent, and the travel safety of elderly pedestrians is drawing attention. By proposing a two-step method that integrates latent class cluster analysis with random parameters Logit model, this paper explored the potential risk factors that contribute to the severity of elderly pedestrian crashes. We first cleaned the crash data of elderly pedestrians aged 65 and older with motor vehicles in North Carolina from 2007 to 2019. To eliminate the unobserved heterogeneity inherent in the crash data, a latent class cluster analysis was carried out to determine the optimal number of clusters based on the goodness of fit index. Three clusters of data were divided, and their characteristics were summarized. Then a random parameters Logit model was developed for each cluster to further explore the unobserved heterogeneity within the cluster, while the marginal effects of significant variables were calculated to quantify their impact on the probability of accident severity. The results show that the random parameters Logit model has better goodness of fit. The parameter estimates vary across clusters, and some variables are significant only within specific clusters. In cluster 1, "ambulance assistance" is a random variable, "accidents in the city" is a random variable in cluster 2, and no random variables are found in cluster 3, which degenerated to a multinomial Logit model. The results provide more reliable and accurate causes of traffic accidents in elderly pedestrians to traffic engineers and policymakers, supporting the formulation of safety plans for elderly pedestrians both in theory and technology. References | Related Articles | Metrics

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Driver Fatigue Detection Based on Spatial-temporal Features and Human Body Pose LI Tai-guo, ZHANG Tian-ce, LI Chao, ZHANG Ying-zhi, WANG Ying 2022, 22(5): 337-344.  DOI: 10.16097/j.cnki.1009-6744.2022.05.035 Abstract ( )   PDF (2273KB) ( )   To reduce the potential safety hazards caused by fatigued driving, this paper analyzed the relationship between the driver's body pose and the driver's fatigue state and proposed a driver fatigue detection model based on spatial- temporal features and human body pose. The improved simple- baselines network is used to locate the key points (spatial features) of the driver skeleton. By analyzing the changing characteristics of human pose during driving, the key points of the human body are modularized according to the principle of "high cohesion and low coupling", and multiple feature representations related to driver fatigue driving are designed. Finally, a sliding window is introduced to calculate the discrete degree of each fatigue feature, which is used as the input of the Long-short Term Memory Network (temporal features), to realize the prediction of the driver fatigue state. Through the driving behavior data of 13 test drivers, the experimental results show that the driver fatigue detection model based on spatial-temporal features and human posture proposed in this paper can achieve 97.73% precision, 98.95% recall, and 98.35% accuracy, indicating that the detection model is feasible. References | Related Articles | Metrics