2022 Selected Papers in English

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A Review and Prospect of Urban Public Transit Level-of-Service Research

MAO Bao-hua , WANG Min , HO Tin-kin , CHEN Hai-bo

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (1): 2-13. DOI: 10.16097/j.cnki.1009-6744.2022.01.001

Abstract （1368）

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This paper summaries the evolution of the concept of level- of- service (LOS) in transportation system and describes the characteristics of LOS in different stages. The implication of LOS has expanded from merely focusing on road design to incorporate multi-modal and wide operational areas. The LOS of public transit include two major components: transport efficiency and passengers' comfort, which are respectively associated with transport product design and passengers' perception to the services. The paper further reviews the LOS evaluation and classification research in the public transport system. These evaluation methods are relevant to the LOS elements and can thus be divided into the objective evaluation that are based upon transport efficiency and the subjective evaluation that focus on passengers' perceptions. Because of the differences in each country, the LOS classification of the Transportation Research Board may not be applicable to all countries and situations. The study then analyses the research and practice of public transit LOS in China and suggests that the existing regulations in China can be improved to clearly define the connotation of public transit LOS and include a systematical classification standard that applicable to China. The challenges in improving the LOS are discussed from the aspects of the formation of LOS, the complexity of evaluation factors, multi-links involved in a trip, and the need for government support and investment. Based upon the practices inurban public transit in China, the following three topics are worthy of in-depth study in the future: define and evaluate public transit LOS in consideration of full travel chains; Measure and evaluate the public transit LOS considering the uneven distribution of transit service quality; Satisfaction survey methods focusing on passenger perception differentiation and LOS evaluation methods based on advanced information technology. The paper also provides suggestions on taking LOS improvement as a starting point to promote the enhancement of public transit operation quality and efficiency.

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Estimating Truck Spontaneous Platoon Fuel-saving Potential Based on Trajectory Data

TAN Er-long , LI Hong-hai , ZHONG Hou-yue , HUO En-ze , MA Xiao-lei

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (1): 74-84. DOI: 10.16097/j.cnki.1009-6744.2022.01.009

Abstract （749）

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This study explores the influence of the maximum truck platoon size and the number of trucks on a spontaneous platoon and evaluates the fuel-saving potential in the real world. A dynamic spatiotemporal search scope was proposed to ensure a certain degree of exploration and prevent vehicles from spending much waiting time caused by the excessive pursuit of a larger-sized platoon. Moreover, we used the truck trajectory data of Liaoning Province to mine the Longest Common Subsequence (LCSS) of trucks, and an integer programming model was built to get the platoon schedule under the maximum fuel saving. The results show that: (a) The platoons' fuel- savings will increase with the increase of transportation missions and the maximum platoon length; the average driving distance and fuelsavings of vehicles in the platoons will eventually converge to a range; (b) The platoon traveled distance does not necessarily rise with the increase about maximum platoon length, i.e., the maximum fuel- saving strategy is not the maximum driving distance strategy for a spontaneous platoon; (c) More fuel-savings can be achieved by continuously increasing the spatial search scope without considering the temporal search scope; while increasing the temporal search scope cannot receive more fuel-savings when the spatial search scope is not considered; (d) 4000 trucks' missions could save up to 2026.21 L per day if they form platoons spontaneously; the average fuel-saving in the situation of platoons with five trucks can be improved by up to 13.92% compared with those of platoons with two trucks. Suppose this algorithm is applied to a larger-scale truck data set, the number of spontaneous platoons will increase significantly, and correspondingly, more fuel consumption and pollutant emissions can be reduced, which has excellent application potential

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Invulnerability Simulation Analysis of Chinese Iron Ore Imports Shipping Network

SHAO Fei , ZHANG Yong-feng , ZHEN Hong

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (1): 311-321. DOI: 10.16097/j.cnki.1009-6744.2022.01.033

Abstract （659）

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To assess the resistance of the shipping network of Chinese iron ore imports and the effectiveness of different safeguards, an invulnerability simulation model was established to fill the gap that traditional evaluation methods fail to consider the overall flow and nodes load state of the network. The data of a state-owned enterprise, major export ports in the world and major import ports in China were used to build the initial network. The network with different numbers of import ports was attacked in particular ways. The simulation results show that the network has a certain self- healing ability after the network is attacked, because of the adjusted ability of ship routes and redistribution of cargo load, but the network invulnerability will suddenly change after the key nodes are affected. The improvement of overload capacity has obvious marginal changes in improving network invulnerability if the overload capacity reaches a critical point, and improving the network survivability may aggravate network congestion. Therefore, it is necessary to strengthen the protection of key nodes, increase the number of import ports, and enhance the overload capacity of the ports, to enhance the invulnerability of the Chinese iron ore import shipping network under the COVID-19 and other critical events. Meanwhile, resources such as wharf yards and equipment should be reasonably allocated to prevent and deal with network congestion.

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Overview of Life-oriented Travel Behavior Research

ZHANG Jun-yi, LI Shuang-jin, MA Shuang

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (2): 1-16. DOI: 10.16097/j.cnki.1009-6744.2022.02.001

Abstract （1197）

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The research on travel behavior should make a paradigm shift from traditional approaches to the life-oriented approach supporting the interdependence of life choices. The life-oriented travel behavior research argues that travel behavior not only results from various life choices, but life choices are also affected by travel behavior. Such arguments have not only theoretical foundations but also empirical evidence. Accordingly, policy decisions related to citizens' lives require communications and collaboration across sectors. Cross-sectoral actions need common languages. The lifeoriented approach presents a brand new theory to support cross-sectoral transportation planning and management. It can also serve as a new theory to support cross-sectoral urban and regional policy (or general public policy). The lifeoriented approach is developed as a truly scientific system, which can serve as a common language to support crosssectoral policy making. In this review paper, first, the life-oriented approach and its implications to deal with travel behavior research are described. Second, the research progresses of the following ten topics are overviewed: lifestyles, car dependence, household energy consumption, information and communication technology and life, health and life choices, tourism behavior, mobility of the elderly, risky behaviors of young people, responses to natural disasters, and mobility biography. These topics are closely related to travel behavior. Finally, travel behavior research challenges and prospects are discussed from the perspective of the life-oriented approach.

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Job Accessibility Analysis Considering Travel Cost

XU Qi, CHEN Yue , HUANG Jing-ru , GAO Shun-xiang , ZHANG Zhi-jian

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (2): 37-44. DOI: 10.16097/j.cnki.1009-6744.2022.02.004

Abstract （687）

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Good job accessibility contributes to the innovation of the job-living interface, which is a key issue in building sustainable cities. Existing accessibility studies have mostly considered travel costs limited to travel distance or travel time, without fully considering travel costs and their effects on different travel modes. Based on POI (Point of Interest) and route planning data from Internet maps and business data platforms, this paper obtains fine-grained employment and travel data and uses an improved two-step floating catchment area model to propose a job accessibility measure that takes into account travel costs, to study the job accessibility of both public transport and private cars and to evaluate the impact of adding travel costs on job accessibility. The case study in Beijing shows that the average travel cost of private cars changes from 54% to 6% higher than that of public transportation after considering travel costs. And job accessibility is sensitive to travel costs, and the interaction between commuting and travel costs cannot be fully captured by considering travel time only; the impact of travel cost is reflected in an overall average decrease of 7.3% and 4.8% for public transportation and private car accessibility, and without considering travel cost, the job accessibility of subdistricts along with the fifth to sixth ring subway will be underestimated; there is a boundary effect of the travel cost on accessibility, and the higher the threshold, the smaller the impact. This paper provides insights for planners and policymakers making job accessibility-oriented adjustment strategies for the balance between jobs and workers.

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Urban Smart Public Transport Studies: A Review and Prospect

XU Meng , LIU Tao , ZHONG Shao-peng , JIANG Yu

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (2): 91-108. DOI: 10.16097/j.cnki.1009-6744.2022.02.009

Abstract （1767）

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Based on the recent development of urban smart public transport and its status in China, this study systematically reviews four crucial research areas, including the analysis of passenger flow characteristics, operations management, network design and optimization, and system evaluation. The limitations of existing researches and future research directions in the four areas are discussed. Correspondingly, this study examines the emerging trends of urbansmart public transport from four aspects: intelligent recognition and prediction of passenger flow characteristics, urban smart public transport operations in complex scenarios, urban smart public transport network design and optimization, and urban smart public transport service evaluation. The primary research questions associated with each aspect are proposed. Particularly, this paper identifies the following four urgent research topics, including (i) mining passengers’ complete travel chain information and providing integrated urban smart public transport travel services; (ii) integrating and optimizing public transport infrastructure layout and operational efficiency from the perspective of land use and transportation integration; (iii) building a three-dimensional bus operation and evaluation system from the perspectives of the government, enterprises, and users, based on their multi-level development needs; and (iv) building an integrated urban smart public transport travel service platform. Furthermore, in viewing the current development of urban smart public transport, this paper summarizes its current status and points out the shortcomings of existing research and critical scientific issues. It is revealed that integrated applications of emerging and disruptive technologies, such as big data, cloud computing, autonomous driving, intelligent, connected, and new energy vehicles, offered new opportunities and challenges in providing multimodal urban smart transport services and promoting sustainable urban development. However, new technologies will not spontaneously improve public transport services and accelerate sustainable urban development. Finally, this study emphasizes that future research needs to strengthen the multi-disciplinary intersection, highlight the combination of industry, university, and research, and provide strong scientific support for the highquality development of urban smart urban public transport in China.

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Calculation Method of Total Carbon Emission and Efficiency of Logistics Enterprises

JIANG Xiao-hong, CHEN Sha, ZHANG Yi

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (2): 313-321. DOI: 10.16097/j.cnki.1009-6744.2022.02.032

Abstract （918）

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The carbon emission coefficient method is used to measure the carbon emissions of logistics enterprises' transportation and storage. The input and output indicators of carbon emission efficiency are selected, and the Superefficiency Slack-based Measurement Model is adopted to obtain the three index values of technical efficiency, pure technical efficiency, and scale efficiency to evaluate the carbon emission efficiency of logistics enterprises. The empirical analysis is performed using SF Express's operating data from 2013 to 2020. The analysis results show that the technical efficiency from 2013 to 2016 and 2020 are all greater than 1, indicating that resource allocation has reached the optimal state. The technical efficiency values from 2017 to 2019 are all less than 1, mainly because of the low scale efficiency value. SF Express's transportation business volume has soared since 2017, and the scale efficiency has been gradually adjusted to find a relatively reasonable balance point by 2020, and the technical efficiency has been improved in 2020. The pure technical efficiency values from 2013 to 2020 are greater than 1. In recent years, SF has continued to increase its capital investment in technology to seek technological improvements. These results show that the proposed method is feasible, and the super-SBM model can effectively evaluate the carbon emission efficiency of logistics enterprises. Finally, we put forward the improvement measures for logistics enterprises to improve carbon emission efficiency from the aspects of innovative production technology, and energy saving and emission reduction technology.

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Platform Competition Strategy Based on Social Network Structure Characteristics of Online Ride-hailing Market

SUN Qi-peng, QIAO Jia-lu , ZHANG Kai-qi , SUN Jia

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (3): 1-6. DOI: 10.16097/j.cnki.1009-6744.2022.03.001

Abstract （1104）

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To study how the online ride-hailing platform selects effective strategies in the highly competitive industry to realize fair market competition, the paper investigations the competitive relationship between online ride-hailing platforms from the dual perspective of the social and econometric networks. Firstly, the competition network of the national online ride-hailing market is constructed, and the network topology is analyzed by selecting indicators such as degree centrality, structural hole, and core edge structure. Then take the practical revenue data of 112 online ridehailing platforms as an example, this paper integrates the network topology attribute into the econometric model and empirically analyzes the relationship between the network index of online ride-hailing competition and platform revenue. The results show that the competitive network of ride-hailing platforms in China is not balanced at present. The core platforms have dense network relations, where most of the platforms are dispersed in the network, and a few of them are on the edge of the market. And the platform's topological position in the network is closely related to the platform's revenue and the core-edge structure has the most significant effect on revenue. Finally, the strategies of using cutting-edge technology, establishing horizontal and hybrid alliances, and providing differentiated services are proposed to improve the market competition.

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Residents' Travel Mode Choice Behavior in Post-COVID-19 era Considering Preference Differences

YANG Ya-zao, TANG Hao-dong, PENG yong

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (3): 15-24. DOI: 10.16097/j.cnki.1009-6744.2022.03.003

Abstract （919）

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In order to explore the choice behavior of residents' travel mode in the post-COVID-19 era, a choice behavior experiment was conducted. A mixed Logit model and a latent class conditional Logit model of travel mode choice were constructed based on the data obtained from questionnaire surveys. Stata software was used to calibrate the model parameters, and the main factors influencing residents' travel mode choices were obtained. The results show that both models reflect the heterogeneity of individual travel mode choices. Compared with the mixed Logit model, the latent class conditional Logit model has an improvement of 13% in the goodness of fit and an increase of 3.03% in the prediction accuracy, which provides an effective tool for analyzing individual heterogeneity of travel behavior under public health emergencies. The latent class conditional Logit model divides residents into four and five groups according to the two scenarios of low and medium risk areas. From the perspective of travel mode attributes, the waiting time and the traveling time have become the most important influencing factors for residents to choose the travel modes. From the perspective of personal socio-economic attributes, women with higher incomes are more inclined to choose private cars to travel. The older are more sensitive to travel costs, and men are more willing to choose bus and subway travel.

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Train Capacity Allocation Strategy and Optimization Model for an Oversaturated Metro Line

SHI Jun-gang , QIN Tan , LI Xiang , YANG Li-xing, YANG Xiao-guang

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (3): 112-119. DOI: 10.16097/j.cnki.1009-6744.2022.03.013

Abstract （693）

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To alleviate the extreme congestions of local stations in oversaturated metro lines, this paper proposes a carriage capacity allocation strategy and optimization method. This method allocates the train capacity to each station by reserving and allocating carriages to ensure that all passengers at each station, especially for the congested stations, can receive fair service and the extreme congestion can be alleviated. Considering the proposed strategy, this studytakes the number of reserved carriages of each train at each station as the decision variable. A linear integer programming model for carriage capacity allocation is developedto minimize the total waiting time of all passengers at each station. A numerical experiment is carried out in Batong Line of Beijing metro for the carriage capacity allocation in the downward direction during the morning peak hour from 7:00-10:40 am on weekdays. The experimental results show that the maximum number of passengers gathered at each station in the line has fallen within an acceptable range, among which the maximum number of gathered passengers has been reduced from 3642 to 1345, a decrease of about 63% . The total waiting time of passengers only increased form 418027 minutes to 420099 minutes, an increase of 0.5%. The results show that the train capacity allocation method performed well in alleviating the extreme congestions in oversaturated metro lines and realized the balance of passenger flow gathering at each station. The method can improve overall operational safety at the line leveland ensure the quality of passenger services.

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Synergistic Benefit Analysis of CO ₂ and NOx Emissions in Civil Aviation of China Under Dual-carbon Target

HAN Bo , DENG Zhi-qiang , YU Jing-lei, SHI Yi-lin , YU Jian

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (4): 53-62. DOI: 10.16097/j.cnki.1009-6744.2022.04.006

Abstract （798）

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As an important part of transportation, the civil aviation industry is of great significance to the implementation of the national carbon peak and carbon neutral policy. In this study, a comprehensive prediction model of carbon emission and air pollutant emission is constructed to fit the characteristics of civil aviation, and the growth of civil aviation aircraft and CO2 and NOx emissions in 2019-2050 is predicted. The synergistic control coordinate system and synergistic emission elasticity coefficient are used to evaluate the synergistic benefits of emission reduction. The research shows that the future annual increment of civil aviation aircraft will show a trend of continuous growth, which is closely related to the development of GDP, potential output, and labor efficiency. The improvement of fuel efficiency cannot change the current situation of the continuous growth of CO2 and NOx emissions in civil aviation. The development of sustainable aviation fuel will make the CO2 emission of civil aviation peak at 3.18×108 tons in 2045 and promote the continuous growth of NOx emission. This effect can be eliminated through technological advancement and the introduction of new power aircraft, and the peak time of CO2 emission in civil aviation will be advanced to 2040, in which the emission can be reduced to 2.65×108 tons. On this basis, accelerating the application of sustainableaviation fuel can make civil aviation CO2 emissions peak at 2.47×108 tons in 2037. Civil aviation cannot achieve a carbon peak in 2030. The proper introduction of sustainable aviation fuel, the acceleration of civil aviation technology improvement, and the application of new power aircraft are the best choices to strengthen the coordinated emission reduction of CO2 and NOx in civil aviation. Finally, some suggestions are provided that, the best way for the civil aviation industry to achieve dual carbon is to focus on improving aircraft fuel economy in the short term, accelerating the application of sustainable aviation fuel in the medium term, and realizing zero-carbon flight by relying on new powered aircraft in the long term.

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Vehicle Lane Change Intention Recognition Driven by Trajectory Data

ZHAO Jian-dong, ZHAO Zhi-min , QU Yun-chao , XIE Dong-fan , SUN Hui-jun

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (4): 63-71. DOI: 10.16097/j.cnki.1009-6744.2022.04.007

Abstract （1047）

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In order to accurately identify the vehicle's lane-changing intention and improve the driving safety of the vehicle, I comprehensively considered the spatiotemporal characteristics of the vehicle's lane-changing process and the influence of different characteristics on the vehicle, and proposed a lane-changing intention recognition model with attention mechanism, which is based on the combination of Convolutional Neural Network (CNN) and Gated Recurrent Unit Neural Network (GRU). Firstly, I filtered and smoothed the vehicle trajectory data, and divided the vehicle trajectory data into three categories: left lane change, right lane change, and straight driving, so as to construct a sample set of lane change intention. Secondly, I built a CNN_GRU model that integrates attention mechanism to identify the sample set of lane change intention. Considering the interaction between vehicles during driving, I utilized the position, the speed information of the predicted vehicle and surrounding vehicles as the input of the model. After the CNN layer feature extraction, I then chose the extracted features as the input of GRU layer. And I also added different weight coefficients to different features through the attention mechanism layer, and leveraged the Softmax layer to identify the lane change intention. Finally, I verified the performance of CNN_GRU model with fused attention mechanism by using the trajectory data of US-101 dataset in NGSIM, and at the same time, compared and analyzed it with LSTM, GRU, CNN_GRU and CNN_LSTM_Att models. The results showed that the proposed model achieves an overallaccuracy of 97.37% for vehicle lane change intention recognition with an iteration time of 6.66 s, which is at most 9.89% and at least 2.1% improvement in accuracy compared to other models. By analyzing the accuracy of intention recognition at different pre-determination times, we know that the intention to change lanes can be accurately recognized within 2 s before the vehicle changes lanes, and the accuracy rate is above 89%, so the model has good recognition performance.

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Impact of Urban Traffic Operations on Vehicle Carbon Dioxide Emission

FENG Hai-xia , WANG Xing-yu , XIAN Hua-cai , LIU Xin-hua , LI Jian , NING Er-wei

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (4): 167-175. DOI: 10.16097/j.cnki.1009-6744.2022.04.019

Abstract （783）

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To quantitatively analyze the impact of traffic operation conditions in different cities on motor vehicle carbon emission, this study first used the congestion delay index (CDI) data provided by a map big data platform to analyze the spatial distribution characteristics and CDI characteristics traffic congestion of major cities in China. A speed-based CO2 emission factor was constructed, and VISSIM software was used to simulate different traffic operation conditions and the corresponding motor vehicle carbon emissions. The results indicate: the distribution of traffic congestion cities is spatially dependent and aggregated, and two high aggregation centers have been found in the Yangtze River Delta economic zone and the Pearl River Delta economic zone; the CDI has an obvious 7-day periodic fluctuation law, which is greatly affected by weather and human activities and broken by the epidemic situation; Urban traffic conditions have a significant impact on CO2 emission of motor vehicles. When the traffic is in mild congestion (CDI is 1.582), the total annual CO2 emission of urban motor vehicles in China during rush hours is about 77 million tons, which is 4.51 times that in unimpeded conditions; When the traffic can keep basically unimpeded (CDI is 1.35), the total annual CO2 emission can be reduced by 29 million tons; When the traffic reaches moderate congestion (CDI is 1.909), the total annual CO2 emission of urban motor vehicles in China during rush hours can be increased by 22 million tons;traffic is in serious congestion (CDI up to 2.394), the total annual CO2 emission of urban motor vehicles in China can reach 133 million tons during rush hours. Improving urban traffic operation can significantly reduce CO2 emission of motor vehicle emissions.

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Capacity Analysis Method of Mixed Flow with Connected and Automated Truck Platooning

QIN Yan-yan , ZHU Yi-wen, ZHU Li, TANG Hong-hui

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (4): 275-282. DOI: 10.16097/j.cnki.1009-6744.2022.04.031

Abstract （572）

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Connected and automated truck platooning is expected to be one of the first scenarios for the application of connected and automated driving. This paper studies the traffic capacity of mixed traffic flow of connected and automated truck platooning, where the random mixed traffic flow is composed of connected and automated trucks, manual trucks, and cars. Firstly, this paper analyzes 10 types of car- following behavior in the mixed traffic flow considering the spatial distribution characteristics of the scale of connected and automated truck platooning, develops its probability expression, and then constructs a general capacity analysis method of the mixed traffic flow. Then, considering the randomness of truck distribution in the actual traffic flow operation, the mixed traffic flow of connected and automated truck platooning is divided into three situations: dominant flow, random flow, and inferior flow to improve the universality of the mixed traffic flow capacity analysis method. Finally, the connected and automated truckfollowing model calibrated by the measured data is selected for case analysis to verify the effectiveness of the theoretical analysis method. The results show that the increase of the proportion of connected and automated trucks, or the increase of its platooning size, are conducive to the reduction of vehicle conversion coefficient and relative entropy in the mixed traffic flow of the three situations, which can effectively improve the traffic capacity of the mixed traffic flow. Under different conditions such as the proportion of connected and automated trucks, the optimal platooning size of connected and automated truck platooning randomly distributed is 2~4 vehicles. At the same time, the trafficcapacity of three mixed traffic flows, i.e., dominant flow, random flow, and inferior flow, decreases in turn. The research results reveal the internal mechanism of improving the capacity of mixed traffic flow of connected and automated truck platooning and provide methodological support for the operation and management of intelligent network truck platooning in the future.

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Optimization of Differentiated Fares and Subsidies for Urban Rail Transit

WANG Qing , DENG Lian-bo , XU Jing

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (5): 26-36. DOI: 10.16097/j.cnki.1009-6744.2022.05.004

Abstract （925）

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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.

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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

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (5): 55-74. DOI: 10.16097/j.cnki.1009-6744.2022.05.007

Abstract （1267）

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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.

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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

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (5): 154-163. DOI: 10.16097/j.cnki.1009-6744.2022.05.016

Abstract （714）

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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.

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Empirical Analysis on Operational Profitability of Urban Rail Network in China

PENG Kai, LI Xia-miao

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (6): 68-73. DOI: 10.16097/j.cnki.1009-6744.2022.06.007

Abstract （759）

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This paper discusses the practical problems of financial sustainable development of urban rail transit network. An operation profit-loss balance model of network based on the calculation of ticket net income and operating cost is established to quantitatively analyze the impacts of fare rate, passenger flow intensity and fare discount factors on operational profitability. The research combined with empirical data shows that there are obvious differences in ticket price rates among the cities in China. The preliminary expansion of urban rail network brings operational benefit of passenger intensity, but this cannot continue when the network scale extends to over 300 km in suburbs, which leads to worse profitability and greater pressure of local governmental subsidy. Due to the characteristics in public welfare for urban residential commuter trips, and the differences of per-capita disposable income of urban residents and local governmental financial capability in various cities, it is necessary to study in detail the relationships among the ticket fare rate, the network scale and the urban rail system modes in the cities with different economic levels to improve the profitability of the urban rail network and finally promote the sustainable development of urban rail transit industry.

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Overtaking Duration Model of Two-lane Mountainous Highways Based on Survival Analysis

JI Xiao-feng, DAI Bing-you, PU Yong-ming, HAO Jing-jing

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (6): 183-190. DOI: 10.16097/j.cnki.1009-6744.2022.06.019

Abstract （614）

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This paper investigates the overtaking maneuver of two-lane highways in mountainous areas under mixed traffic flow conditions and identifies the relationship between key variables and the duration of overtaking. Taking a typical two-lane mountainous highway in Yunnan Province as an example, this paper uses an unmanned aerial vehicle to acquire video data of overtaking behaviors and extracts the vehicle trajectories. The variables of overtaking maneuver is constructed to obtain the overtaking characteristics of two-lane mountainous highways. The overtaking duration model is established based on survival analysis to determine the key variables and then analyze the quantitative relationship between the key variables and the overtaking duration. The results show that under the mixed traffic flow conditions, the average overtaking duration of the two-lane highway in the mountainous area is 10.3 s, and the average overtaking distance is 201.3 m, which is caused by the combined effect of drivers' driving style, high driving speed, and complex traffic flow conditions. The Log-logistic Accelerated Failure Time model has the best fitting effect on the duration of overtaking. The AIC and BIC are 272.989 and 265.650, respectively. The inflection point of the hazard function is about 13 s, indicating that the possibility of overtaking ending before 13 s is the largest. The key variables are the overtaking distance, the initial speed difference, maximum lateral distance, the oncoming traffic, the length of the overtaken vehicle, and the type of the overtaking vehicle. The variables with the greatest influence are the type of overtaking vehicle and the oncoming traffic . When the overtaking vehicle is a truck, the overtaking duration increases by 22.9%. When there is an oncoming vehicle, the overtaking duration is reduced by 17.8%.

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Measurement of Carbon Emission Reduction Effect of China's Freight Transportation Structure Optimization

ZHU Li-chao, LIU Zhao-ran, WANG Rui-qi, XIONG Qiang

Journal of Transportation Systems Engineering and Information Technology 2022, 22 (6): 309-315. DOI: 10.16097/j.cnki.1009-6744.2022.06.031

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Management department and academic community attach great importance to the optimization of freight transportation structure because the excessive volume of road freight transportation leads to high CO2 emissions, which is not conducive to early achievement of the "carbon peaking and carbon neutrality". Apart from freight transportation structure, a variety of factors affect CO2 emissions in freight transportation. However, researchers mainly focus on the impacts of other key factors, lacking a precise understanding of the impact of freight transportation structure optimization on reducing CO2 emissions. In this regard, this paper applies the top-down method to calculate the CO2 emissions of freight transportation in China from 1999 to 2019. A partial least square regression (PLSR) model with socio- economic variables (e.g., per capita GDP) and freight transportation characteristic variables (e.g., freight transportation structure) is constructed to quantify the contribution of each factor, which is used to simulate CO2 emissions reduction in 2030 caused by freight transportation structure optimization under different policy scenarios by adjusting usage fee of different freight modes. The results show that socio-economic variables contributed an average rate of 73% to the increase of CO2 emissions in freight transportation in the period of 1999 to 2019, which were significantly higher than freight transportation characteristic variables. The average contribution rate of the changes in the road, rail, and water freight share to the growth of CO2 emissions in freight transportation was 1.81%, -0.01%, and -0.26%, respectively. The extreme case of switching all road freight volume to rail or water in 2030 cannot achieve a reduction of 65% in CO2 emissions per unit GDP compared to 2005. In addition, the benefits of reducing CO2 emissions achieved by increasing the usage fee for high-carbon freight modes are more significant than reducing the usage fee for low-carbon freight modes.

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