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Evolution of Transportation Systems Engineering in China WANG Qing-yun, MAO Bao-hua, ZHANG Guo-wu 2021, 21(5): 2-11.  Abstract ( )   PDF (1286KB) ( )   Transportation systems engineering is one branch of systems engineering combining the systems engineering theories with transportation engineering. Since the introduction of this terminology in 1980s, the transportation system engineering in China have shaped its unique characteristics through the application of systems engineering into transportation systems. By reviewing the development of transportation systems engineering in the past decades, this paper analyzes the evolution of both theories and practices of transportation system engineering in China. Considering the key factors and important activities in the history of transportation systems engineering, the paper summarizes the characteristics of transportation systems engineering in different stages, and reveals the corresponding theoretical progress and outstanding achievements. In view of the tremendous changes of social and economic status in China in the past four decades, the paper proposes the key research areas for transportation systems engineering theory and practice, and the challenges in practicing the transportation system engineering. It reveals that the transportation systems engineering is accessing new opportunities in the new age. The professionals in the industry should focus on the improvement of service efficiency and consider the time and spatial characteristics of transportation demands and the evolution of transportation supply modes. It is also of great value to promote technologies and management mechanism under the target of carbon neutrality in China, and to solve the increasingly complex problems in transportation engineering practice and policy, which would support the development of transportation and transportation systems engineering in China through the academic, theoretical, and practical developments. References | Related Articles | Metrics

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Tradable Credits Scheme for Urban Travel Demand Management XU Meng, GAO Zi-you 2021, 21(5): 12-21.  Abstract ( )   PDF (1294KB) ( )   As an emerging approach for travel demand management, the tradable credits scheme (TCS) has received close attention and been deeply studied. This paper reviews and analyses the TCS researches in terms of public acceptance, mobility management modelling, and integrated traffic management mechanism based on the research progress of TCS on urban travel demand management in the recent five years from 2016. Comparing to the modelling and/or simulation based TCS studies five years ago, the current TCS studies focus more on the practical applications. However, the application feasibility has not been well considered in most of the TCS studies. This paper further analyses the definition of TCS and four key factors including the determination of total number of credits, initial allocation of credits, credits charging scheme, and the credits trading mechanism. The shortcomings in current TCS studies are reviewed and the key factors of TCS are presented based on the authors' understandings. It is proposed to understand the interactions, essences and functional field of the four key factors of TCS, and the specific feature of the city and the traffic management characteristics should be considered in the TCS studies. This paper also points out the areas or topics that are worth studying in the near future, for example, the impact of TCS on individual travel behaviour. The quantitative trading techniques of TCS for carbon neutral are recommended as one of key research directions. References | Related Articles | Metrics

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Architecture and Key Technologies for New Generation of Waterborne Transportation System YAN Xin-ping , LI Chen , LIU Jia-lun, YOU Xu , WANG Shu-wu , MA Feng 2021, 21(5): 22-29.  Abstract ( )   PDF (1546KB) ( )   This article reviews the research progress and engineering practice in green and intelligent waterborne transportation in recent years, including the latest research results in transportation equipment, infrastructure, and operation services, along with the application of green and intelligent technology. The existing problems and technical bottlenecks in current developments are analyzed. Facing the future development needs and challenges, this study proposes the definition of the new generation of waterborne transportation system, which is featured as green, intelligent, and resilient. Through analyzing the basic connotation of the new generation of waterborne transportation system, the study also summarizes the architecture of the waterborne system. On the basis of the cyber-physical system theory, the hierarchical structure is divided into elemental unit level, functional system level, and architecture system level. The core components of the system are green intelligent ships, digital ecological infrastructures, reliable shorebased support facilities, and resilient operation services within an integral framework. With the analysis of basic servicetopology and logic of the system, the“ship-port-cargo”and“man-system-environment”modes are analyzed from the physical and information aspects. The future transport organizational operation paradigm of ships is described as “shore-based control”, supplemented by“ship-based monitoring and watch-keeping”. The new pattern of waterborne transportation has been clearly defined with key technologies as the planning programming of systems, green intelligent waterborne transportation equipment, digital ecological infrastructures, construction and conservation techniques, intelligent control of ships, transport operation and organization, waterborne emergency rescue, and system testing and verification. The study proposes a transformative direction of waterborne transportation in the future, which provides effective support for the high cooperation among, humans in the loop, ship- based systems, shore- based stations, and cloud servers, which realizes the information interconnection, system co-construction, and systematic innovation and promotes a high-quality development of waterborne transportation. The research results can effectively guide the planning, design, construction, and application of the new generation of the waterborne transportation system, supporting the independent development and standardization of future waterway transportation. References | Related Articles | Metrics

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A Unified Traffic Assignment Method and Application Based on Network Assignment Genealogy WANG Wei , WANG Jian , HUA Xue-dong , YU Wei-jie, CHEN Si-yuan, WEI Xue-yan 2021, 21(5): 30-39.  Abstract ( )   PDF (3344KB) ( )   Considering the diverse needs of traffic assignment method applications in transportation planning, construction, and management, this study developed a unified traffic assignment method and framework that incoproate most of the commonly- used traffic assignment methods in traffic system analysis. This technique framework is embedded into the traffic analysis software "TranStar". The framework systematically integrates three modules, including "key model parameters", "traffic impedance function", and "basic traffic network traffic assignment models and corresponding algorithms". The proposed method can be used in a unified multi- modal transportation network which includes walking, biking, automous vehicles, and public transit. The proposed method also supports a unified application for urban planning, transportation infrastructure construction, traffic management and control, public transit system, and traffic policy design. The numerical application of the proposed methods in the road network and the transit network of Nanjing city shows that the unified traffic assignment method performs well when analyzing the multimodal transportation networks with over 10000 nodes, and the predicted multi- modal network flow under different scenarios provide valuable references for urban transportation system planning, construction and management. References | Related Articles | Metrics

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Technologies and Applications for Intelligent Vehicle-infrastructure Cooperation Systems ZHANG Yi , YAO Dan-ya , LI Li , PEI Hua-xin , YAN Song , GE Jing-wei 2021, 21(5): 40-51.  Abstract ( )   PDF (2145KB) ( )   Intelligent Vehicle-Infrastructure Collaboration Systems (i-VICS) represent the cutting-edge technology and an inevitable trend in the intelligent transportation systems (ITS) globally. It is critically developed to improve travel efficiency, optimize energy consumption, and reduce vehicle emissions, and will fundamentally change the management mode of traditional road transportation. Firstly, i-VICS is introduced in the paper as the common platform for future road traffic systems. Based on it, the change of service domains for the user services in the national architecture of ITS is discussed. The latest related technologies are then investigated for the implementation of i-VICS, including technologies for multimode wireless communication, intelligent networking, information security, and system integration, and also for the application of i- VICS, including technologies to support the collaborative perception, swarm coordinated decision-making and control, simulation-testing validation, and connected automated driving. With the consideration of the long- term development of i- VICS, the contents of implementation, degree for information sharing and synergistic functions that could be realized in different stages are presented. Furthermore, concerning the challenge from its implementation and application, the paper points out that to obtain deep understanding, to grasp the essence, promote the experience and moderate scale of application for i-VICS can effectively address the developmentof modern intelligent transportation system. In short, the fundamental theoretical research, key technology development and practical system application of i- VICS will play an important role in ITS and related disciplines, like systems engineering for transportation and science for systems. References | Related Articles | Metrics

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A Review of the Impact of Autonomous Driving on Transportation Planning HU Jia , LUO Shu-yuan , LAI Jin-tao, XU Tian , YANG Xiao-guang 2021, 21(5): 52-65.  Abstract ( )   PDF (1304KB) ( )   As vehicle is an important component of the transportation system, the development and application of autonomous driving is triggering a revolution of the transportation system. This paper focuses on the impact of autonomous driving on transportation planning. By summarizing the technologies, status in quo and prospect of transportation planning, this paper reviews the revolution in data acquisition and management, land use, parking demand, supply-demand analysis, traffic prediction and transportation network design in the environment of autonomous driving. Furthermore, from the perspective of transportation planning, this paper refreshes the understanding of transportation system with consideration of autonomous driving. This paper also proposes novel philosophy and methods of transportation planning, which provide a new analysis framework and research methods for traffic demand forecasting and traffic network design in the environment of autonomous driving. The understanding of transportation system could be refreshed from three aspects. First, traffic data will be more fine-grained and fresh.Second, changes in land use patterns will cause cities to expand and de-industrialize, and the demand for parking will decrease. Third, the supply capacity and reliability of the transportation system will be improved, and greater dispersion will take place in the temporal and spatial distribution of travel demand. Changes in methodologies of the transportation system planning are reflected in two aspects: demand forecasting and traffic network design. First, the framework of demand forecasting will be transformed from a four-step framework to a framework of model combination and travel behavior integration. In addition, in each step of demand forecasting, the characteristics of autonomous driving and its systematic impact should be analyzed. Second, the traffic network design will adopt a continuous-time dependent design framework, which is expected to improve traditional network design by solving the issue of responsive delay. This framework can adapt to and serve the dynamic land use and traffic demand. This study suggests that future research should devote the major efforts to investigating the impact of autonomous driving on traffic safety, congestion, public transit planning and non-motorized transportation planning. In addition, the research difficulties will lay on the following aspects: solving the issue of lacking real-world data of autonomous driving; revealing the mechanism of the transportation operation in the heterogeneous-traffic stage; coping with the situation when demand exceeds supply due to the traffic demand rebound, and evaluating the external costs which are difficult to measure. References | Related Articles | Metrics

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A Comprehensive Review of Traffic Signal Timing Practice and Techniques in the United States TIAN Zong, WANG Ao-bo 2021, 21(5): 66-76.  Abstract ( )   PDF (1347KB) ( )   Traffic signal control is a critical part of urban transportation management. As a cost-effective approach to traffic operational improvements, facilitating the development of signal timing has been of a great interest to traffic engineers and researchers in recent years. The United States (US) is one of the most advanced countries where traffic signals were first implemented, and its best practices and lessons learned could be beneficial to many other countries. This paper provides a comprehensive review of traffic signal timing practice and techniques in the US, focusing on signal control characteristics, timing development process and software tools, as well as emerging technologies and techniques. The signal control practice in the US (also Canada) possesses some unique characteristics comparing to other countries. First, some signal timing terminologies may only exist in the US or have different meanings, such as a “signal phase”. Those who are interested in understanding the US practice must go through the details of the term definitions documented in the US manuals and standards. Secondly, a special ring-barrier structure is widely adopted to describe signal phasing and timing. Through a combination of rings and barriers that imply the duration, sequence and compatibility of signal phases, this structure allows for safe and efficient implementation of signal timing, especially at typical intersections with actuated traffic signals. Thirdly, the US signal control facilities and signal timing techniques are mostly on traffic actuated control. In the context of an actuated control mode, timing development for isolated signals can be simplified, as signal operations are largely in response to detector actuations; hence, the major effort goes to developing signal coordination.An outcome-based procedure has been highly encouraged in the US signal timing development process. The procedure is comprised of several steps, such as data collection, data analysis, timing development, and timing maintenance, in which the effectiveness and efficiency of signal timing development must rely on advanced software tools. In this paper, five signal timing software tools are analyzed regarding features of data management, timing optimization, timing diagnosis, and performance evaluation. While all of these software tools have basic functions of signal timing optimization and data management, some major differences exist in terms of timing diagnosis and performance evaluation. Timing diagnosis is important for identifying erroneous and abnormal signal operations, which ensures consistency between the designed timing plans and actual field operations. The mobile version of TranSync features active time- space diagrams and visualization of ring- barrier- strucature- based signal operations, allowing for convenient timing diagnosis in the field. Performance measurement is needed for monitoring the quality of signal timing and validating the effectiveness of signal re- timing. Earlier software packages, such as TRANSYT- 7F, PASSER and Synchro, only provide performance evaluation functions based on deterministic algrithoms and simulation, while emerging tools such as Tru- Traffic and TranSync allow users to collect actual travel- run trajectories and produce performance evaluations accordingly. The signal timing practice and techniques in the US are transforming along with the emerging technologies. Numerous studies have been conducted in recent years, and two topics are highlighted in this review, i.e., traffic signal performance meansures based on new data sources and new signal control methodologies considering a connected-andautonomous- vehicles (CAV) environment. In recent years, a variety of data sources have been used to assess traffic control performance. Automated Traffic Signal Performance Measures (ATSPMs) is an influential research effort that incorporates high-resolution controller and detector event data to gauge traffic control efficieny such as the quality of platoon progression. Travel-run trajectory data are also used in some studies to evaluate signal coordination according to travel time and the number of stops. A vast number of studies are conducted on the second topic, investigating the impacts of future CAV applications and formulating many possibilities of next- generation traffic signal control. In addition to the two topics, a few studies are devoted to improving the classic signal timing optimization algorithms. The improvements are aimed at signal coordination for multimodal traffic and special cases. Lastly, this paper provides an outlook for future signal timing practice and techniques. Signal timing tools will continue to play an important role in satisfying complex traffic management strategies and goals. The innovative use of multi-source data will enhance the traffic timing process in terms of performance monitoring. The application of CAV technologies may lead to a revolution of signal control; however, a dramatic change of the current signal control infrastructure is unlikely in the near future due to the immaturity of the current research and the mixed driving environment during a transition stage. As a result, it advocates studies for improving traffic signal timing during the transition stage towards a complete CAV circumstance. Research efforts are also required for developing necessary updates for the classic signal timing theories that were established decades ago. References | Related Articles | Metrics

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Review of App-based Ridesharing Mobility Research CHEN Xi-qun 2021, 21(5): 77-90.  Abstract ( )   PDF (1811KB) ( )   App-based ridesharing mobility is an essential component of intelligent urban transportation systems. As an emerging mobile internet travel mode, it generates massive, complex, heterogeneous, multi-source, large-scale, and spatially-temporally correlated transportation big data, which contain rich information that can describe the supply and demand situations of complex transportation systems. This paper reviews the state- of-the- art and practical results of transportation management from the four aspects of app-based ridesharing mobility travel behavior mechanism, platform management optimization, government regulatory policies, and system simulation optimization, then summarizes the existing problems. Through the mobile internet transportation big data, the paper analyzes the influencing factors, characteristics identification, and the externalities of passengers' and ride- sourcing drivers' travel behaviors, tracks travel behavioral evolutions both on the individual and population levels, and reveals the balancing mechanism of supply and demand, as well as network equilibrium of the app-based ridesharing mobility system. We study to solve the spatial-temporal effect and short-term prediction problem of ridesharing demand and supply, optimize the pricing strategy of the app-based ride-sourcing platform, improve the platform matching and dispatching efficiency, and realize the optimal allocation of the spatial- temporal resources of supply and demand. By using the technologies of agent-based simulation, activity-based simulation, and data-driven simulation, the above results can be simulated and optimized to provide a theoretical basis and supporting tool for the government to formulate relevant regulatory policies and the platform to optimize operation management strategies. Finally, facing the complex dynamic mobile internet environment, we prospect some key research directions. References | Related Articles | Metrics

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Review on Application of Truck Trajectory Data in Highway Freight System GAN Mi, QING San-dong, LIU Xiao-bo, LI Dan-dan 2021, 21(5): 91-101.  Abstract ( )   PDF (1401KB) ( )   With the continuous improvement of the accessibility and accuracy of trajectory tracking data, truck trajectory data has been widely used in the planning and management of highway freight system. At the same time, the rapid development of artificial intelligence and big data analysis technology also brings new opportunities and challenges to the study of highway freight system. This paper comprehensively summarizes the researches on the application of highway freight trajectory data, and reviews the research objectives, main contents and research methods of existing literatures from three aspects: identification of freight travel information, prediction of key features of freight system, and further application of freight trajectory data. Literature analysis shows that the research on freighttravel information identification focuses on hot topics such as freight stop points, vehicles and goods, and activity travel patterns. However, the existing identification methods are mostly transplanted from the research of passenger travel, and more considerations need to be given to the unique characteristics of freight travel. In terms of forecasting the key features of the freight system, researchers mainly conduct research on topics such as freight travel time, spatial location, and travel demand, and proved the feasibility of forecasting freight characteristics based on trajectory data. However, the spatial and temporal range of prediction is relatively limited, further research is needed on specific freight tasks, characteristics of truck drivers, and freight policies. In addition, trajectory data are also further applied to freight travel route choice behavior, freight parking and rest behavior, driving safety, freight emissions and energy consumption analysis, freight policy evaluation. On the basis of analyzing the shortcomings of the existing research, this paper suggests that future research should focus on combining freight trajectory data with other multi-source data, make breakthroughs in three key technologies. First, in view of individuals of freight practice, it is necessary to focus on exploring the travel characteristics and travel patterns of efficient truck drivers and apply them in the freight system. Second, in view of new transportation technologies and new situations, the development and optimization of freight organization models, and strategies under the influence of autonomous driving technology and major emergency events should be focused. Thirdly, in view of freight supply and demand relationship and matching mechanism, the research on freight supply and demand status identification, and prediction of the whole freight process should be focused on, and the intelligent supply and demand matching model combined with deep learning methods should be trained and developed, so as to optimize the freight system scheduling, facilitate the integration of social scattered transportation resources and improve the overall efficiency of the freight system. References | Related Articles | Metrics

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A Review of Data-driven Car-following Models HE Zheng-bing , XU Rui-kang , XIE Dong-fan , ZONG Fang , ZHONG Ren-xin 2021, 21(5): 102-113.  Abstract ( )   PDF (1988KB) ( )   A car- following model is one of the microscopic traffic flow models that are widely focused on by transportation research and engineering. In recent years, the rapid technological advancement in information perception and acquisition, big data, and artificial intelligence, etc., has promoted the great development of data- driven carfollowing models. Based on data science and machine learning theory, data-driven car- following models obtain the inherent law of car- following behaviors through the training, learning, iteration and evolution of real-world vehicle motion data. This paper reviews the evolution of data-driven car-following models over the past 20 years and analyzes its two research waves driven by neural network and deep learning, respectively. Three typical types of data-driven carfollowing models and their representatives are reviewed, including traditional machine learning- based car- following models, deep learning-based car- following models, and model-data hybrid driven car- following models. Data source analysis indicates that, although a variety of high-fidelity trajectory datasets are constantly emerging, the Next Generation Simulation (NGSIM) datasets released by the United States in 2006 are still the most widely used, inparticular in recent years. Therefore, the transferability and generalization of the models are worth investigating. We also discuss from the following aspects: model input and output including how to involve more driving behavior variables, whether it is necessary to consider more behavioral variables, and whether the existing input and output can be replaced; Model testing and verification including insufficient testing, incomplete comparison, lack of unified test dataset and test standard. At last, the key factors regarding the originality and success of data- driven car- following models are discussed. It is expected that this review can help researchers better understand the past and present situations of data-driven car-following models and promote the progress of related research. References | Related Articles | Metrics

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Literature Review on Rail Train Timetabling NIU Hui-min 2021, 21(5): 114-124.  Abstract ( )   PDF (1230KB) ( )   The rail train timetabling problem has always been a hot research topic in the field of transportation and operations research due to its wide practical applications and complex computational challenges. As a sub- stage of the hierarchical planning of rail transit operations, the timetable problem can be extended to multiple related areas by integrating the upper- layer line planning problem and the lower- layer rolling stock scheduling problem. The train timetable design is to determine a conflict- free running path for each train in the elaborated space-time network, in which the objectives are the user- based measurements such as the passenger waiting times or the supply- based measurements such as the operating costs. If the overtaking activities are not allowed and the stop-skip pattern is given, the optimization models for train timetables can be formulated by using integer variables. Otherwise, zero-one variables are required to represent the departure orders or skip- stopping decisions of trains at the stations. Generally, the models are typical large-scale, multi-objective and strong-coupled NP-hard problems. It is important and difficult to design effective solution algorithms for this type of problems. For the cases with simple conditions and small scales, one common approach is to properly simplify the original complex problem and/or reasonably revise the intractable formulations, and then solve the updated model using state- of- the- art solution frameworks and commercialoptimization solvers. Two types of direct decomposition algorithms, i.e., branch and bound and dynamic programming are two effective methods. Furthermore, the dual decomposition algorithm, which is represented by Lagrangian relaxation and column generation, is normally the best choice for the complicated and large scale problems. The future research should explore the timetabling problem with the consideration of many practical requirements (i.e., infrastructure maintenance) and time- dependent fares and ticket distributions. In addition, it is an interesting topic to address the train timetabling problem within network-wide applications. Finally, solution algorithms that combine the characteristics of problems and the advanced optimization technologies, and commercial software that is applicable to the actual operations, should be developed in the future. References | Related Articles | Metrics

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Review and Prospect of Dynamic Traffic Assignment Research LONG Jian-cheng, GUO Jia-qi 2021, 21(5): 125-138.  Abstract ( )   PDF (1294KB) ( )   Dynamic traffic assignment (DTA) theory is one of the most important technical foundations in intelligent transportation systems, and it is also one of the most active research fields in current transportation science. DTA models can be used in the wide areas of offline traffic planning, policy evaluation, and online intelligent transportation systems. This paper first reviews the development of DTA theory in the past 50 years, and summarizes the important theories and methods developed at different stages. Second, it introduces the two basic components of the DTA problems: travel choice principle and traffic flow propagation model. The two basic components are related through the travel time function (or impedance function). This paper also summarizes the major travel choice principles, the major traffic flow propagation models, the key traffic behaviors, and travel time functions considered in DTA problems. The classification of DTA problems is discussed in terms of traveler's travel choice content, mastery of traffic conditions, demand elasticity, travel decision time span, user class, and so on, and the differences among different types of DTA problems are compared and analyzed in detail. This paper further analyzes the major DTA models based on whether the time variable is continuous or not, and reveals the advantages and disadvantages of different types of DTA models. The main solution methods of DTA problems under different travel choice principles are introduced, and the convergence and efficiency of the solution methods are reviewed. In addition, the applications of the DTA model in transportation planning, transportation policy evaluation, traffic control and management, etc. are also outlined. At last, this paperproposes that DTA theory and methods might find breakthroughs in the following five aspects: (1) efficient calculation method of dynamic network loading model and well defined dynamic impedance function, (2) effective algorithms for solving DTA problems on large-scale transportation networks, (3) active-chain-based DTA models on super networks, (4) applications of DTA models for traffic management and control, and (5) DTA models and their applications under future intelligent connected environment References | Related Articles | Metrics

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A Review and Prospect of Urban Transportation Governance Policy HU Xiao-wei, BAO Jia-shuo, AN Shi 2021, 21(5): 139-147.  Abstract ( )   PDF (1354KB) ( )   Urban transportation governance is an important part of public governance. The modernization of the urban transportation governance system and governance ability plays an important role in enhancing the transportation systems in China, and also provides an important support to increase the competitiveness of cities and improve people's quality of life. With the development of Internet + , big data and sharing economy, traditional urban transportation governance policy and mode can no longer meet the needs of rapid urban transportation development. The advance of new technologies has brought both opportunities and challenges to improve the urban transportation governance ability. This paper systematically summarizes the connotation and goals of urban transportation governance, policy decisionmaking methods and policy evaluations. It reviews the evolution of urban transportation governance policy decisions from urban traffic management and public participation to urban transportation governance modernization, and then forecasts the transformation of urban transportation governance mode in the new era. The methods used for evaluating the urban transportation governance policy are also reviewed. The study reveals the trend of urban transportation governance policy research in China: the first trend is to analyze the needs from different participants and stakeholders in urban transportation governance, and to explore the dynamic mechanism when multiple participants involved in urban transportation governance as well as the interaction and coupling among different participants; the second is to explore the temporal and spatial dynamic evolution and governance model of urban transportation, and to analyze thetravel decision- making behavior and evolution mechanism with intelligent transportation information; the third is to establish integrated platform for urban transportation governance to quickly and efficiently integrate the opinions of different participants and form value policy recommendations; the fourth is to establish urban transportation governance policy simulation and evaluation model, quantitatively evaluate the implementation effects of urban transportation governance policies, such as the public's acceptance and satisfaction with the policies. References | Related Articles | Metrics

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Review of Car-following Behavior Analysis and Modeling Based on Trajectory Data TIAN Jun-fang, ZHU Chen-qiang, JIA Ning , MA Shou-feng 2021, 21(5): 148-159.  Abstract ( )   PDF (1726KB) ( )   With the rapid development of trajectory collection technology and data analysis technology, more and more vehicle trajectories are collected and analyzed in traffic flow research. Vehicle trajectory data mainly includes the location and time of the vehicles, which can be used to calculate the driving behavior parameters, such as the speed, acceleration and space headway or time headway between the vehicle and vehicle in front. Through the analysis of trajectory data, the operation law of vehicles themselves, the interaction law between vehicles, the law of road environment on vehicles and the resulting macro and micro traffic flow phenomenon can be revealed, so the research of trajectory data has been paid more and more attention. The paper briefly reviews the history of trajectory data collection, introduces Next Generation SIMulation(NGSIM) data collected in natural scenes and Vehicle Platoon Data collected in experimental scenes, and combs the micro theoretical research based on the car- following trajectory in recent years. Firstly, the research work of key phenomena in traffic flow, such as traffic oscillation and traffic hysteresis, is analyzed; The research results of car-following behavior analysis are summarized, including asymmetric car-following behavior, the existence of stable car-following behavior, the memory effect, task difficulty, stochasticityand heterogeneity of car-following behavior; Then, the introduction of simulation models based on the above analysis results of car- following behavior is followed. Finally, from these three aspects, some discussions and prospects are made according to the research status: In the aspect of key phenomena of traffic flow, more data under different conditions should be collected, and more universal theories or models should be built to explain traffic flow phenomena; In the aspect of car- following behavior analysis, data mining technology or physiological and psychological theories can be used to quantify the car- following characteristics and physiological or psychological characteristics, and combine them to deeply analyze the mechanism of car- following behavior; In the aspect of simulation modeling, the physiological and psychological variables of drivers can be considered more in the future to make the model more humanized; At the same time, pay attention to the evaluation method of the model and the interpretation ability of the model to the empirical traffic flow. References | Related Articles | Metrics

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A Prospect of Reserved Transportation GUO Ji-fu , DIAO Jing-jing, XIAN Kai, WANG Qian 2021, 21(5): 160-164.  Abstract ( )   PDF (1333KB) ( )   In the urban transportation system, uneven distribution of supply and demand has caused many congestions before bottlenecks. Although everyone will ultimately pass the bottleneck, the congestion and queuing still generate additional waiting time. Ideally, if every traveler arrives at the bottleneck at the actual passing time, the waiting time in the queue can be transformed into the waiting time at home. The value of those two types of waiting time is significantly different in the generalized travel cost function. In a traditional transportation system, due to the lack of proper information guidance, travelers can only rely on queuing on the road to obtain the opportunity to pass the bottleneck at a certain time point. With the development of emerging technologies such as instant messaging and artificial intelligence, the technical methods can be used to arrange orders of passing bottlenecks for travelers in advance and inform travelers the estimated passing time. Travelers can immediately pass the bottlenecks instead of wait in the queue at the estimated time. Based on this, this article proposes a traffic organization mode of“reserved transportation”, that is, using innovative technologies and the notion of reservation to guide travelers to arrive at the time they can pass the bottlenecks. This mode transforms the queues at the roadway bottlenecks into virtual online queues. This research believes that the reserved transportation mode can alleviate the time- space dis-match between supply and demand to a certain extent, reduce queuing on the road under limited resource conditions, and improve the organization and management of future urban transportation system. References | Related Articles | Metrics

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Reduction Benefits and Mechanism of Pollutant Emissions from Civil Aircraft Based on Point Merge System HU Rong, FENG Hui-lin, LIU Bo-wen, ZHANG Jun-feng, WANG De-yun 2021, 21(5): 165-173.  Abstract ( )   PDF (2287KB) ( )   To investigate the environmental benefits and pollutant emission reduction mechanism of the point merge system, this study introduced the models of aircraft performance, fuel flow, and pollutant emission calculation under two different operational conditions for off-peak and peak time, and compared the five pollutants (i.e., HC, CO, NOX, SOX, and PM) of the civil aircraft between the point merge system (PMS) and the standard instrument approach procedure (STAR). The pollutant emissions and their reduction mechanism of PMS were also analyzed from three different views of flight time, fuel consumption, and pollutant emission indices. The study found that: for the off-peak condition, the total pollutant emissions of the PMS and STAR were 5.79 kg and 7.17 kg, respectively; the PMS can reduce about 19.25% of total pollutant emissions than STAR, and the emission reduction of NOX, SOX and PM was significant; for the peak condition, the total pollutant emissions of the PMS and STAR were 290.01 kg and 406.69 kg, respectively; the PMS can reduce about 28.69% of total pollutant emissions than STAR, and the NOX emission reduction ratio can reach as high as 48.32%. The results show that the PMS has positive environmental benefits and can effectively reduce the total pollutant emissions; especially for NOX emission reduction; shorter flight time and lower fuel-flow rate are the key driving factors for the pollutant emission reduction of the PMS. References | Related Articles | Metrics

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Passenger Cars Driving Behaviors Recognition Under Truck Movement Interruption JI Xiao-feng, LU Meng-yuan, QIN Wen-wen 2021, 21(5): 174-182.  Abstract ( )   PDF (2406KB) ( )   To identify passenger car driving behaviors under truck movement interruption on mountainous two-lane highways, this paper collected vehicle trajectory data from an unmanned aerial vehicle (UAV) video films and image processing afterwards. The car- following behavior, lane- change behavior and overtaking behavior of passenger cars were calibrated with the threshold criteria of passenger car headway and slope of lateral position curve. To obtain the recognition model input variables, Kruskal Wallis Test and Principal Component Analysis were used to filter and reduce the dimensionality of passenger car driving behavior parameters. A passenger car driving behaviors recognition model based on Support Vector Machine (SVM) was developed using the grid search algorithm to determine the optimal combination of parameters for the kernel function. The study also analyzed the characteristics of passenger cars driving behaviors under truck movement interruption in multiple dimensions, then trained and tested the recognition model taking a typical mountainous two-lane highway in Yunnan Province as an example. The results indicate that: (1) the passenger car speed under truck movement interruption is lower than that under the free flow condition, the speed decrease is about 20 to 30 km·h-1 . (2) The average headway of a passenger car following a truck on two-lane highway in mountainous area is 2.53 s, which is less than the prescribed minimum safe headway and significantly increases the risk of the following behavior. (3) The recognition accuracy of the proposed model is up to 98.41%, which shows good recognition ability and applicability References | Related Articles | Metrics

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Pricing and Investment Strategies for Electric Vehicle Battery Charging and Swapping XU Su-xiu , XIE Bing , QIN Wei, CHENG Hui-bing 2021, 21(5): 183-189.  Abstract ( )   PDF (1462KB) ( )   Considering different preferences of consumers on battery charging and swapping modes, this paper develops a tripartite game model from the perspective of electric vehicle manufacturers and a third-party investor of the battery-swapping stations. The mechanism of electricity price and investment decisions is revealed. Three decision variables are incorporated into a three-level Stackelberg model which include the investment level and two types of prices. The optimal pricing and investment strategies can then be obtained through the proposed model. The sensitivity analysis is also performed on the optimal pricing and investment strategy factors that affect the electric vehicle market demand and the battery-swapping modes. The study also investigates the impact of the cooperation mode between a manufacturer and a third-party investor of the battery-swapping stations on the optimal pricing and investment strategies. The results indicate that the cooperation of a manufacturer and a third-party investor would reduce the profit of their competitor (for example, the manufacturer of charging electric vehicles). When there is no cooperation established between a manufacturer and a third-party investor, the investment and constructions would be affected by the profit-sharing ratio of the battery-swapping mode, which causes the underinvestment or overinvestment problems. References | Related Articles | Metrics

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Impacts of COVID-19 Traffic Control Policy on Population Flows in Changsha YAN Chang-xin , WANG Bin , CHEN Li, XIANG Wang , WANG Yun , YAN Xue-dong 2021, 21(5): 190-197.  Abstract ( )   PDF (1973KB) ( )   To investigate the impact of COVID-19 traffic control policies on population flow in Changsha, this paper divided the prevention and traffic control policies into different stages corresponding to the real-time epidemic situation in Changsha. Based on Baidu migration big data, the difference- in- difference model was used to identify different stages of traffic prevention and control policies and quantify the effect of prevention. With the traffic control policy implemented during COVID- 19, the average inflow intensity of Changsha City decreased by 83.68% , the average outflow intensity decreased by 69.24% and the internal travel intensity respectively, decreased by 59.74%. After the end of the traffic control policies, the population flow intensity of Changsha City gradually rebounded, and the urban internal travel intensity basically recovered to the same level as in 2019. The results indicated the effectiveness of the traffic control policies on the limitation of population flow and epidemic spread. The results also provide reference for making effective prevention and control policies for the normalized COVID-19 epidemic situations. References | Related Articles | Metrics

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Evaluation and Optimal Recovery Strategy of Metro Network Service Resilience LV Biao , GUAN Xin-yi, GAO Zi-qiang 2021, 21(5): 198-205.  Abstract ( )   PDF (1958KB) ( )   Since the existing network resilience indexes based on topological efficiency cannot reflect the actual metro operation situations, a novel index of metro network service efficiency considering the influence of line flows, an index of metro network service resilience based on service efficiency, and an index of node importance based on metro network service efficiency were constructed. An optimization model was proposed to maximize the metro network service resilience, and then an optimal recovery strategy was obtained by solving the model using a genetic algorithm. The results show that the recovery orders of failure nodes are different by taking service efficiency and topological efficiency as metro network performance index respectively. Under the deliberate attack, the network service resilience obtained by the optimal recovery strategy is 16.76%, 72.11%, and 86.21% higher than the priority recovery strategy based on node importance, the priority recovery strategy based on node degree, and the random recovery strategy, respectively. The above results indicate that the network performance indexes and the recovery strategies should be selected reasonably according to the actual metro operation situations. Otherwise, the suboptimal or even worse schemes which significantly deviate from the actual situations may be obtained, and thus the expected goals cannot be achieved. References | Related Articles | Metrics

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Passenger Flow Assignment Method for Common-line Operation with Multi-routing of Urban Rail Transit XU De-jie , GONG Liang, ZHU Ning , WANG Xue-xin 2021, 21(5): 206-213.  Abstract ( )   PDF (1920KB) ( )   The passenger flow assignment for common-line operation mode with multi-routing is the basis of complex routing design and train plan optimization of urban rail transit. Taking the typical common-line operation with multirouting as an example, this paper analyzes the passenger trip routing and develops a passenger flow assignment model. In the analysis, the passengers are classified into different types based on the passenger trip space distributions. The path choice optimal strategies are then analyzed for different types of the passengers. The paper also proposes the calculation methods of passengers' share ratios based on the frequencies of multiple routings, and presents the frequency-based passenger assignment method. The multi-routing common-line physical network is transformed into a common-line service network. By introducing the concept of hyperpath, this paper converts the optimal strategy problem into the shortest hyperpath problem in the common-line operation service network. The passenger flow incremental assignment method is also proposed with consideration of the passengers' perception cost of crowding. The case study verifies the effectiveness of the passenger flow assignment method, and compares the applicability and property of two passenger flow assignment methods. References | Related Articles | Metrics

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A Nonlinear Dynamic Model for Evolution of Road Traffic System WANG Peng-fei , ZHU Jun-ze , WANG An-ge , LIU Peng , LI Meng , XU Qiu-shi 2021, 21(5): 214-221.  Abstract ( )   PDF (1705KB) ( )   This study investigates the effect of various planning, management policies and advanced technologies on road traffic system. A three-dimensional nonlinear dynamic model is constructed to depict the dynamic evolutions of energy storage consumption, vehicle ownership and roadway area. The study analyzes the existence, uniqueness and stability of the equilibrium solution of the dynamic model, and verifies the correctness of the theoretical results through numerical experiments. The results indicate that: the equilibrium solution which has practical significance is unique and stable if all variables and parameters are strictly positive; the equilibrium average vehicle traveling speed increases when meet one of the following conditions : growth rate of energy available for vehicles decreases, the town development boundary, supply quantity of shared parking lots, or the average energy consumption of vehicles increases; when a certain condition is satisfied, the equilibrium average vehicle speed increases with the conversion coefficient between network area and road network capacity; there exists an optimal intensity of traffic volume, which could make the equilibrium road network reach its minimum saturation. References | Related Articles | Metrics

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Urban Traffic Congestion Mitigation and Optimization Study Based on Two-level Programming HU Li-wei, ZHAO Xue-ting, YANG Jin-qing, ZHANG Su-hang, FAN Zi-jian, YIN Xiu-fen, GUO Zhi 2021, 21(5): 222-227.  Abstract ( )   PDF (1446KB) ( )   This paper focuses on the traffic zoning and traffic congestion optimization in urban road network under regional signal control. The factors that determines the traffic zones under congestions are identified and a model is proposed to describe the correlation degree of adjacent intersections. The congestion control sub-area is divided into “evacuation zone”and“balance zone”. Considering the different optimization objectives for“evacuation zone”and “balance zone”, the paper develops a bi-level optimal programming model for urban road network congestion mitigation. Taking some part of the road networks in Kunming city as an example, the paper compares the effectiveness of the actual control scheme and the proposed model through simulations. The results show that the proposed model performs well in the congestion control, except two optimization schemes on the average number of stops. The average vehicle delay time is reduced by 7.7 s, the proportion of severely congested mileage is reduced by 10.1% , and the vehicle occupancy in the network decreases 14.1%. The model has good effectiveness and can provide references for road network traffic congestion zoning and mitigation. References | Related Articles | Metrics

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Classification of Subway Stations Based on Land Use and Passenger Flow Characteristics YANG Jing , WU Ke , ZHANG Hong-liang , DAI Sheng-xu , WANG Yi-le 2021, 21(5): 228-234.  Abstract ( )   PDF (1610KB) ( )   This paper studies the fine classification of subway stations. In this paper, we use a commuter trip identification method based on trip chain analysis to identify the commuter passenger flow, then analyze the jobhousing characteristics of stations with the inbound and outbound passenger flow volume in the morning and evening peak. The point of interest (POI) data captured from the open-source platform of the Baidu map is classified according to the land use function to explore the built-up environment characteristics around the stations. Combined with the two types of characteristics, a subway station classification model based on the unsupervised learning k-means++ method is established, and 307 stations of Beijing subway are divided into 7 categories. According to the characteristics of passenger flow and surrounding land use, the stations are classified as the typical residential station with welldeveloped supporting facilities, the typical residential station with commercial development potential, the residential station configuring certain jobs, the highly developed typical working station, the working station combined with work and housing, the tourist and leisure station and the outer suburban station to be developed. The classification results are highly consistent with the actual situation, which verifies the effectiveness of the model, and can provide the basis for city planning and land development around the station. References | Related Articles | Metrics