Responsible Institution:The Ministry of Education of the People's Republic of China (MOE)
Sponsor:ChangAn University
Publisher:Editorial Department of Journal of Traffic and Transportation Engineering
Chief Editor:Aimin SHA
Address: Editorial Department of Journal of Traffic and Transportation Engineering, Chang 'an University, Middle Section of South Second Ring Road, Xi 'an, Shaanxi
Abstract: The National Natural Science Foundation of China (NSFC) has actively promoted its reform, and has developed the technology and science sector. According to the essential requirements and main economic challenges of China, the NSFC has attempted to solve the underlying core technical and scientific problems and has stimulated the scientific research. As an important part of NSFC's technology sector, the transportation and vehicle engineering discipline should seriously and proactively respond to the NFSC targets and adjust to its funding policy in the discipline in a timely manner. Transportation and vehicle engineering studies are demand-driven and future-oriented. They integrate various types of technology and bring different fields together. In this study, the differences between transportation elements of different transportation systems and their uniqueness were analyzed from the perspective of "small discipline, large industry" to avoid blind sorting of the so-called "common scientific problems" of industry and applications. The development of an engineering science and engineering technology evaluation system based on RAMS theory, i.e., reliability, availability, maintainability, and safety, was proposed. The characteristics of each transportation system and the differences in their scientific bases were carefully examined to establish a selection method for key funding directions and feasible technical routes based on RAMS. In this way, the application of the proposed method can be boosted in project approval, application, evaluation, and post evaluation. The rapid and efficient transformation of scientific achievements can then be realized such that China can become a great transportation power. 8 refs.More>
Abstract: The high-speed railway of China is an important part of the development of the world high-speed railway. The development and rise of Chinese high-speed railway were reviewed from the historical perspective (the inevitability of human society development) and the global perspective (the continuation of the world high-speed railway development). The timeline of the world high-speed railway development was analyzed from a macro point of view and the encouragement of the four worldwide industrial revolutions to the major advances of transportation technology was expounded. It is pointed out that the development of the high-speed railway goes through four stages: ferment, exploration, mature and development. The United States first suggested building high-speed railway, but it is still in the ferment stage. The high-speed railways of Japan, France and Germany are in the exploration stage. Only the Chinese high-speed railway has entered a rapid development stage. Based on the great achievements of Chinese high-speed railway, this paper expounded the path of introduction, digestion, absorption, innovation, and independent innovation in the process of Chinese high-speed railway development. The significant achievements have been made, on one hand, on the policy level, mainly due to Chinese efforts of taking the high-speed railway exploration experience of other countries and Chinese governmental ability of concentrating resources to accomplish large projects, integrating the advantages of enterprises, universities, and research institutes, and creating a national rail transit technology innovation system. On the other hand, from a technical perspective, the main reason of Chinese great achievements in high-speed railway lies in three important breakthroughs, which are technical breakthrough, theoretical breakthrough, and experimental breakthrough. The technical challenges faced by the development of high-speed railway and the research progress of key technologies of high-speed railway were discussed. The directions of the development of wheel-rail based high-speed transit and high-speed maglev in the post high-speed railway era were prospected, and the future development concepts of digital, intelligent, and smart high-speed railways were proposed so as to provide a reference for the future development of Chinese high-speed railway and to help to realize the great dream of building a great nation with modern transportation. 2 tabs, 25 figs, 40 refs.More>
Abstract: To comprehensively review the research progress in customized bus route optimization, the relevant literatures were classified and analyzed from three aspects including optimization objective, issue scenario, and solution algorithm. Analysis results show that researches on the single-objective optimization of customized bus routes have mainly focused on the travel time, operating mileage, operating cost, operating revenue, and total system cost formed by the linear weighting of multiple costs. However, research on the multi-objective optimization was mainly achieved by simultaneously considering two or three objectives, including the operating cost, travel cost, and service quality. According to the number of departure and arrival stations, the issue scenarios of customized bus route optimization problems can be divided into three types including one-to-one, many-to-one, and many-to-many. Research on the time impedance scenarios between different stops mainly focuses on the static time impedance, and less on the dynamic time impedance. Research on the scenario of travel demand mainly focuses on the static travel demand, and two-stage optimization strategies are generally used to solve dynamic travel demand scenarios. Since the route optimization problem of customized public transportation is a special vehicle route optimization problem, the precise solution algorithm is suitable for the analysis of small travel demand. For the practical problem of large-scale travel demand, the heuristic intelligent algorithm is generally used. In future studies, the optimization of customized bus routes needs to consider the influence of the parking yard settings, stop selection, and formulate particular time window attributes for different types of travelers. Besides, in the context of a big data environment, how to take into account real-time travel demand and operating cost constraints and provide differentiated customized bus routes will also be a challenging research direction. 5 tabs, 6 figs, 61 refs.More>
Abstract: The pyrolysis combustion mechanism of asphalt material was analyzed, and the test methods for flame-retardant and smoke-suppression performance of asphalt materials were concluded. The types, advantages, and disadvantages of commonly used asphalt flame retardants in domestic and overseas were investigated. The commonly used flame-retardant technologies of tunnel asphalt materials were studied, and the flame-retardant and smoke-suppression mechanism of nano-modified asphalt was evaluated. The influence of nano-clay on the road performance of asphalt materials was examined in terms of the high- and low-temperature performances, moisture stability, and aging performance. Moreover, the future research directions for flame-retardant and smoke-suppression asphalt materials for tunnels were assessed. Research results show that the flame retardant used in tunnel asphalt materials should have high synergistic flame-retardant and smoke-suppression effects, and the metal hydroxide and nano materials have great application potential. The flame-retardant and smoke-suppression performance testing of asphalt materials mainly includes polymer flame-retardant test methods, but these methods are inconsistent with the actual combustion state of asphalt pavement. Therefore, it is necessary to supplement the flame-retardant and smoke-suppression performance test methods and standards for asphalt materials. Nano-modified materials, such as the nano clay, significantly inhibit the smoke release of hot asphalt. However, current research mainly focuses on the flame-retardant mechanism of nano-materials and polymers, and there is a lack of systematic research on the flame-retardant and smoke-suppression mechanism of nano-modified asphalt. Nano clay significantly improves the high-temperature, moisture stability, and aging performances of asphalt, but there is controversy in the study of low-temperature performance in domestic and overseas. Investigating the technology for the smoke control of hot mix asphalt mixture, metal hydroxide and nano-clay synergistic flame-retardant technology, and flame-retardant performance test methods for asphalt materials should be the focuses of future research on tunnel flame-retardant and smoke-suppression asphalt materials. 3 tabs, 8 figs, 144 refs.More>
Abstract: Taking the slab ballastless track in the frost heaving area of the Harbin-Dalian High-Speed Railway subgrade as the research object, the deterioration laws of materials properties under freezing-thawing cycles were investigated through the axial compression and splitting tensile failure tests on the standard cubic specimens of C60, C40 concrete and mortar under rapid freezing-thawing cycles. On this basis, a spatial finite element model was established for a CRTS Ⅰ slab ballastless track-subgrade frost heaving and freezing-thawing, considering the limit retaining boss, ring-shaped resin and interlayer bonding contact properties. The static properties of tracks after the freezing-thawing damage were studied, and the stress states and damage characteristics of the base plate were revealed. Research results demonstrate that the use of high strength grade concrete considerably decelerates the material deterioration and erosion due to the freezing-thawing cycle. Intense freezing-thawing cycles remarkably deteriorate the contact state of the structural interface. As the number of freezing-thawing cycle increases, the materials properties of mortar layer and base plate worsen significantly, their elastic moduli, interlayer bonding strengths, and axial tensile strengths decrease substantially. The peak compressive strengths of C60, C40 concrete and mortar decrease by 14.7%, 34.6%, and 29.9%, respectively, after 300 freezing-thawing cycles compared to those without any freezing-thawing cycles. The axial tensile strength of cementation interface between the C60 concrete and the mortar decreases by 90.6%. The axial tensile strengths of C60, C40 concrete and mortar decrease by more than 56%. Under the typical frost heaving condition (the frost heaving wave length is 10 m, and the frost heaving peak is 8 mm), the maximum tensile stress is observed at the upper surfaces of all structural layers of the track at the frost heaving center, whereas the maximum compressive stress is observed at the foot of the frost heaving wave. As the number of freezing-thawing cycle increases, the maximum tensile stresses of track slab and base plate also increase. Hence, when designing slab ballastless tracks in cold areas, the base plate is the main control component, and the frost heaving in the middle of the base plate is a highly unfavorable condition. 6 tabs, 11 figs, 32 refs.More>
Abstract: A tracking test was conducted to evaluate the damage development and stiffness evolution of the elastic iron plate of high-speed turnouts. Based on the measured data, a vehicle-turnout coupling dynamics calculation model was established, and the influence of stiffness deterioration of the elastic iron plate on the vehicle-turnout dynamic characteristics was analyzed. The adaptability of high-speed turnout to the further increase of operation speed under deteriorated stiffness was studied. Analysis results show that with the long-term use of the elastic iron plate of high-speed turnout, a series of damages appear, including rubber aging, cracking, separation, falling off, and rusting of iron components. For both the ballast and ballastless turnouts, the ratios of dynamic stiffness to static stiffness of iron plates change slightly, whereas the static stiffnesses increase. The static stiffness of the iron plate of ballast turnout shows evident changes at the initial stage, and the growing rate can exceed 60% after 3 years of service. The static stiffness of the iron plate of the ballastless turnout in the general area can increase maximum by 30%. The stiffness change is smaller than that of the ballast turnout. The static stiffness of the iron plate of the ballastless turnout changes rapidly in the cold, windy, and sandy areas. The gradual stiffness deterioration of the elastic iron plate of high-speed turnout has an effect on the dynamic performances. Under stiffness deterioration, the rail deformations in the turnout zone decrease, the wheel-rail dynamic interactions increase, and the safety parameters increase. The moving trajectories of the vehicle and wheelset are basically unchanged, but the vibration of both the wheelset and vehicle intensifies. Under stiffness deterioration of the elastic iron plate of the high-speed turnout, the increase in operation speed leads to further deterioration of the vehicle-turnout system dynamic performances, and the margins of safety and fatigue further reduce. The stiffness deterioration reduces the adaptability of the high-speed turnout to the speed increase. To expand the scope of raising speed, the stiffness deterioration of the elastic iron plate in the turnout zone should be considered. Some elastic iron plates should be replaced appropriately to ensure the running safety and stability. 2 tabs, 9 figs, 30 refs.More>
Abstract: Combined with vehicle-mounted laser profiler and global navigation satellite mobile positioning system, a method for measuring the all-wave roughness of an airport runway was proposed. The on-situ test was carried out at Jinan Yaoqiang International Airport, and the repeat test and level were used to verify the reliability of this measurement method. A virtual prototype model of B737-800 was built using ADAMS/Aircraft software, and the simulation of aircraft taxiing under the measured runway roughness data was carried out. The influence of the measured data characteristics of the runway under different measuring methods, taxiing speeds, and aircraft positions on the aircraft vibration responses was explored. Research results show that the proposed measuring method can obtain all-wave runway roughness data, which makes up for the defect that the laser profiler is unable to capture wavelengths of above 14 m. When the speed is 80 km·h-1, the fluctuant amplitudes of aircraft vibration responses under all-wave roughness runway are 1.25-2.39 and 1.19-1.85 times that under a long-wave roughness and short-wave roughness, respectively, indicating that aircraft vibration responses under the real runway roughness may be underestimated if only considering long-wave roughness or short-wave roughness. With the increase of aircraft taxiing speed, the differences of aircraft vibration acceleration increase gradually under the all-wave roughness and short-wave roughness. While the differences of dynamic load coefficients first increase and then decrease, and reaching the maximum at the speed of 160 km·h-1, indicating that the effect of long-wave roughness on the runway is more obvious during high-speed taxiing. Compared with the short-wave roughness condition, the increase of cockpit acceleration under all-wave roughness is 0.062 m·s-2 higher than that at the center of gravity on average, and the increase of dynamic load coefficient of nose landing gear is 0.039 higher than that of the main landing gear on average, which shows the effect of long-wave roughness on the vibration in the front part of aircraft is greater than that in the center part of aircraft. In addition, with the increase of taxiing speed, the differences first increase and then decrease. The difference of acceleration is most obvious at speeds between 80-120 km·h-1 with the peak at around 0.078 m·s-2, while the peak of difference of dynamic load coefficient is 0.062 at the speed of 160 km·h-1. 2 tabs, 12 figs, 30 refs.More>
Abstract: Focusing on the evaluation indexes of the low temperature performance of asphalt binders, based on rheological bending beam rheometer (BBR) and extended bending beam rheometer (EBBR) tests, the low temperature rheological properties of the extracted asphalt, aging base asphalt and modified asphalt on actual pavements were analyzed. The low temperature performance evaluations of the asphalts were carried out using the traditional stiffness modulus and modulus changing rate. The equivalent low temperature design temperature index and the temperature difference value index were proposed. Simulations in different curing environments were conducted, and the influencing factors of physical hardening of newly prepared and extracted asphalt at low temperature were studied using low temperature grade loss index. Different sources and types of asphalt test results were used to verify each other, the above indexes were compared and analyzed in terms of anti-interference ability, stability, evaluation accuracy, intuitiveness, and difficulty in obtaining indexes. The abilities of four indexes in distinguishing and evaluating the low temperature performance of asphalt were established. Research results show that the laboratory rheological analysis of the extracted asphalt can reflect the low temperature crack resistance level of the pavement structure. The modulus of the asphalt in the severely cracked section is significantly higher than those in the other sections, and the value difference can reach about 130 MPa. The newly prepared SBS modified asphalt and the extracted asphalt have a high consistency at low temperature loads, and the modulus deviation is lower than 15%. It can effectively establishes the relationship between laboratory research and actual pavement disease treatment needs. The stability of traditional index data is weak, and the confidence is only 64.7%-82.3%, which is difficult to satisfy the research needs. The applications of temperature difference value index and low temperature grade loss index is also restricted, which still needs more in-depth research. 4 tabs, 10 figs, 32 refs.More>
Abstract: To quantitatively evaluate the creep characteristics of asphalt mixtures, the mechanisms associated with both creep hardening and creep damage and deterioration throughout the creep process of asphalt mixtures were considered. Based on the fractional calculus theory, a relatively simple fractional creep damage model was developed. In this model, a fractional Maxwell model was used to describe the creep hardening mechanism, and the damage strain was used to represent the creep damage and deterioration mechanism. In addition, a damage evolution equation for asphalt mixtures was statistically derived. Uniaxial compressive creep tests were performed on AC-13 asphalt mixtures at different stress levels (0.179, 0.358, 0.448, 0.537, and 0.716 MPa). The nonlinear fitting was carried out using the Levenberg-Marquardt optimization algorithm to determine the parameters of fractional creep damage model as well as the damage evolution curves at different stress levels. To construct a unified damage evolution model for different stress levels, a method to statistically quantify the damage evolution of asphalt mixtures was proposed, and the evolution relationship between the creep damage and the damage strain was established. Research results show that the determination coefficients between the proposed fractional creep damage model results and the test results at different stress levels are all not less than 0.995, indicating that the proposed model is suitable for describing the entire creep process including the decay, stable, and accelerated creep stages. In the decay creep stage, the damage of asphalt mixture at different stress levels is less than 1.0×10-3 and is negligible compared to the damage (0.8) at creep failure. In the stable creep stage, the damage gradually increases. Eventually, the asphalt mixture undergoes creep failure when the creep stress exceeds a certain value. The flow time depends on the applied stress level. The determination coefficient of evolution relationship between the creep damage and the damage strain fitted by the two-parameter Weibull distribution function is 0.992. This indicates that one damage evolution model can be developed for different stress levels. Its parameters are only related to material properties and temperature and are independent of the applied stress. 2 tabs, 10 figs, 32 refs.More>
Abstract: Aiming at the train tail lateral sway of 160 km·h-1 electric multiple units (EMUs), which occurs in single-track tunnels, the mechanism was put forward that the vortex shedding effect of gas flow in the train tail causes the vortex-induced vibration of the car-body and results in the lateral sway of the train tail. Relevant mitigation measures, such as the optimization of vehicle suspension parameters, were studied. Based on the structural parameters of a certain type of locomotive, the vehicle lateral dynamics model was established and combined with the semi-empirical nonlinear vortex-induced vibrator model to enable the fluid-solid coupling lateral dynamics calculation during the vortex-induced vibration. Calculation results show that a large lateral vortex-induced force acting on the train tail of EMUs in a single-track tunnel and the resonance between the vortex-induced frequency and the car-body hunting frequency are the main causes of car-body sway. Reducing the lateral vortex-induced force and improving the vehicle hunting stability are effective measures to reduce the amplitude of the car-body sway. For this type of locomotive, avoiding wheel-rail contact with a lower equivalent conicity is required to prevent aggravation of the vortex-induced vibration by vehicle primary hunting behavior. When the damping of the yaw damper is reduced from 800 kN·s·m-1 to 400 kN·s·m-1, the lateral vibration acceleration amplitude in the rear end of the car-body during vortex-induced resonance is reduced by 40%. When the semi-active control with skyhook damping in the secondary lateral suspension is adopted, the lateral vibration amplitude of the car-body in the vortex-induced resonance zone is effectively reduced. Moreover, the lateral ride comfort at the front and rear ends of the car-body can be guaranteed. 1 tab, 9 figs, 29 refs.More>
Abstract: A dynamics model of a variable gauge bogie motor car (MC) for body suspension motor high-speed electric multiple units (EMUs), which was suitable for 1 435/1 000 mm gauge changes, was established. The bifurcation characteristics of the running stability of the motor car under different wheel-rail matching relations and different wear conditions were calculated on two gauge lines, and the effects of the track gauge and clearance between the wheel flange and gauge line on running stability were calculated. The vertical and lateral stationarities of the vehicle operation and the curve-passing performance of the vehicle under different curve conditions were calculated. The dynamics performance indexes were evaluated in combination with relevant dynamics standards, and the reasons for the differences in the dynamics indexes were briefly analyzed. Twelve suspension parameters of the variable gauge bogie MC with a body suspension motor were taken as factors, five dynamic indexes, including vehicle hunting instability speed, wheel-axle lateral force, wheel-rail vertical force, wheel load reduction rate, and derailment coefficient, were taken as responses. Moreover, the optimal Latin hypercube design method was used for the experimental design. A radial basis function neural network agent model was established and the main suspension parameters of the vehicle were optimized using the NSGA-Ⅱ multi-objective genetic algorithm. Calculation results show that the running stability, stationarity, and curve passing performance of the designed high-speed EMU variable gauge bogie on two gauge lines meets the design requirements under the design conditions. The running stability on the 1 000 mm gauge is better than that of the 1 435 mm gauge, but the running stationarity and curve passing performance are inferior to those of the 1 435 mm gauge. As the optimized suspension parameters consider the running stability, stationarity, and curve passing performance of the vehicle, the vehicle exhibits a better dynamic performance. All the calculated performance indexes meet the relevant standards in the operation of the two gauge lines. 10 tabs, 13 figs, 31 refs.More>
Abstract: To achieve the lightweight design of high-speed trains, the unique inner supporting structures and load-bearing characteristics of inner journal high-speed railway axles were analyzed, and a theoretical model to study both the load-bearing status and structural strength was established for the inner journal high-speed railway axle. An analytical calculation method was proposed to calculate the design limit load and fatigue strength for the inner journal high-speed railway axle. Based on the presented methods, theoretical analysis, finite element method, and vehicle system dynamics, a structural design method was developed for inner journal high-speed railway axles. Further, an inner journal high-speed railway axle with a 17-t axle load was used as a case study to carry out the application research. The critical safety section and detailed dimension scheme of the axle were determined using the theoretical load-bearing analysis results of the inner journal high-speed railway axle. A finite element model for the inner journal high-speed railway axle was established, and the fatigue strength of the axle was evaluated and verified. A rigid-flexible coupled system dynamics simulation analysis model for the high-speed electric multiple unit (EMU) with inner journal axles was constructed. The dynamics properties of the vehicle and the dynamic loads of the axle were obtained and verified. Analysis results reveal that the weight of newly developed inner journal high-speed railway axle with a 17-t axle load is 273.6 kg, about 30% less than that of the traditional outer journal high-speed railway axle. The safety factor of fatigue strength for each section of inner journal high-speed railway axle is larger than 1.66. The critical safety sections are transferred to the bottom of relief groove between the journal and the wheel seat as well as to the arc-shaped transition zone between the journal and the axle body. The high-speed EMU with inner journal axles can stably pass through a curved route with a radius of 5.5 km at a speed of 350 km·h-1, and its main dynamics property indices are excellent. The dynamic loads borne by the axles under the selected curve passing conditions fall within the design limit loads. Therefore, it is robust enough to carry out the structural design and strength analysis for the axles. Thus, the inner journal high-speed railway axle shows significant technical advantages in achieving the lightweight design of high-speed trains with excellent high-speed adaptability. It has immense development and application potential in the field of high-speed trains. 2 tabs, 10 figs, 32 refs.More>
Abstract: The effects of adhesive and composite materials were decoupled. Adhesive, carbon fiber reinforced plastic (CFRP), and CFRP/aluminum alloy adhesive joints were immersed in water at room temperature for different durations, and the effect of different stress states on the failure of adhesive joints was investigated. Analysis of the failure strength and failure mode of the quasi-static failure test was the main method, combined with the chemical analysis of Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), and scanning electron microscopy (SEM). The failure mechanisms of adhesive and CFRP after moisture absorption were studied, and the effect of moisture absorption on the failure mechanism of composite material adhesive joints was revealed. Analysis results show that the adhesive is hydrolyzed after 30 d moisture absorption, the failure strength decreases by approximately 53.7%, and the failure strain is approximately 3.2 times of the adhesive without moisture absorption. Interface failure of CFRP occurs because of the decrease in the adhesivity after moisture absorption, but it improves after polishing. The mechanical properties of the fiber/matrix interface decreases after moisture absorption, which caused the fiber tear of CFRP to be subjected to a normal stress state. The failure strength of CFRP/aluminum alloy adhesive joints decreases by approximately 23%, and ductile fracture and interface failure of the fracture surface of the adhesive occurs after moisture absorption for 30 d. Through the failure analysis of adhesive, CFRP, and CFRP/aluminum alloy adhesive joints after moisture absorption, it's determined that the failure of CFRP/aluminum alloy adhesive joints under shear stress is mainly affected by the performance reduction of the adhesive after moisture absorption, and the interface failure is the secondary cause. The failure of CFRP/aluminum alloy adhesive joints under normal stress is also influenced by the fiber tear of the CFRP owing to the performance reduction. 3 tabs, 20 figs, 30 refs.More>
Abstract: Under the condition of simple harmonic excitation, a simulation test device of shafting longitudinal vibration suppression based on the particle damping was used to investigate the vibration reduction ratio of particle damping in a rotating condition. The acceleration variations of shafting simulation system for single- and multiple-cavity particle dampers were explored, and the parameters influencing the vibration reduction ratio of the system, such as material, size and filling ratio of particle, cavity number, rotating speed, frequency, and amplitude of excitation, were examined. Research results show that when there are multiple particles in a single cavity, the vibration reduction ratio of a system filled with copper, steel, and rubber-coated steel particles is between 7.83% and 8.91%, and that of a system filled with rubber particles is close to zero. This indicates that copper, steel, and rubber-coated steel particles have an obvious suppression effect, and the higher the material density and damping ratio of the particles, the better the damping effect. When the particle mass filling ratio is 15%, the maximum vibration reduction ratio of the system is 13.77%. However, when the mass filling ratio exceeds 15%, the vibration damping ratio of the system decreases. Therefore, the mass filling ratio should be controlled at approximately 15% according to the actual situation. The influences of particle size, rotating speed, excitation frequency, and displacement amplitude on the vibration reduction ratio of the system are 1.76%-8.68%, 6.77%-12.50%, 4.41%-10.12%, and 2.19%-7.05%, respectively. Under a multicavity and multiparticle condition, when the total mass filling ratio of the particles and the rotating speed are constant, the cavity number has a significant impact on the vibration reduction ratio of the system. When the cavity number is 3, the best vibration reduction ratio of the system is 22.5% under a rotating speed of 100 r·min-1 and a mass filling ratio of 25%. Under multicavity and multiple particle sizes, when the total mass filling ratio is 10% and the rotating speed is 50-150 r·min-1, the vibration reduction ratio of the system fluctuates little, with an average of 14.18%. This shows that the combined multicavity and multiple-particle-size system is not very sensitive to the rotating speed, and it has a better vibration reduction effect. As a result, the range of the rotating speed can be widened. 14 tabs, 18 figs, 30 refs.More>
Abstract: To analysis the problems of equivalent inertia moment reduction, static and transient stabilities deterioration when a high-penetration grid-connected photovoltaic system was integrated into the ship power system, the first vehicle carrier transport ship ("COSCO Tengfei") integrated the grid-connected photovoltaic power system manufactured in China was taken as the research object. The simulation model of ship grid-connected photovoltaic power system was established according to the power load calculation and electrical system diagram of ship. A constant power control strategy was adopted for the photovoltaic grid-connected inverter, the differences in the calculation results of Newton-Raphson, XB fast decoupled, BX fast decoupled, Runge-Kutta, Iwanoto, and simple robust algorithm were discussed in terms of the system power flow analysis. A total of eight simulation examples were analyzed to discuss the static stability of system under different photovoltaic penetrations. The effects of continuous load and sequential launching of bow thruster on the transient stability of system were analysis during the photovoltaic grid-connected operation. Analysis results show that the Newton-Raphson method requires four iterations, the dynamic simulation time is only 10.4% of that needed by the Iwanoto algorithm, and the other six evaluation parameters for the Newton-Raphson method are consistent with the average results of various algorithms. So, the Newton-Raphson algorithm is the most suitable method to solve the power flows of strongly coupled rigid power systems. The total active and reactive system power losses increase as the photovoltaic penetration increases. Especially when the photovoltaic penetration exceeds 33.36%, the reactive power loss is 10 times the active power loss. When the dynamic load of the same magnitude as the power provided by the synchronous generator set is launched at a penetration of 21.32%, the transient power angle and voltage instability occur in the ship power system simultaneously. The grid-connected photovoltaic system can quickly compensate for the low-frequency oscillation in the ship power system, but it cannot play an effective role in maintaining or restoring the ship power system transient stability. 4 tabs, 10 figs, 30 refs.More>
Abstract: To estimate stopping activities of ships from massive trajectory data accurately, a two-stage strategy was established to extract stop points from ship trajectories, and an automatic characteristic-based ship stopping behavior recognition and classification method was also proposed. By taking the distance, time and number of points as the constraint conditions, a rule model was constructed to detect the candidate stop trajectories from the raw trajectories. The isolation forest algorithm was applied for the abnormal outliers detection and elimination. A set of highly clustered ship stop trajectories was extracted. Based on the spatio-temporal characteristics of ship berthing and anchoring. Three indices, including the repetition rate of trajectory point, mean distance between neighboring points, and distance between the farthest point pair, were defined to establish a new trajectory similarity measurement model. Then, the distribution characteristics and aggregation degree of ship stop trajectory points were quantitatively evaluated, and the K-nearest neighbor algorithm was then used to automatically classify the berthing and anchoring behaviors of ships. The proposed method was applied to the ship trajectory data collected from three different waters. The classification results of ship stopping behaviors were obtained accurately. The differences in spatio-temporal characteristics of ship anchoring and berthing were verified. The accuracies of recognition and classification of ship stopping behaviors were assessed with the help of manually annotated results. Research results indicate that the repetition rate of trajectory points for ship berthing is more than 80%. The distance between the furthest point pair and the mean distance between neighboring points are 6-11 and 1-2 m, respectively. The repetition rate of trajectory points for ship anchoring is less than 10%. The distance between the furthest point pair and the mean distance between neighboring points are 150-250 and 8-10 m, respectively. Thus, the three spatio-temporal characteristics, including the repetition rate of trajectory point, mean distance between neighboring points, and distance between the farthest point pair have a significant ability to distinguish the ship berthing and anchoring. The recognition and classification accuracy of the proposed method reaches up to 98%. Therefore, its effectiveness is fully proved. With the help of the proposed model, the spatial positions of existing docks and anchorages can be updated. Abnormal ship stops outside the regular waters or abnormal ship stops for prolonged periods inside the regular waters can be recognized automatically. The stopping distribution in ports can be monitored, and the popular docks and anchorages in different times and seasons can be known. In this way, the port planning layout and traffic organization can be optimized. 3 tabs, 7 figs, 31 refs.More>
Abstract: Based on ship automatic identification system (AIS) trajectories, static dissimilarity models, dynamic dissimilarity models, and a combined dissimilarity model of ship trajectories were constructed, including the following dissimilarity models: trajectory departure and destination, trajectory length, trajectory spatial distribution, trajectory mean speed, trajectory mean course, trajectory speed standard deviation, and trajectory course standard deviation. Trajectories were classified using the KNN classification algorithm, the effectivenesses and efficiencies of each single dissimilarity model were analyzed, the effect of trajectory classification under different unique dissimilarity models and the combined dissimilarity model were compared, and the influence of the categories and weights of dissimilarity models on trajectory classification in the combined dissimilarity model was studied. Experiments were conducted using ship trajectories in inland waterways and port waters. Experimental results show that under the condition of adopting a single dissimilarity, in terms of the classification effect, the ship trajectory classification based on the dissimilarity model of trajectory departure and destination and the dissimilarity model of trajectory mean course is better than that using other dissimilarity models in inland waterways and port waters, whereas the trajectory classification effect based on the dissimilarity model of trajectory mean speed and the dissimilarity model of trajectory speed standard deviation is worse. In terms of classification efficiency, the time consumed by the dissimilarity models based on mean value and standard deviation is significantly lower than that of the other dissimilarity models. Through the analysis and optimization of trajectory dissimilarity models based on the trajectory classification results of the KNN classification algorithm, when the trajectory classification is conducted using the combined dissimilarity model, macro and micro averages based on accuracy and recall of ship trajectory classification results in the inland waterway and port waters can both reach 99%; moreover, by increasing the number of dissimilarity categories in the combined dissimilarity from 4 to 7, the evaluation result of trajectory classification is further improved. Therefore, in the single dissimilarity model, the classification effects of the dissimilarity model of trajectory departure and destination, the dissimilarity model of trajectory mean course, and the dissimilarity model of trajectory spatial distribution are optimal and stable, whereas the time consumption of the dissimilarity model of trajectory spatial distribution and the dissimilarity model of trajectory length are significantly higher than those of other models. The adaptabilities of each dissimilarity are similar in different scenarios. By increasing the dissimilarity category in the combined dissimilarity model, the trajectory recognition effect can be improved. 3 tabs, 12 figs, 30 refs.More>
Abstract: To effectively solve the problem that it is difficult to automatically separate the standard flight, non-standard flight and anomalous flight patterns in high-traffic terminal areas, an aircraft trajectory clustering model was established based on the robust deep auto-encoder (RDAE) and clustering by fast search and find of density peaks (CFSFDP) using the widely recorded automatic dependent surveillance-broadcast (ADS-B) data. The RDAE was designed to reduce the dimensionality and extract nonlinear features from the aircraft trajectory dataset of terminal areas, while various regularization methods were adopted to constrain the internal low-dimensional manifolds to reconstruct a denser aircraft trajectory, and the aircraft trajectory was input to the CFSFDP algorithm. The silhouette coefficient was used to select the cluster centers for flight patterns with different densities and recognize anomalous trajectories by adjusting the edge density parameter. Two widely used aircraft trajectory clustering models, namely principal component analysis (PCA) combined with density-based spatial clustering of applications with noise (DBSCAN) as well as dynamic time wrapping (DTW) combined with DBSCAN, were taken as comparisons. Experiments were conducted on a small data of 1 d and a large data of 45 d of Guangzhou Baiyun Airport. Analysis results demonstrate that the model combining DTW and CFSFDP provides the best aircraft trajectory clustering performance on the small data, and the silhouette coefficient is 62% and 28% higher than those of comparisons, respectively. The DTW/CFSFDP model can automatically recognize standard flights following the area navigation procedures and non-standard flights that reflect controllers' preferences in specific environments, and the accuracies for identifying anomalous aircraft trajectories also improve by 57% and 10%, respectively. For the large data, the clustering performance of the proposed RDAE/CFSFDP model improves by 13% compared to that of the classical PCA/DBSCAN algorithm. Further, the proposed model exhibits acceptable time complexity. In summary, the established flight pattern discrimination model for terminal areas can provide a data extraction platform for the airspace-level traffic flow performance evaluation and the flight-level aircraft trajectory prediction and optimization. 2 tabs, 10 figs, 31 refs.More>
Abstract: In order to quickly relieve the large passenger flow of stations on urban rail transit lines and reduce the total waiting time of passengers, the problem of standby train deployment was studied. Based on the consideration of train tracking relationship, train dwelling time, and other constraints, a multi-objective optimization model was established to determine the timing of standby train deployment, select the best station, and dynamically adjust the schedule. The conditions for the deployment of standby trains were defined and a quantitative determination method for the timing of the standby train operation was proposed. A 0-1 variable was used to characterize whether the station was equipped for standby trains, and it was used as the model input. Then, a mixed integer nonlinear programming (MINP) model of standby train deployment was established to minimize the waiting time of passengers at the station with large passenger flow, and the deviation time (delay time) of the timetable was constructed. The model compared the efficiency of different standby train deployment schemes to get the best standby train deployment station and the subsequent operation plan. An improved particle swarm optimization algorithm with a penalty function was designed to deal with the 0-1 variable and continuous variables simultaneously. Research results show that the method can make plans for all stations satisfying the conditions of standby train deployment, and further select the best standby train stations from the alternative stations. The maximum total passenger waiting time reduces by 1 318 209 s, and the optimization efficiency reduces about 21.9%. Moreover, the improved particle swarm optimization algorithm has good applicability to the MINP model. Compared to the existing urban rail line train operation adjustment and schedule optimization methods, the proposed method provides a more quantitative judgment on the timing of the standby train deployment in response to large passenger flow situations. It provides the evacuation capacity and efficiency of stations with large passenger flow stations and optimizes the operation plans of the standby and subsequent trains. The problem of large passenger flows at stations during peak hours can be relieve effectively. 4 tabs, 9 figs, 30 refs.More>
Abstract: Under practical demand of partitioning for large-scale urban road traffic networks, a comprehensive index that measures the similarity of traffic flow time series was constructed based on the Pearson correlation coefficient and Euclidean distance which reflects the trend and describes the spatial relationships for time series. By incorporating the spatial-temporal similarity of the traffic flow time series, an improved static partitioning algorithm for road networks was designed using the normalized cut (NCut) algorithm under the spatial connectivity constraint for each subregion. To reflect the time-varying characteristics of road networks, reasonable cluster numbers during each time period was determined by selecting an appropriate evaluation criterion, and a dynamic partitioning algorithm of the road network based on NCut for the time series was proposed. By using the link traffic flow speed data collected within a region in the Northeast Second Ring of Beijing, the designed partitioning algorithms were applied to the road network covering 7.23 km2, and the partitioning performances during evening peak hours was compared. Analysis results indicate that the proposed partitioning algorithms can effectively distinguish the traffic conditions in different areas within the road network. Using the dynamic partitioning algorithm with a time interval of 30 min, the road network can be divided into several alterable subregions with time-varying cluster numbers and time-varying scopes. Compared to the static partitioning algorithm using fixed subregion numbers of 2, 3, 4, and 5, the evaluation criterion of the proposed dynamic partitioning algorithm increase by 63.77%, 50.06%, 6.43%, and 7.13%, respectively, and the partitioning performance for the road network improves. Therefore, the proposed dynamic partitioning algorithm can divide the heterogeneous road networks into a number of internally homogeneous subregions while the internal connectivity within each subregion is guaranteed, and can fully embody the spatial-temporal evolution characteristics of the traffic flow, and can benefit to formulating dynamical perimeter control scheme for multiple regions. 2 tabs, 8 figs, 30 refs.More>
Abstract: To realize the accurate prediction of the short-term passenger flow of rail transit and explore the changing mechanism of passenger flow under the station closure, a short-term spatio-temporal corrected passenger flow forecasting method considering dynamic factor model (DFM) and support vector machine (SVM) under the station closure was developed and denoted by DFM-SVM. A hybrid model combining symbolic aggregation approximation (SAX) and dynamic time warping (DTW) denoted by SAX-DTW was proposed to identify the spatio-temporal ranges of the affected stations. DFM was developed to forecast the short-term passenger flow under the normal scenario based on the historical data. SVM was developed to extract and process the nonlinear characteristics of the passenger flows at the affected stations and time periods and used to correct the correspondingly affected passenger flows. The validity of the method was verified by an example of the inbound volume prediction at the Beijing Subway Station under the station closure. Research results show that compared with the SAX, the proposed SAX-DFM not only comprehensively considers the changes in the number and trend of passenger flow, but also identifies the abnormal segments of several stations according to the case study more accurately. Compared with the traditional DFM, the proposed DFM-SVM can significantly reduce the forecasting residual errors of passenger flows at each station. Taking the Olympic Sports Center Station as an example, the residual error reduces by about 60%. In terms of overall passenger flow prediction of the whole stations, the proposed DFM-SVM reduces the root mean square errors by 43.39%, 70.00%, 33.18% and 70.83%, respectively, and the mean absolute errors by 43.72%, 67.17%, 28.98% and 57.08%, respectively, compared with the baseline models such as Holt-Winters, SVM, gate recurrent unit (GRU), and long short-term memory (LSTM). In terms of the passenger volume prediction at a single station, the proposed DFM-SVM can reduce the root mean square errors and mean absolute errors at about 70% stations compared with other benchmark models. Therefore, the proposed DFM-SVM can capture the nonlinear feature of passenger flow affected by the station closure, which greatly improves the prediction accuracy and provides reliable passenger flow's early warning information and decision-making basis for operation managers. 4 tabs, 9 figs, 30 refs.More>
Abstract: To accurately analyze the trip characteristics and time-varying differences of different passenger flows of bus routes and stops, combined with deep learning theory, a bus passenger flow classification prediction model based on a combination of a convolutional neural network (CNN) and gated recurrent unit (GRU) was proposed. By integrating and matching multi-source data, such as bus card swiping, bus global positioning system (GPS) trajectory, route and station basic information, and weather data, bus passenger flow data was reconstructed. The K-medians algorithm was used to divide passengers into commuter and non-commuter categories. Taking the factors of passenger type, historical passenger flow, time period, high/flat peak, week, precipitation, and major events as input vectors, a single model of CNN and GRU was established, and forecasts were conducted using mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE) as evaluation indicators. As a single model is not suitable for multi-feature time series forecasting, line passenger flow and cross-section passenger flow prediction models combined with a CNN and GRU were constructed. Taking Beijing Special 15 Bus as an example, the classified passenger flows of routes and cross-sections under the scenarios of working days and non-working days were predicted. Analysis results show that for commuter and non-commuter routes and cross-section passenger flows, the MSEs of the combined model reduce by 57.932, 13.106, and 33.987 on average, the RMSEs reduce by 1.862, 1.058, and 1.538 on average, and the MAEs reduce by 1.399, 0.487, and 0.613 on average, respectively. Thus, the CNN-GRU combined model driven by multi-source data has a good prediction performance. 3 tabs, 7 figs, 36 refs.More>
Abstract: Using the advanced public transportation system (APTS) to extract individual passenger travel information, the bus trip-chain was constructed, and the method of bus passenger classification based on the spatial and temporal behavior regularity mining (STBRM) was examined. Time series were used to characterize the travel temporal characteristics of passengers, and the cross-correlation distance (CCD) algorithm was used to calculate the temporal regularity of individual passengers. The density-based spatial clustering of applications with noise (DBSCAN) algorithm was used to mine the travel spatial regularity of individual passengers. According to the travel intensity and spatial-temporal regularity, bus passengers were divided into five groups, including rare travel, regular time, regular space, regular space-time, and irregular. Taking the numbers of travel days, similar boarding times, and similar boarding bus stops as the clustering indexes, the K-means++ algorithm was applied to classify passengers into three categories, namely high regularity, medium regularity, and low regularity. The classification result of the proposed method was compared with the K-means++ clustering method, and the relationship between the two methods was revealed. Research results show that when the time division length is 5 min and the temporal regularity judgment threshold is 3.0, the CCD algorithm has the best identification effect of passengers with temporal shifted patterns. Compared with the DBSCAN algorithm, the recognition rate improves by 14.64%. Increasing the time window length can improve the stability of travel spatial and temporal regularity judgment. When the time window length reaches three weeks, the proportion of passengers in a spatial pattern decreases slowly and becomes stable after six weeks. When the time window length reaches two weeks, the proportion of passengers in a temporal pattern increases slowly and becomes stable after four weeks. The number of passengers for regular time, regular space, and regular space-time accounts for only 30.4% of the total number of passengers, but their number of trips accounts for 84.7% of the total number of trips, therefore, the bus dependence is very high, which should be taken as the key service object of public transport institutions. The classification results of the proposed method and K-means++ clustering method have a strong correlation, and the groups with very high or very low regularity for the two methods have a high degree of overlap. 13 tabs, 9 figs, 31 refs.More>
Abstract: To establish the intelligent train control system, the rail application of global satellite navigation system (GNSS) was focused, and the researches on the positioning optimization method of train were pursued. Based on the real-time characteristics of broadcast ephemeris, the frame transformation model was used to provide real-time, accurate and unified spatio-temporal reference for the system. Combined with the error model, the errors related to positioning were corrected to reduce the complexity of positioning solution. In order to further optimize the positioning performance of the system and improve the positioning accuracy, a non-differential carrier-phase positioning method based on GPS/BDS multi-constellation combined solution was proposed. A simulation was carried out based on the actual data of Beijing-Shenyang High-Speed Railway, the signal geometric distributions and positioning errors of single constellation positioning method and multi-constellation positioning method were compared. To further verify the performance of the proposed positioning method, its positioning result was compared with that of the traditional pseudorange-based single point positioning (SPP) method based on the same group of data. Experimental results show that, during the test, the visible average satellite numbers of GPS and BDS single constellation positioning methods are 9.2 and 13.4, respectively, and the means of geometric dilution of precision (GDOP) are 2.341 7 and 2.272 1, respectively. The visible average satellite number of GPS/BDS multi-constellation positioning method is 22.5, and the mean of GDOP is 1.264 6. Hence, the multi-constellation positioning method can multiply the number of visible satellites and optimize the geometric distributions of satellite signals, which ensures the accurate and continuous positioning under the continuous variation of satellite signal. When the satellite signal is relatively stable, the root mean square errors (RMSEs) of the three-dimensional positioning are 5.396 1, 5.569 7, 2.831 2 and 0.976 1, 0.988 8, 0.861 8 m with respect to the SPP method and the proposed method, respectively. In signal limited area, the RMESs are 7.245 9, 7.056 3, 3.756 2 and 1.561 2, 1.603 1, 1.215 5 m, respectively. Therefore, compared with the traditional SPP method, the proposed method can achieve better positioning accuracy under different signal conditions. 5 tabs, 7 figs, 22 refs.More>
Abstract: An intelligent navigation method of dynamic adaptive target ship collision avoidance action in open water was proposed considering the ship maneuvering characteristics, the requirements of International Regulations for Preventing Collisions at Sea 1972 and good seamanship. The digital twin traffic environment was constructed by classifying and modeling objects. An automatic navigation model was developed by combination of course control method, ship maneuvering motion and sailing resuming model, and ship's nonlinear maneuvering motion was deduced. The requirements of International Regulations for Preventing Collisions at Sea 1972 were quantitatively analyzed based on the automatic navigation model, and the dynamic collision avoidance mechanism was studied. The method to calculate applicable course was established. In the multi-target environment, the maneuvering discrimination method of target ship was proposed. The method to obtain the factors such as the course changing time, amplitude and sailing resuming time which constitute the autonomous navigation scheme under the constraint of rules was studied. Simulation results show that the intelligent navigation method can adapt to the residual error and random motion of the target ships based on the rolling calculations of the information update at the second-level. The proposed intelligent navigation method can accurately achieve the feasible course range and course change amplitude of 1°. The calculation step lengths of program and sailing resumption time are set to 1 and 10 s, respectively, and multiple static objects and six target ships maintaining the course and speed are established in this simulation environment. Own ship remains clear from all targets and sails autonomously to the destination after a series of maneuverings of 9° to starboard, sailing resuming, keeping course and speed, sailing resuming at 640, 1 053, 2 561 and 3 489 s, respectively. Target ships are set to perform uncoordinated collision avoidance actions at 300 s, and own ship remains clear from all targets and sails autonomously to the destination after a series of maneuverings of 9° to starboard, 12° to port, 17° to starboard, and sailing resuming at 980, 2 790, 3 622 and 5 470 s, respectively. Therefore, a ship in any initial states can automatically sail along a planned route to its destination. The proposed method is suitable for intelligent navigation in actual open sea areas with multiple and multiple dynamic and static objects. 5 tabs, 13 figs, 30 refs.More>
Abstract: To realize the automatic segmentation of puddle area of asphalt roads under various brightness levels and climate conditions, an attentional supervision mechanism was developed on the upsampling layer of existing full resolution residual network (FRRN). A puddle area attention module based on the full-resolution residual network (PAAM-FRRN) model was established by adding the puddle area attention module (PAAM) and the deep supervision module. An encoder-decoder structure was constructed by max-pooling and upsampling to capture the visual characteristics of puddle in a global scale. An attentional supervision mechanism was introduced in the upsampling layer to conduct the upsampling for the puddle area and fuse the features of different network layers to minimize the loss function of each network layer and optimize the overall final loss of the network. A total of 1 770 images (750 under low light, 740 under strong light and 280 under rainy weather) of asphalt pavement with puddle were collected for the five-fold cross-validation test, and the segmentation results of the puddle area were obtained. Manual annotation results were used as truth values, and the dice similarity coefficient (DSC), Jaccard similarity coefficient (JSC), precision, recall, and Hausdorff distance (HD95) were used as quantitative evaluation indexes. The segmentation effect of the proposed model was compared with the FRRN and seven other representative traditional models. Research results show that the mean values of DSC, JSC, precision, and recall obtained by the proposed model are 0.91, 0.86, 0.92, and 0.93, respectively, which are 3.41%, 6.17%, 2.22%, and 4.49% higher than those obtained by the FRRN, and are all higher than those obtained by the seven traditional comparison models. Standard deviation values of DSC, JSC, precision, and recall as computed by the proposed model are 0.12, 0.15, 0.11, and 0.12, respectively, which are 20.00%, 16.67%, 21.43%, and 25.00% lower than those of FRRN, and are all lower than those of the seven traditional comparison models. The HD95 of the proposed model is 38.56, which is lower than those of the other comparison models. Therefore, the proposed model can achieve accurate and effective segmentation of puddle areas of asphalt pavements under different brightness levels and climate conditions. 6 tabs, 11 figs, 40 refs.More>