Abstract:To investigate potential differences in the brain cognitive responses to emotions between road traffic and daily life scenarios， ten participants were invited to complete emotion induction experiments in both road traffic and daily life settings. Then we analyzed the differences in concentrations of oxygenated and deoxygenated hemoglobin in the frontal and lateral lobes across two scenarios， discrete emotion and continuous emotion， in order to infer the activation degree of brain regions. The results show that the activation of the frontal and lateral lobes is stronger under anger and surprise emotions in road traffic scenario than that in daily life scenario， but lower in happiness emotion. However， significant differences are found only in the frontal lobe under fear emotion， and the activation is lower. In addition， compared with daily life scenario， the functional connectivity strength between the frontal and lateral lobes is higher under anger， fear， and surprise emotions in road traffic scenario， while it is lower under happiness and sadness emotions.

Abstract:The level of human-machine mutual trust is a key factor affecting the performance of human-machine cooperative systems. This paper presents a Stackelberg Game-based cooperative control strategy that considers human-machine trust matching. Firstly， a method was proposed for assessing the mutual trust level between drivers and machines. Based on this， the weight allocation in cooperative driving was performed according to the level of human-machine trust matching. Subsequently， a model predictive control framework was adopted， and the optimal cooperative control strategy was obtained by combining the Stackelberg Game theory for optimization. Finally， driver-in-the-loop experiments were conducted to validate the proposed cooperative control strategy. Results demonstrate that， for drivers with different trust matching levels， the strategy can improve the precision of path tracking by 70.91%， and reduce the driving burden by 44.03%. The proposed strategy enhances the driving performance and reduces the driver workload.

Abstract:Previous research in the passenger car domain has found that drivers using advanced driver assistance system （ADAS） are more likely to experience fatigue compared to manual driving. Therefore， it is necessary to investigate the impact of ADAS on the fatigue levels of truck drivers during long-haul driving. Based on over 120 h of naturalistic driving experiments， multiple psychophysiological indicators （such as heart rate， heart rate variability， etc.） were used to compare the fatigue levels of heavy truck drivers when manually driving vehicles and when driving vehicles with ADAS. The average heart rate， respiratory rate， respiratory depth， and pupil diameter of drivers driving with ADAS are all higher than those under manual driving. When driving with ADAS， the drivers’ root mean square of continuous RR interval， low to high frequency ratio， blink frequency， blink duration and PERCLOS are all lower than those under manual driving. When the driver is driving manually， the reaction time will increase by 0.032 s for every 2 hours. When the driver is driving with ADAS， the reaction time does not change significantly with the increase of driving time. The fatigue levels of heavy truck drivers when driving vehicles with ADAS are lower than when manually driving， providing theoretical support for the safe use of ADAS in heavy trucks.

Abstract:In response to the problem of lack of haptic feedback or overly simplistic haptic feedback in the virtual buttons of automotive user interfaces， three types of real physical button data （toggle switch， self-locking button， reset button） were collected， and button features were extracted. Different vibration feedbacks were achieved in segments based on finger pressure. Subsequently， a haptic rendering method that reproduces button compliance was further proposed， and its improvement in compliance and user pleasure compared with compliance illusion methods was verified based on user subjective feelings. Finally， a matching experiment was conducted， and the experimenter matched three types of virtual buttons with physical button types based on haptic sensation. The overall accuracy is as high as 94.33%， proving that the vibration haptic feedback of the proposed virtual button effectively restores the unique perceptual characteristics of different physical buttons，and users distinguish the type and state of the manipulated virtual button without the need for visual attention.

Abstract:While providing more environmental information to drivers， the blind area display of intelligent vehicles during lane changes may also increase the driver’s cognitive load. To address this issue， this paper presents an improved AttenD algorithm， which establishes a relationship model between the cognitive load and distribution of drivers’ fixation points. Field tests were conducted on three intelligent brand cars， and differences in drivers’ gaze characteristics， driving behavior characteristics， and cognitive load during the interaction between the driver and lane-changing blind area display were analyzed. Results show that increasing the size of the blind area display， increasing the blind area’s ratio on the center control panel， and minimizing unnecessary scanning movements can reduce the cognitive load and improve the safety during lane changes.

Abstract:In this paper， high-risk scenario element parameters are used as control switching conditions to explore the impact of secondary tasks on driver takeover performance. Specifically， the high-risk scenario of adjacent vehicles entering is extracted from the NGSIM dataset as the control switching condition. The Pearson correlation test is used to analyze the correlation between different takeover performance indicators， and one-way ANOVA is used to analyze the impact of the resource occupation mode and interruptibility of secondary tasks on takeover performance indicators. The results show that the takeover time is coupled with the lateral and longitudinal maneuverability， safety， and takeover efficiency during the takeover process. Increasing visual occupation increases the takeover reaction time by 0.26 s and undermines the vehicle longitudinal stability and takeover efficiency. Increasing auditory occupation increases the takeover reaction time by 0.45 s and reduces the takeover efficiency. Increasing cognitive occupation decreases the takeover reaction time by 0.23 s and improves the takeover safety. Increasing operational occupation increases the takeover reaction time by 0.21 s and increases the maximum lateral acceleration during the takeover process. The interruptibility of secondary tasks reduces the takeover reaction time by 0.23 s， but has no significant impact on subsequent vehicle control related indicators during the takeover.

Abstract:In this paper， the calculation method of modified wind direction reduction factor of strong wind speed considering the influence of twisted flow in the design wind load estimation of super high-rise buildings is proposed. Wind tunnel tests of a square section high-rise building model under twisted and non-twisted wind fields are conducted. Using the proposed correction method， the wind direction reduction factors of design wind speeds of the Beijing and Nanjing regions are calculated. And the influence of twisted flow on the wind direction reduction effect of the aerodynamic force of the building is analyzed. The results show that there is a shift of wind pressures on the building under the twisted wind field， and the wind direction angles of the most unfavorable wind pressure under the twisted wind field are different from the cases under the non-twisted wind field. In the wind load estimation of the wind direction reduction effect， ignoring the influence of twisted flow may lead to a serious underestimate of the wind load of super high-rise buildings， making the structural design more dangerous. Moreover， the proposed correction method in this paper can effectively solve this problem.

Abstract:In this paper， the rigorous incremental dynamic analysis （IDA） method is employed to systematically investigate the ductile seismic performance of pile-group foundations （PGFs）. A shake-table test on the pier-PGF system in sand is firstly used to validate the numerical modelling technique. Based on the engineering practice， a series of analytical models are then established considering the variation of nine structural/geotechnical parameters. Seven ground motion records are selected for the implementation of IDA. Finally， the seismic failure process of PGFs is validated and three performance indicators in terms of displacement， rotation and strength are proposed. And the impact of each parameter on the proposed performance index is investigated. It is found that for PGFs in the easy-to-repair state， the average displacement ductility is 2.52 and the average lateral strength is 1.41 times of that of the first-yield state. The average ultimate displacement ductility of PGFs is 3.62 and the average ultimate lateral strength is 1.47 times of that of the first-yield state. The maximum drift ratio of the pier induced by pile-cap rotation is less than 0.7%.

Abstract:Ten axial tensile tests and twelve combined tension and bending tests were conducted on the designed anchorage system specimens to investigate the mechanical properties of the carbon fiber reinforced polymer （CFRP）bonded anchorage system under combined tension and bending. Based on the optimization of the anchorage system， the ultimate bearing capacity， failure modes， anchorage efficiency， and CFRP tendon load-strain relationship of the specimens were studied with CFRP diameter and bending radius changes. The results indicate that the tensile strength reduction coefficient of the anchorage system decreases with the increase of CFRP tendon bending radius， and the larger the CFRP tendon diameter， the greater the reduction coefficient of specimen bearing capacity. The transverse constraint of CFRP tendons contributes to the improvement of tensile strength with bending. Additionally， the nonlinear variation of the load-strain curve of CFRP tendons is a typical characteristic before specimen failure； the ratio of bending radius to CFRP tendon diameter shows a linear relationship with the anchorage efficiency coefficient， and when the ratio is below 2.4‰， the anchorage efficiency coefficient of the specimen is less than 80%， exhibiting failure modes of non-uniform fracture and shear.

Abstract:In order to analyze the effect mechanics of chemical weathering on the mechanical properties of rock， in this paper， the densely packed particle assembly is used to simulate rock materials， and the mass loss rate related to chemical weathering time is introduced into the particle stiffness and contact model. Through the homogenization method and lattice model， the stress-strain relation in elastic stage， strength criterion and macro and micro quantitative relations of elastic and strength parameters with microscopic parameters （e.g.， inter-particle contact properties， weathering damage parameters） of rock are obtained， and the effects of chemical weathering and aging are investigated. The results show that with the increase of mass loss rate and erosion time， the stiffness and strength negative exponentially decrease. For the lower environmental pH value， both of the peak cohesion and peak internal friction angle decrease significantly with reaction time； while for the higher environmental pH value， the peak cohesion reduces significantly and the peak internal friction angle almost keeps constant in a short time， and more environmental time is needed for the decrease of peak internal friction angle.

Abstract:In this paper， the basic characteristics of water-sediment movement in swash zone are described， and the latest research progress on the influence of infiltration or exfiltration， bore turbulence， sediment advection， settling or scour lag， longshore current， wave-swash interaction and wave group on the water-sediment movement in the swash zone is summerized. The basic facilities of physical experiments on the water-sediment movement in the swash zone are introduced， and the latest progress of the observation technology of the sediment movement in the swash zone is reviewed. Two types of numerical models used to study the water-sediment movement in the swash zone are presented， and their advantages and disadvantages are investigated. The limitations of existing research methods and results are discussed， and the future research prospects are proposed.

Abstract:This paper presents the control mechanism of deep reinforcement learning （DRL） in a typical ramp metering scenario. The state value function is used to evaluate if the DRL model has the ability to distinguish the change of state. The saliency map is used to perceive the state key features and control pattern for the DRL model under specific traffic states. By using the input perturbation， the action match ratio and control performance under perturbed data are analyzed to explore the key areas of control. The results show that the DRL model can evaluate the traffic state accurately， distinguish the key features， and then make reasonable decisions.

Abstract:A fusion speed measurement algorithm of high-speed trains based on robust adaptive filter was proposed to solve the problem that the fusion accuracy decreased due to the observation gross errors and the dynamic model errors in the fusion speed measurement using Kalman filter. Firstly， the anomaly detection function and error discrimination statistics were constructed on the basis of Kalman filter， which were used to detect and distinguish the observation gross errors and dynamic model errors caused by abnormal observations of sensors. Then， for observation gross errors and dynamic model errors， a three-segment function and an exponential function were used to construct robust factor and adaptive factor， respectively. The weights of observation information and model information in state estimation were reasonably adjusted by the two factors， so as to reduce the impact of observation gross errors and dynamic model errors on the fusion results. Finally， the performance of robust adaptive filter was verified by simulation with two operation scenes and comparison between algorithms. The simulation results show that compared with the fusion speed measurement algorithm based on Kalman filter， the proposed algorithm has higher accuracy and stability in both the observation gross errors scene and the dynamic model errors scene.

Abstract:Aerobic composting is a traditional method for organic solid waste treatment. However， high temperatures， high pH values， and anaerobic conditions during the composting process contributed to severe nitrogen loss in the form of NH₃， N₂O， N₂， which exacerbated the pressure of environmental pollution and reduced the quality of compost products. Biochar， phosphorus magnesium additives， microbial inoculants and other exogenous substances were proved to play a significant role in reducing nitrogen loss in the composting process. It was attributed to nitrogen cycle regulation composting by environment optimization and microbial activity improvement. This paper presents the basic mechanism of nitrogen cycle in aerobic composting. Meanwhile， the recent achievements of physical， chemical and biological additives on controlling nitrogen loss in aerobic composting are summarized. Furthermore， the influence mechanism of exogenous additives on nitrogen transformation and metabolism in composting is elucidated. Finally， the potential in nitrogen cycle path and the interaction between additives and matrix in the future research are prospected.

Abstract:In order to study the thrust of cylinders in the trimmer mechanism of a segment erector under the pipe-splicing operation， the dynamic characteristics of the trimmer mechanism under yaw and pitch motions were analyzed. Firstly， the relationship between the platform angle of the simplified trimmer mechanism and the stroke of the driving cylinder was figured out. Secondly， the mechanism was modeled and simulated with Matlab Simscape to obtain the thrust values of two cylinders under the specified motion. Thirdly， the mechanism model was verified by ADAMS to carry out the dynamic simulation. Lastly， the dynamic simulation of the mechanism model under working load was carried out with ADAMS， and the maximum thrust values of the two cylinders were obtained. The results show that the maximum thrusts of the two cylinders are 8 998.47 N and 6 390.48 N respectively when the trimmer mechanism performs pitch and yaw motions as a sinusoidal function with an amplitude of 0.035 rad and an angular frequency of 1 rad·s^-1.

Abstract:To mitigate the adverse effects of large-scale integration of electric vehicles into the grid， a method for the precise prediction of charging station load is proposed in this paper. The method employs a combination of LightGBM and XGBoost to construct offline-online ensemble models. Historical data including charging load， time， temperature， and weather are considered. Firstly， a charging load offline prediction model is established using LightGBM. Based on the XGBoost model， with the error between offline prediction model output load and actual load as the optimization target， and the real-time varying traffic flow as a covariate， an online prediction model is developed， and the error correction is performed on preliminary prediction results. Predictions from actual charging stations in a certain city indicate that compared to random forest （RF）， LightGBM， XGBoost， multilayer perceptron （MLP）， and LightGBM-RF ensemble models， the ensemble model demonstrates higher prediction accuracy while accurately forecasting real-time charging loads for different charging stations.

Abstract:The urban tree species are an important factor affecting the ability of carbon sequestration by urban forest and the maintenance of ecosystem stability. However， due to the wide spatial distribution and complex environment of urban trees， there is a lack of tree species classification models applicable to cities. In this paper， the spaceborne LiDAR is introduced into tree species classification. Considering the vegetation canopy structure， horizontal spectra and spatial environment characteristics， the optimal feature set is constructed by quantitatively measuring the contribution of each parameter through feature space analysis. Finally， an urban tree species classification model combining spaceborne LiDAR and optical images is established using support vector machine （SVM） algorithm. Four representative regions in Shanghai are selected for validation， and the results show that the proposed fusion model has a high accuracy with the Kappa coefficient reaching 0.82 and the overall classification accuracy of 87.04%. The spaceborne LiDAR plays an important role in the urban tree species classification， and its retrieved 3D structural variables of vegetation together with spatial environmental characteristics play a major contribution to urban tree species classification.

Abstract:With the continuous acceleration of urbanization and the rapid advancement of the Internet of Things technology， the study of wireless sensor networks within complex underground soils has become a new hot spot. In this paper， we first summarize the basic architecture and research status of LoRaWAN-based wireless underground sensor networks and build a network simulator to implement two optimization algorithms of adaptive data rate （ADR） mechanism at the sensor node and the network server， respectively. Furthermore， we conduct a quantitative evaluation of network performance from the aspects of the underground deployment environment （soil’s moisture content and sensor’s burial depth） and physical layer parameters of LoRa， according to the performance indicators of the overall data extraction rate and network energy consumption. The results show that for the complex soil， the ADR mechanism has a good ability to adjust the physical layer parameters of nodes in LoRaWAN-based wireless underground sensor networks， which can provide a favorable means for the performance optimization of wireless underground sensor networks， and is expected to greatly reduce the network energy consumption.