In order to evaluate the temperature sensitivity of high viscosity modified asphalt and explore a more reasonable temperature sensitivity evaluation method for high viscosity modified asphalt, the temperature sensitivity of self-made high viscosity modified asphalt, domestic high viscosity modified asphalt and SBS/resin modified asphalt are evaluated by using the methods of penetration index (PI), penetration viscosity index (PVN), viscosity temperature index (VTS), complex modulus index (GTS) and complex index (CNI), and the applicability of 5 evaluation methods to the temperature sensitivity of high viscosity modified asphalt is compared. The test result shows that (1) the self-made high viscosity modified asphalt has the least temperature sensitivity, and its temperature sensitivity is better than that of other domestic high viscosity modified asphalts, while the SBS/resin modified asphalt has the greatest sensitivity to temperature, and the stabilizer is helpful to improve the temperature sensing performance of modified asphalt; (2) among the 5 temperature sensitivity evaluation methods, the data points collected by PVN method cannot meet the wide temperature range of high viscosity modified asphalt, and the test accuracy is low, which is not suitable for evaluating the temperature sensitivity of high viscosity modified asphalt; (3) the PI method, VTS method, GTS method and CNI method can be used to evaluate the temperature sensitivity of high viscosity modified asphalt, among them, the temperature range adopted by PI method is narrow and has certain limitation; (4) the temperature range involved in VTS method, GTS method and CNI method is consistent with the service temperature of high viscosity modified asphalt in actual asphalt pavement, while CNI method better considers the viscoelastic characteristics of high viscosity modified asphalt, so it is more accurate and reasonable to evaluate the temperature sensitivity of high viscosity modified asphalt.

In order to study the influence of Chloride Erosion on the mechanical properties of steel slag cement solidified silt soil and the law of chloride ion migration, indoor tests were carried out on the physical and mechanical properties and microstructure of steel slag cement solidified silt soil under Chloride Erosion, through unconfined compressive strength test, chloride ion concentration measurement test The macroscopic physical and mechanical properties, microstructure changes and internal chloride ion migration of solidified soil eroded by chlorine salt and solidified by steel slag cement under different conditions were studied by SEM test. The test results show that with the increase of erosion time, the mass change rate of steel slag cement soil sample is significantly higher than that of cement soil under the erosion of chlorine salt. The maximum mass change rate is 1.78 times of that of cement soil, and the maximum difference of water content can reach 9.17% and 8.54%; With the increase of erosion time, the unconfined compressive strength of specimens cured for 7 days showed an overall growth trend, and the broken line of unconfined compressive strength of specimens cured for 28 days showed the form of first increasing and then decreasing. The unconfined compressive strength of cement soil sample is significantly higher than that of steel slag cement soil, and its maximum strength is 2.34 times that of steel slag cement soil; With the increase of erosion time, the internal chloride ion concentration first increases and then tends to be stable. The chloride ion corrosion resistance of cement soil sample is better than that of steel slag cement soil sample. Compared with the maximum chloride ion concentration, steel slag cement soil sample is 1.52 times higher than that of cement soil. Microscopically, SEM test results show that with the increase of chloride erosion time, the internal structure arrangement of cement soil samples becomes relatively loose, which can seriously damage the internal structure of samples and reduce their bearing capacity.

To study the dynamic influence of hydraulic compactor reinforcing the subgrade on the back of abutment, based on the subgrade filling project of abutment back in the transition section of the high-speed bridge and tunnel, the interaction model of rammer, subgrade and abutment is established by ABAQUS. The accuracy of the model is verified by full-scale ramming test. In the process of simulation, the maximum dynamic displacement and maximum dynamic strain of abutment are taken as evaluation indexes. The influence of factors such as the dropping distance, the distance between tamping point and abutment, the initial compactness of subgrade, the strength grade of abutment concrete and the top support conditions of abutment on the abutment deformation were analyzed. The results show that (1) The error between the measured value and the simulated value is less than 10%, and the variation trend of abutment dynamic displacement and dynamic strain along the abutment height is in line with the convention, and the simulation model is reliable. (2) The maximum dynamic displacement and strain of abutment increase linearly with the increase of dropping distance and increase exponentially with the decrease of distance between tamping point and abutment. (3) When the initial compactness of subgrade increases from 75% to 95%, the maximum dynamic displacement and the maximum dynamic strain of abutment are basically the same, and the initial compactness of subgrade has little effect on the deformation of abutment. (4) The improvement of concrete strength grade of abutment has significant effect on the reduction of abutment deformation. (5) When there is no expansion joint at the top of the abutment, the maximum dynamic displacement and the maximum dynamic strain are reduced by 75% and 24% compared with those with expansion joint. In the process of reinforcement, the method of temporary blocking of bridge expansion joint can be used to change the stress form of abutment.

With the development of BIM technology in the highway industry, its application value has been fully affirmed in all stages of construction, such as design stage, construction stage and maintenance stage. The application field and depth continue to increase, while the accuracy of BIM models and the richness of information are proposed higher Claim. This paper conducts a systematic study on the application requirements of highway bridges at various stages, and formulates information standards such as coding, design information and engineering quantities included in the BIM model according to the application requirements of various stages. At the same time, it studies the BIM model decomposition and component level division rules of general highway bridges. In combination with application requirements, information standards, model decomposition and component hierarchy division rules, a BIM model structured organization method is proposed. This method separates BIM model to geometric model and model attributes, establishes the corresponding relationship between geometric model and model attributes through the ID, creates the BIM model decomposition scheme and hierarchical relationship configuration table based on the engineering construction application requirements, and finally creates the BIM model which matching this decomposition scheme and hierarchical relationship based on this configuration table. Research shows that the BIM model obtained based on the structural organization method of the highway bridge BIM model described in this article can adapt to different BIM standards and the change of BIM model under different application requirements, which is conducive to the adjustment of component hierarchical relationships and the expansion of BIM information, It is useful for establishing the correspondence between workflow (WBS) and BIM components, and improve the efficiency of BIM application, meet the needs of highways BIM application requirements at all stages of bridge construction.

In order to solve the problem of blasting vibration generated by the drilling and blasting method of the land section of the urban submarine tunnel, which has a great impact on the safety of the surrounding building (structure) structure and the life of residents, this paper optimizes the blasting technology of the sensitive building (structure) section of the urban shallow buried tunnel under complex geological conditions through field tests and theoretical calculations. The paper proposes the protection and reinforcement scheme of the building (structure), the auxiliary measures for controlling blasting and the optimization scheme of the control blasting parameters, and verifies the design of the trenching of the guide hole, the gun hole and the hole layout. The analysis of the data from the field test shows that the use of digital electronic detonators, controlling the maximum charge, reducing the size of the excavation section, shortening the feed can significantly control the blast vibration of the surrounding buildings, combined with the "hollow hole + hollowing + wedge hollowing" plan and parameter optimization. In addition, when the tunnel crosses the surface buildings in close proximity, the grouting piles, isolation piles and grouting are installed between the affected area and the building foundation, which can play an obvious role in vibration and settlement control. It can be seen that the blasting scheme adopted can effectively control the tunnel blasting vibration speed within 0.5 cm/s, basically achieve sensorless blasting at the surface 10 m in front of the palm, and the surface blasting vibration speed monitor outside the palm 20 m in front of the palm has no trigger, which greatly reduces the impact of tunnel blasting construction on the surrounding environment and ensures the structural safety of the buildings (structures) around the tunnel.

In order to understand the current study status and development trend of traffic volume forecast, based on the VOSviewer bibliometric tool, taking the Web of Science core collection and the literatures related to traffic volume prediction studies in recent 29 years (1993—2021) in CNKI core database as the data sources, the study trends in the field of traffic volume forecasting are analyzed in terms of article age, country and region, journal source and technical topics. Taking the "traffic volume forecast and" "traffic volume forecasting" as the search topics, 592 valid literatures covering 6 438 keywords are searched. Based on the scientific knowledge mapping, the literatures in the field of traffic volume prediction are sorted out and analyzed. The result shows that (1) Traffic forecasting studies have been on the rise in the past 29 years, and the number of publications in China is the highest. (2) Transportation Research Part C: Emerging Technologies is not only the journal with the largest number of literatures, but also the journal with the largest number of citations, and Journal of Highway and Transportation Research and Development is the most cited journal among domestic journals. (3) The studies in the field of traffic volume forecasting are mainly conducted from the perspectives of highway traffic demand development prediction, traffic volume prediction method model, traffic events and real-time monitoring, focusing on the topics of highway traffic volume prediction, project construction feasibility study, short-time traffic volume prediction method modelling and accuracy improvement, traffic event monitoring and traffic spatial and temporal distribution characteristics. (4) The number of foreign study literatures on the relationship between highway traffic volume and construction investment, traffic volume prediction under atypical conditions and the studies on traffic volume prediction under adverse weather conditions such as rain and snows shown a significant increase in recent years. (5) Domestic studies on the improvement of the four-stage method, feasibility study of road traffic construction projects and road tourism traffic volume prediction are relatively abundant, but mainly from the macro perspective of economy, population and tourism industry, it is necessary to further increase the studies on the influence of seasonal changes, individual travel characteristics and travel preferences on road tourism traffic volume prediction.

To improve the the vehicle detection accuracy under the condition of low light and long distance detection requirements on expressway, a radar-camera fusion vehicle target detection method based on visual enhancement and feature weighting is proposed. First, starting with the fusion of the radar-camera data layer, the spatial location of the potential target based on millimeter-wave radar is characterized, and the characterization result is used for the division of long-distance target areas in visual images. Then, the images of the divided area are reconstructed, detected, and restored to improve visual detection accuracy of the long-distance target. Next, the radar-camera detection feature layer is fused and modeling is conducted. Considering the difference in the contribution of different layers to feature detection, the weight parameters of different feature maps are obtained through model training, and the features of different layers are fused and calculated according to the weight to enhance the feature information of the target. Next, branch network is added, and different receptive field information in the feature map is extracted by using convolutional layers of different sizes, and the branch output results are fused to obtain stronger image representation ability, which can achieve the goal of improving the detection accuracy in low light. Finally, combining with the feature-weighted radar-camera framework and the vision enhancement based on millimeter wave radar spatial preprocessing, the radar-camera fusion detection network based on YOLOv4-tiny is designed and the verification system is built. The results show that (1) the average precision (AP) of the proposed algorithm in the low-light environment increased by 20% compared with that of YOLOv4, and the AP increased by 5% compared with that of the radar-camera fusion algorithm RVNet; (2) in the test of detection performance at different distances, when detecting a 120-meter target, the AP of the proposed algorithm is 73% higher than that of the YOLOv4 algorithm, and 63% higher than that of RVNet, which improved the coverage distance and low-light detection accuracy of vehicle detection in intelligent transportation systems(ITS).

To overcome the difficulty of complex network theory (CNT) to meet the requirements of integrated, comprehensive, and networked urban transport hub network system modeling. It leads to the incomplete depiction of heterogeneity characteristics of urban hub network elements and loss of internal structure characteristics of the hub, which leads to a large deviation in importance discrimination. Firstly, based on the super-network theory (SNT), the SNT model of urban transportation hub is defined and constructed. Secondly, combined with the actual structure characteristics of the hub and the characteristics of the hub SNT model, the lateral and longitudinal selection indexes of the super-edge (SE) are proposed, and based on this, the SE selection index is constructed. Then, from the perspective of the SNT, the paper introduces the method of judging the importance of urban transportation hub by using the SE selection degree. Finally, taking Beijing’s urban transportation hub as the research object, 16 transportation hubs composed of aviation, railway, long-distance passenger transport, urban public transport, and urban rail transit are selected for modeling and importance analysis. The results show that: compared with the node degree identification method of CNT modeling, the identification result of urban transportation hub importance based on the SE selection degree from the perspective of the SNT has a high degree of coincidence with the actual situation, which can deeply mine the topological structure features that are homogenized due to CNT modeling, and reveal that a single hub has multiple transportation modes and multiple links between hubs The functional characteristics of two modes of transportation connection. In terms of performance law, the fitting results of importance and selectivity from the perspective of SNT show the significant heavy-tailed distribution and power-law distribution, which are in line with the law of network evolution and development. It is of high theoretical and practical value to verify the importance discrimination method of selectivity as a measure from the perspective of SNT.

In order to further fully extract the spatio-temporal and periodic characteristics of traffic flow, this paper adopts a combined model (DLSTM-AE) of Autoencoder architecture and Deep Long Short-Term Memory neural networks, and introduces rectified adaptive moment estimation (RAdam) algorithm for model training. Firstly, the characteristics of traffic flow sequence information are collected by using the deep long short-term memory network model, and the collected information is compressed into a fixed dimension representation vector with the help of the automatic encoder structure. Then, the vector is reconstructed by the decoder to realize further information mining. Finally, in the process of model training, the RAdam algorithm is used to optimize and update the momentum parameters in batches, so as to shorten the time to find the optimal solution. This can improve the timeliness and accuracy of model prediction. Simulate on real data sets of highway traffic flow and compare with other model methods, DLSTM-AE combined model not only has obvious advantages in prediction results, but also has good curve fitting ability in traffic flow periodicity. The root mean square error (RMSE) value of DLSTM-AE combined model on the test set decreased by about 0.445 to 1.826, the average absolute error (MAE) value decreased by about 0.282 to 0.984, and the coefficient of determination (R²) value increased by about 0.005 to 0.023. In terms of periodicity, the prediction accuracy of working days corresponding to adjacent weeks is much higher than that of the control group. Simulation results show that the model can capture more potential spatio-temporal and periodic information in traffic flow sequence. It can better meet the needs of highway traffic flow prediction.

Based on the stopping sight distance and reliability theory, the braking safety reliability of road vehicles in heavy rainfall environment is studied. Starting from the principles of kinematics, the AASHTO model is improved, and the vehicle braking safety reliability model in heavy rainfall environment is established. Taking the vehicle speed, rainfall intensity and thinking time as random variables, the braking safety reliability and reliability sensitivity of road vehicles with different rainfall intensities and different vehicle speeds are researched by using Monte Carlo method. The result shows that (1) Compared with the original AASHTO model, the stopping sight distance calculation value obtained by the improved AASHTO model is larger and the difference value increases with the increase of vehicle speed. (2) the change of vehicle speed has great influence on the fluctuation degree of stopping sight distance, while the change of rainfall intensity has little influence on the fluctuation degree of stopping sight distance. (3) The safety speed limit in rainy days calculated by the deterministic method is dangerous, while more reasonable safety speed limit in rainy days can be obtained based on the reliability method. (4) There is a maximum value of the sensitivity of failure probability to the mean random variables. The maximum values of the sensitivity of failure probability to the mean vehicle speed and the sensitivity to the mean thinking time increase with the increase of rainfall intensity, while and the maximum value of the sensitivity to the mean rainfall intensity decreases with the increase of rainfall intensity. (5) There is a maximum value and a minimum of the sensitivity of failure probability to the standard deviation of random variable. The absolute values of the maximum and minimum of the sensitivity of the failure probability to the standard deviation of vehicle speed and the standard deviation of thinking time increase with the increase of rainfall intensity, while the absolute values of the maximum and minimum of the sensitivity to the standard deviation of rainfall intensity decrease with the increase of rainfall intensity.