Abstract:This paper first reviews the privacy backgrounds especially the Internet of Vehicle （IoV）characteristics， privacy features and common privacy leakage attacks. Then， it elaborates the characteristics and needs of different types of privacy in terms of identity privacy， location privacy and data privacy as well as the key privacy protection technologies and methodological evolutions for different privacy types . On this basis， the representative privacy metrics schemes， theoretical models， and metrics challenges for different types of privacy are studied in depth across multiple privacy domains. Furthermore， 8 key attributes and 32 indicators of privacy metrics in IoV are summarized. Finally， a discussion is also made on the future research directions and challenges of privacy metrics.

Abstract:Aiming at the information security and data missing caused by network attacks or interference for ICVs （Intelligent Connected Vehicle）， this paper proposes a short-term prediction method of traffic flow state based on data imputation. Firstly， based on the edge computing task offloading model， the abnormal data of the V2X （vehicle to everything， V2X） communication process of ICVs is identified dynamically. Secondly， a graph embedding （GE） with data imputation mechanism and long short-term memory （LSTM） neural network model is proposed to impute the missing data. Thirdly， the neural network model is established based on the complete data sets to realize the short-term traffic flow state prediction. Finally， by the proposed model applied in Beijing for field test， the final results show that the short-term prediction effect of traffic flow state is significantly improved. In comparison with other methods， the prediction error is reduced by 87.4% and the accuracy of the prediction effect is 95% according to the actual traffic flow state， which provides a novel theoretical support and technical solution for vehicular information security and dynamic optimization of traffic resources in the intelligent networked environment.

Abstract:The connected automated vehicle （CAV） is promising to enhance traffic efficiency， traveling safety， and energy savings. However， due to the open wireless communication， the CAV is vulnerable to cyber threats. Existing studies mainly focus on surveying related cyberattacks and evaluating the impact of attacks on vehicular longitudinal behaviors on a single lane. This paper aims to investigate the effects of cyberattacks on vehicular lateral behaviors on a two-lane highway， i.e.， the lane-changing （LC） behaviors under cyberattacks. Based on a classical lane-changing model--minimizing overall braking induced by lane changes （MOBIL） model， and a classical car-following model--Intelligent Driver Model （IDM）， this study proposes an extended lane-changing model （ELC） which can model CAV's lane-changing behaviors under cyberattacks. At the end， simulations are conducted to illustrate the impact of different malicious attacks on vehicles' LC movements. Results show that cyberattacks can imperil the LC maneuvers and lead to abnormal driving behaviors.

Abstract:This paper proposes a novel lane-changing trajectory planning algorithm that could mitigate lane-changing impact. We introduce the intelligent driver model（IDM ）to construct the optimization objective of the surrounding vehicles， and we employ the quintic polynomial model to formulate the optimization objective of the lane-changing vehicle. Thereafter， we introduce the multiobjective optimization algorithm to solve the multi-objective problem， as a result， we obtain the pareto-optimal front of the lane-changing vehicle and the surrounding vehicles. Our experiments demonstrate that in comparison with the existing algorithms， our algorithm can significantly reduce the total cost of all vehicles within the region and improve the traffic flow operation state.

Abstract:A microscopic traffic flow model was proposed based on a traditional car-following model with the consideration of the effects of multiple preceding cars’ velocity and acceleration； then the parameters of car-following models were calibrated on the basis of the vehicle trajectory； Subsiquently， the impact of multiple preceding vehicles information on traffic safety and efficiency were also investigated； finally，the influence of cooperative adaptive cruise control （CACC） vehicles on traffic safety and efficiency with different penetration rates were also studied. Simulation results prove that except for the immediately preceding vehicle，multiple preceding vehicles’information in the control strategy of the CACC system would have an impact on the following vehicle； the consideration of the velocity and acceleration of multiple preceding vehicles can improve traffic safety and efficiency；the impact of CACC on traffic safety and efficiency was highly related to the penetration rate and arrangement of CACC vehicles.

Abstract:Aiming to reduce the differential deformations between frame columns and core tubes in super high-rise buildings， a synchronous grouping compensation method is proposed， which considers the time-dependent effects of concrete and the influence of construction process. In this method， frame columns and core tubes are synchronized grouped and compensated by setting the allowable value of the elevation difference. In addition， the proposed grouping compensation method is applied to the elevation compensation of the Tianjin Building 117 The analytical results show that the vertical deformation of frame columns and core tubes under the effect of long-term shrinkage and creep exceeds 30% of the total deformation， and the proportion increases with time. Besides， the proposed method can limit the elevation difference of the vertical components themselves and their relative elevation difference within the allowable value， which can effectively reduce the additional internal force of the components caused by the time dependent effects.

Abstract:In order to investigate the static performances of segmental prefabricated large-cantilevered PC cap beams with different epoxy joints under the combined action of bending and shear internal forces， an integral precast large-cantilevered PC cap beam model and 3 segmental prefabricated large-cantilevered PC cap beam models with large key teeth， small key teeth and corbel joints respectively （the scale of each model is 1：5） were designed and manufactured based on a practical engineering. The full-process static loading tests of the four models were conducted， and the key results such as cracking loads， ultimate load capacities， distributions of concrete strains， deflections， and maximum crack widths of the cap beams were obtained. The test results show that： the crack distributions of the segmental prefabricated models are basically the same as that of the integral prefabricated model， and cracks in the cap beams of all test models are sparse and wide during failure； the failure modes of all test models are flexural failure； the cracking load of the cap beam model with large key teeth or corbel joint is the same as that of the integral cap beam model， while the cracking load of the cap beam model with small key teeth joint is only 81% of that of the integral cap beam model； the ultimate bearing capacities of the cap beam models with different epoxy joints are significantly lower than that of the integral cap beam model； among segmental precast models， the ultimate bearing capacity of the cap beam model with corbel joint is the largest， which is about 84% of that of the integral cap beam model； in terms of ultimate deformation capacity， the ultimate displacement of the cap beam model with corbel joint reaches 75% of that of the integral cap beam model， while the ultimate displacement of the model with large or small key teeth joint is lower than 50% of the integral cap beam model. From the test results of static performances and construction performance， the corbel joint is a more reasonable epoxy joint recommended for segmental prefabricated large-cantilevered PC cap beams.

Abstract:On the basis of the analysis of engineering characteristics of anchoring strata， six relevant engineering indicators referring to characteristics were proposed. Three operational parameters of shield machine were included into inputs. A set of model indexes for the prediction of shield performance was constructed by taking the penetration rate and the torque of cutter head as outputs of tunneling performance. In combination with an actual project of Wuhan metro，the excavation parameters were collected during the anchor-cutting excavation. Prediction models for penetration rate and torque were developed respectively based on LightGBM method， and whale optimization algorithm （WOA） was used to find the most suitable parameters in LightGBM model. Results show that the proposed model indexes are proper and rational， which can predict the shield performance when tunnelling in anchorage zone； the WOA-LightGBM-based prediction model has obvious advantages in prediction accuracy compared with BP and ELM neural network， while the time-consuming is similar.

Abstract:Based on the investigation of typical earthquake disasters， this paper reveals the phenomenon of post-earthquake urban structure alienation from the perspective of resilient cities. Based on the basic process of urban restoration， a key indicator named the social impact factor of urban systems is proposed， which couples engineering science with social science and further revises the function evaluation for the urban system resilience. Finally， based on the Agent model， this paper quantitatively studies the population redistribution for determining the social impact factor of urban systems， and quantitatively studies the influence of disaster prevention education， earthquake intensity， and post-earthquake crowd information communication efficiency on the short-term population redistribution.

Abstract:This paper identifies the residents who have changed their residence and workplace through tracking analysis by the signaling data of shanghai mobile phone in two weeks of 2011 and 2014 as the research object， and to track and study the commuting behavior of the same group of the residents who have changed their residence and workplace by means of data visualization， descriptive statistics and quantitative comparative analysis， so as to analyze the "self-balancing" characteristics existing in the process. And the relationship between the characteristics and urban space is further studied. The results show that： On the overall level， from the change of average commuting distance and over-commuting rate， residents have the characteristics and trends of commuting "self-balance" when they change their residence and workplace； On the individual level， the farther the original commuting distance is， the better their commuting will be through the change of residence and workplace. The more obvious the effect of relationship pursuit of commuting "self-balance"； The commuting "self-balance" characteristics of residents in the change of workplace are more significant than those in the change of residence； At the level of spatial aggregation， there is a general "self-balance" phenomenon in the residential and employment areas with poor occupational-residential relationship.

Abstract:Based on the movement bottleneck and traffic flow theory， a "truck movement block" effect model was constructed to analyze occurrence mechanism and the car-following behavior. Then， the UAV was selected to collect the vehicle driving video under the truck movement block， and the high-precision car-following trajectory was extracted by trajectory software. Last， the car-following risk assessment methods and grading standards that considers both the possibility and the severity of the risk was proposed. And the random parameter ordered probit model （RP-ORP） was established to assess the car-following risk， and the elasticity coefficient was introduced to analyze the magnitude and direction of the impact on car-following risk. This finding demonstrates that truck movement block includes two processes： car-following and overtaking， which dynamically affects the traffic stability. the RP-ORP model has a better fit than the FP-ORP model， and can realize the probability prediction that different car-following levels under certain conditions. Five variables significantly affect the car-following risk level， such as truck longitudinal acceleration， car-following distance， car-following time， average car-following speed difference， radical driver， among the variables of car-following time and radical driver have random parameter characteristics.

Abstract:An adaptive signal control optimization method based on E-police data was proposed by deeply mining and utilizing the traffic flow information contained in E-police data. The study object is a four-arm intersection where E-police detectors are deployed at each approach. Its four upstream intersections are also equipped with E-police detectors， which can obtain the traffic flow to the target intersection. Firstly， according to the matched historical data of upstream and downstream E-police in the TOD period， the link travel time parameters were estimated by Gaussian mixture model， and then the platoon discrete model based on truncated normal distribution was calibrated； Secondly， based on the predicted value of real-time arrival rate， taking the minimum total delay of the target intersection as the optimization objective， an integer programming model was established to optimize the signal control parameters in real-time by rolling horizon scheme， which was solved by dynamic programming； Finally， the proposed methods were simulated and verified in different demand scenarios. The results show that the estimation errors of the mean and standard deviation of link travel time are less than 3s， and the average vehicle delay and queue length are reduced by more than 34.2% and 40.5% respectively compared with the optimal group-based timing. Compared with the actuated control， the improvement of the proposed method is more obvious in high demand scenarios， where the average vehicle delay and queue length are reduced by 12.9% and 15.8% respectively， and more than 2.6% and 5.4% in other scenarios respectively. At the same time， the increase of planning horizon can also improve the control benefits.

Abstract:This paper studies the main factors influencing breakthrough automobile styling design decisions and the weights in each period， in order to assist the decision makers of automobile design to select breakthrough automobile styling， From the perspective of design decision-makers， evidence triangulation was used to screen out 17 factors affecting breakthrough car styling design， and several experts and professors with 15~60 years of experience worldwide were investigated. Factor analysis was used to extract the factors. The tendency of the weight of breakthrough automobile styling design is obtained by using analytic hierarchy process （AHP） and sequence diagram method. The results show that the decision factors of automotive breakthrough styling design are affected by the following 5 factors： user psychology and aesthetics， marketing strategy， production technology and materials， dynamic arrangement factor， economy and society. Their weights have gone from chaotic to stable over the past century.

Abstract:Aiming at the problems of insufficient data collection range， high cost， low data accuracy and low utilization rate of unstructured data when analyzing user perceptual evaluation， a perceptual evaluation method of industrial design based on sentiment analysis was proposed. Taking battery electric vehicle as an example， the prediction model of perceptual image of electric vehicle modeling was constructed. Firstly， the subjective comments of users are quantified based on sentiment analysis to obtain the perceptual image score. Then， according to the modeling characteristics of battery electric vehicles， the main design elements different from traditional internal combustion engine vehicles are extracted. Finally， the mapping model between perceptual image score and design elements is established through quantitative-I theory. Taking the optimization of electric vehicle design scheme as an example， the feasibility of this method is proved， and the relative error of the prediction result is 5.41%. This method conforms to the user's subjective cognition and can effectively predict the user's perceptual evaluation of the scheme， so as to assist the designer to optimize the product design according to the perceptual evaluation. It has practical application value.

Abstract:The k-frugal choice number of graph G is denoted by chk(G). In this paper， we prove the following theorem. Let G be a graph with maximum average degree madG<3-a (0<a≤13) and maximum degreeΔG≥k+3a-3， then chkG=?k-1+1 for any integer k≥3； Let G be a graph with maximum average degree madG<3， then chkG≤?k-1+2 for any integer k≥4； Let G be a graph with maximum average degree madG<103， then chkG≤?k-1+3 for any integer k≥4.

Abstract:On the ground that previous buffer determination methods do not pay much attention to the psychological and behavior impact on the safety time extraction， based on the principal-agent model， this study selects the vertical trust between employees and supervisors as the breakthrough point by taking into consideration of the influence of factors such as trust relationship and behavior preference on the determination of buffer. It takes the maximum benefit of both parties as the optimization goal to solve the effort level of employees and determine the safety time of activities. This method is validated by Monte-Carlo simulation and proves to be appropriate to protect the project with reasonable buffer. The duration is shortened， and the project completion is guaranteed.

Abstract:The paper analyzes its elements and dimensions from the evolution of science and technology development strategies， and studies the interaction mechanism between the future， vision， scenario， scene and technology through the deep neural network model，.Finally， The paper constructs a bidirectional multi- layer neural network model with four layers and two action ways and the basic formulation process of vision-based technology development strategy.