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With the continuous improvement of the integration and intelligence of ubiquitous power Internet of things system equipment, its cost in life cycle management such as data service, operation monitoring, and safety protection is becoming higher and higher. At the same time, the probability of power grid failure, reduced operation efficiency, and function failure will gradually increase with the development of its scale. Accurately evaluating the metering performance of distribution network digital metering system in the operation of power system and improving its accuracy, stability, and reliability are the key issues for its future use in power trade settlement. In this paper, a digital reconstruction method of power metering production data based on digital twin is proposed. The operation data of power system is collected in real time through the data acquisition module, the operation data is analysed, identified, and predicted, and then the analysis, identification, and prediction results are used to realize the visualization and digitization of operation data. Further, the operation data of the digital metering system are monitored and analysed to verify the effectiveness of the method. The advantages and disadvantages of the design scheme of the digital metering system are obtained by analysing the active power error, which provides the basis of practice and selection for the application of the digital metering system.

In this work, a La

The floor heating system with phase change materials (PCMs) for thermal storage is an effective approach to increase the floor thermal capacity and reduce indoor temperature fluctuation range. A two-dimensional numerical model of the floor heating system combined with PCM was developed to investigate its dynamic thermal performance in winter. To verify the reliability of the model, an experimental room was established in Beijing, China. The experiment results agreed well with the modelling results, which demonstrated that the numerical model was reliable. The effects of the phase change temperature, latent heat and thermal conductivity of PCM on the thermal performance of the floor were numerically investigated. The results showed that the phase change temperature and thermal conductivity of PCM had a significant influence on thermal comfort. At the same time, these two thermal physical parameters also played a critical role in improving the utilization rate of PCM. Conversely, the latent heat, in the range of 100 to 200 kJ/kg, had no obvious influence on the thermal performance of the floor. PCM with phase change temperature of 313 K was recommended, which could increase the average indoor temperature by 2.2 K, increase the thermal energy storage ratio by 12% and reduce indoor temperature fluctuation range by 2.2 K.

Missing traffic data are inevitable due to detector failure or communication failure. Currently, most of imputation methods estimated the missing traffic values by using spatial-temporal information as much as possible. However, it ignores an important fact that spatial-temporal information of the traffic missing data is often incomplete and unavailable. Moreover, most of the existing methods are verified by traffic data from freeway, and their applicability to urban road data needs to be further verified. In this paper, a hybrid method for missing traffic data imputation is proposed using FCM optimized by a combination of PSO algorithm and SVR. In this method, FCM is the basic algorithm and the parameters of FCM are optimized. Firstly, the patterns of missing traffic data are analyzed and the representation of missing traffic data is given using matrix-based data structure. Then, traffic data from urban expressway and urban arterial road are used to analyze spatial-temporal correlation of the traffic data for the determination of the proposed method input. Finally, numerical experiment is designed from three perspectives to test the performance of the proposed method. The experimental results demonstrate that the novel method not only has high imputation precision, but also exhibits good robustness.

Vehicles are often caught in dilemma zone when they approach signalized intersections in yellow interval. The existence of dilemma zone which is significantly influenced by driver behavior seriously affects the efficiency and safety of intersections. This paper proposes the driver behavior models in yellow interval by logistic regression and fuzzy decision tree modeling, respectively, based on camera image data. Vehicle’s speed and distance to stop line are considered in logistic regression model, which also brings in a dummy variable to describe installation of countdown timer display. Fuzzy decision tree model is generated by FID3 algorithm whose heuristic information is fuzzy information entropy based on membership functions. This paper concludes that fuzzy decision tree is more accurate to describe driver behavior at signalized intersection than logistic regression model.

Due to the short laser wavelength, almost all practical targets are rough. Surface elevations in rough targets will result in layovers in synthetic aperture ladar (SAL). High resolution SAL image with layovers will be different from the target picture taken by incoherent tools as digital camera. To investigate the layovers in SAL image, a simplified mathematical model is built by optics diffraction theory and a laboratory SAL is setup using 1550 nm tunable laser source. Layovers in SAL images, in both theoretical simulation and experimental demonstra- tion, are carefully observed. Detailed results on various targets are illustrated.

Urban Traffic Flow Guidance System (UTFGS) may cause the overreaction and concentration of travelers and lead to the phenomenon of Braess Paradox. The paper develops a constrained K-shortest paths algorithm within a dynamic restricted searching area in consideration of realistic road network spatial distribution features. Through the test with the microscopic transportation simulation tool VISSIM, the algorithm could not only decrease the searching scale but also efficiently balance the traffic flow in the net and avoid the phenomenon of Braess Paradox.

A detailed description and analysis of the methods of travel time estimation based on the data collected by loop coil and floating car were made. The main factors influencing the accuracy of the abovementioned two methods were clearly defined, and the experiment was designed to make quantization analysis of these influencing factors. Based on this analysis, the applicable conditions of the two methods were discussed. The influencing factors were grouped and classified, the weighting fusion method was applied to the two results of the abovementioned estimations, and the distribution principle for optimal weighted value was analyzed. At last, the abovementioned fusion method was verified by the experimental data. The result was encouraging.

This paper aims at the traffic flow agglomeration effect characteristics and rapid evacuation requirement in sudden disaster; operation time of intraregional boundaries traffic signal coordination was presented firstly. Then intraregional boundaries intersection group dynamic subdivision and consolidation method based on relative similarity degree and similarity coefficient of adjacent intersections was put forward. As to make the traffic control strategy adapt to traffic condition of different intraregional boundaries intersection groups, this paper proposes an intraregional boundaries traffic signal coordination and optimization technology based on organic computing theory. Finally, this paper uses Delphi 7.0, MapX, and Oracle developing a software package, combined with Paramics V6 Simulator to validate the methods of this paper. The result shows that it can obviously improve disaster affected regional traffic signal control efficiency which reduces average traffic delay by 30–35%, decreases vehicle queue by more than 20% and reduces evacuation time more than 13.06%.

Short-term traffic flow prediction is one of the most important issues in the field of adaptive traffic control system and dynamic traffic guidance system. In order to improve the accuracy of short-term traffic flow prediction, a short-term traffic flow local prediction method based on combined kernel function relevance vector machine (CKF-RVM) model is put forward. The C-C method is used to calculate delay time and embedding dimension. The number of neighboring points is determined by use of Hannan-Quinn criteria, and the CKF-RVM model is built based on genetic algorithm. Finally, case validation is carried out using inductive loop data measured from the north–south viaduct in Shanghai. The experimental results demonstrate that the CKF-RVM model is 31.1% and 52.7% higher than GKF-RVM model and GKF-SVM model in the aspect of MAPE. Moreover, it is also superior to the other two models in the aspect of EC.

To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM) model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface). The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.

Short-time traffic flow prediction is necessary for advanced traffic management system (ATMS) and advanced traveler information system (ATIS). In order to improve the effect of short-term traffic flow prediction, this paper presents a short-term traffic flow multistep prediction method based on similarity search of time series. Firstly, the landmark model is used to represent time series of traffic flow data. Then the input data of prediction model are determined through searching similar time series. Finally, the echo state networks model is used for traffic flow multistep prediction. The performance of the proposed method is measured with expressway traffic flow data collected from loop detectors in Shanghai, China. The experimental results demonstrate that the proposed method can achieve better multistep prediction performance than conventional methods.

The shortcomings of existing studies on the optimal location model of emergency resource and characteristics of multi-objective on location were analyzed. The dynamic characteristics of emergency needs were considered. And there are three main objects: the maximum of emergency rescue efficiency, minimum of construction cost and fairness of emergency rescue. Based on the above, a multi-objective emergency resource location optimization model was proposed to optimize the positions of supply centers as well as their scale. The assumptions and constraints of the model were clarified. In view of the different emergency needs of various disasters, the proposed basic model was improved. Basic efficacy coefficient algorithm and unitcost utility algorithm were proposed to solve the model. An example was used to verify the model and algorithms. The result of the experiment behaved rationally gave credibility to the location optimization model.

The violating traffic rules adventure will be taken when the non-motor driven traffic unit has waited so long that it exceeded the red light bearing. At this time, the intersection direction in motor vehicles at the end of the green light are eager to cross the intersection and accelerate in the green light time and, accompanied by the line of sight keep out, are now vulnerable to serious traffic accidents. At night, with most of the intersection signal control is the yellow light flashing, the vehicle speed is high, and a non-motor traffic unit has a greater risk to cross the street. In view of the above type analysis braking process, this study constructs the collision model of the intersection between non-motor driven traffic units and motor vehicles and designs a collision warning algorithm process and early warning system. Finally, an intersection test system was conducted in Changchun; the experiment results show that the system has strong reliability.

In the process of predicting link travel time, the difficultly of handling high dimensional and nonlinear data consistently poses problems to researchers. Because the single least squares support vector machine cannot handle these issues, a prediction method based on wavelet package analysis and least square support vector machine was proposed to forecast link travel time. The verification results obtained from VISSIM simulation data show that the link travel time prediction method is better and has definite application value.

Emergency resources allocation is essential to the emergency rescue effectiveness, and it has become a research focus for emergency rescue. This paper proposes a multiresource dynamic allocation model of emergency rescues and corresponding solving method. The object of the proposed model is to maximize the overall emergency rescue effectiveness of allocated resources and minimize the allocating costs of resources. The model considers the dynamic nature that the casualties of trapped victims change over time. At last, a numerical example is presented to test the model and its algorithm.

For the current problem of urban traffic congestion, the topology structure is proposed in this paper, based on GIS using cultural algorithm to solve the shortest path problem. The simulation results show that the actual optimal path of the improved algorithm is superior to the traditional optimal path algorithm in speed and accuracy.

This paper proposes a topological analysis of urban transit system based on a functional representation network constructed from the urban transit system in Beijing. The representation gives a functional view on nodes named a transit line. Statistical measures are computed and introduced in complex network analysis. It shows that the urban transit system forms small-world networks and exhibits properties different from random networks and regular networks. Furthermore, the topological properties of the transit-line network are investigated to get some useful conclusions for public transportation engineering.

With the development of hardware for on-board navigation equipment, more and more functions such as 3D map route guidance are applied for assisting driving. It is difficult to realize lane-level route guidance because of the accuracy of single global positioning system (GPS) receiver. On the basis of modeling of 3D digital maps, a lane-level positioning method was presented combined with virtual differential GPS with a single GPS receiver, height aiding, and collision detecting technique in this paper. The process of map matching was divided into two steps in order to get lane-level position. At the first step, the single GPS parameters were amended through virtual differential technology and height aiding technology in order to improve the precision. Then a method of lane-level map matching was implemented in 3D digital map based on the collision detection technology. Tested by DGPS data, the method was proven to fulfill the demands of vehicle navigation systems.

UTCS (Urban Traffic Control System) and UTGS (Urban Traffic Guidance System) are two main subsystems of traffic management system. In this paper, traffic optimal control model and quasi-system optimal dynamic traffic assignment model are used. Then, the dynamic cooperation optimizes the results alternatively until the results are fitted to both UTCS and UTGS. In the process of dynamic cooperation, one guidance cycle consists two close control cycles, using the second control cycle parameters to calculate the next guidance cycle parameters, this cooperation can ensure UTCS and UTGS follow the real-time traffic flow dynamically. It also ensures UTGS strategy continuity and dynamic cooperation of UTCS with UTGS. The simulation result proved that the dynamic cooperation in this paper is practical and feasible. The study provides theory and method guide for real cooperation of UTCS with UTGS application system development.

A multi-objective emergency resource scheduling model with transportation capacity constraint is proposed to raise multi-depot emergency resources scheduling efficiency and reduce casualties and property losses. In the proposed model, the time-variation of casualties is considered, and the maximum amount of effective relief commodities is the first objective. And the minimum transportation cost for emergency resources scheduling is also an important objective. During practical emergency rescue, multiple transportation means and their cost and capacity are main constraints. Moreover, the distribution of emergency in different depots influences strongly the scheduling of emergency resources. All of this has been discussed in the proposed model, and it is verified by an example. Experiment indicates that the proposed model is coincident with the practical emergency rescue.

Considering the equilibrium theory, this paper presented a new optimal velocity function (desired velocity), and discussed its formation and validity in detail. Further, we established an improved dynamic model based on the well accepted "stimulus response" pattern. Finally, we performed parameters calibration and model validation with the experimental data. The results showed that the improved model’s theoretical simulation results are in better agreement with the experimental results in both acceleration even speed and deceleration process, without unrealistic acceleration appearance in existing car-following models.

Traffic information has been dynamically provided by variable message signs (VMS), on-board equipment, traffic radio etc. in urban traffic flow guidance system (UTFGS) to help balance the traffic flow in the net, however, the impacts have not been well evaluated by taking the daily OD demand fluctuation in to consideration. Therefore, from discussing the impact of dynamic traffic information on driver's choice behavior and pointing out the key factors need to be considered, the paper proposes a realistic evaluation method of dynamic traffic information in considering of OD demand fluctuation and carries out a real urban network test for a week to show the possibility that the information provided in UTFGS may lead to a increase in total travel time. To sum up, it is confirmed that dynamic traffic information provision would not be effective under regular traffic condition except at the beginning of a peak; meanwhile, the benefit arises in unusual traffic condition caused by incidents.

In the traditional traffic control system, there is no coordination between different regions. This paper analyses the significance of coordination of the region boundary, brings out the condition for coordination and proposes two traffic control situation discrimination models of region boundary. After that, a dynamic hierarchical coordination control model of region boundary is proposed. Finally, a simulation test is carried out to validate the dynamic hierarchical coordination model with the help of VISSIM 4.2. Through evaluation index comparison of the traditional traffic control and the coordination model, it is concluded that the dynamic hierarchical coordination model is more efficient and produces better traffic control benefit than the traditional traffic control system.

On the basis of the concept of abnormal incidents, a detailed analysis of the influences on the state of urban traffic was introduced. Based on the characteristics of urban traffic under abnormal incidents, the principles of emergency evacuation strategy to be followed were set, and then, emergency evacuation plan development process and emergency management organization process were proposed. Finally, in order to improve traffic management as well as decrease the loss, the lack of existing conditions disposing abnormal incidents was analyzed and the content to be further built was put forward, which is essential for protecting urban safety and social stability.

For the problem of emergency traffic organization, designed the architecture of traffic emergency organization and command support system. Firstly analysised the emergency transportation organizational processes in-depth, and then put forward the route and possible projects of emergency traffic organization program. Finally, designed a traffic organization and command support system, and requested the system structure and function, and definitude the flow of traffic organization and command.

Aiming at the phenomenon of road traffic accident frequency, a method of road traffic accidents causes analysis based on data mining was put forward. First analyzed the related attributes and causes of road traffic accidents. Then introduced two kinds of basic theory of data mining : rough sets theory and the theory of association rules. Finally proposed the method of road traffic accidents causes analysis based on data mining. Using the method of traffic data analysis, can improve the road traffic safety management level effectively.

This paper presents a method called Event-based Incremental Update of Spatial-Temporal Database. By studying the event-based incremental update of spatial-temporal database, proposed event-based incremental information model, including incremental information modeling and the description method of incremental information based on XML, established the overall framework of the incremental update, including: event queue, spatial-temporal database, 3 agencies, 2 rules, and described the process of its implementation.

Vehicle-grade traffic information selecting type based on floating cars plays a significant role when it was under the influence of emergency accidents, and map matching (MM) is the key technology of this type. In this paper, against the problems of current MM method, we proposed a novel MM method based on road incremental updating data. This method was carried out through network topology which updated according to roads' dynamic changes, and it could solve real-time MM process by an effective candidate links identification method, at the same time, the MM method put forward applied parallel roads reverse recognition method on the link matching. And on the junction, this method took delay matching method and optimal path selection method to overcome the MM complexity caused by intersections and main side roads in large-scale urban traffic network. Experiment results showed that the MM method proposed in this paper can perform high MM precision in large-scale and complicated road network under emergency accidents.

Large-scale emergency events bring a lot of effect to people's ordinary life, so it is necessary to provide fast and effective location-allocation analysis information for emergency traffic evacuation and succor. In this issue, some related models based on location-allocation analysis are introduced into emergency traffic evacuation field. Considering the actual situation and character of emergency traffic evacuation, we develop maximum covering models which are applied to emergency traffic evacuation and its optimized algorithm. Finally, we discuss some feasible solution strategies, and then get the large-scale emergency traffic evacuation plan, provide dependable decision-making support for succor.

Collaborative optimization of multiple traffic management systems is the most effective way to improve rescue and evacuation ability of an urban when emergency accidents happen. In this paper, we made an analysis on function and information relevance of common traffic management systems, after that, each system was taken as an order parameter that prompt traffic flow to change from disorder to order, and an order degree function was founded. Based on these, we proposed a hierarchical collaborative optimization model of multiple traffic management systems. Also, according to occur pots and severity of traffic incidents, we raised specific collaborative optimization implementing scheme. The result realized resource sharing and integrated scheduling, thus it can strengthen the cooperation between urban traffic management systems under traffic incidents powerfully.

The paper first illustrates the meaning of division and integration of traffic control sub-zones. Then, it categorizes all the division rules and decides to make the distance+cycle rule as the resort of division rule in the paper. The essay utilizes the cycle rule to select a certain intersection as the critical intersection of a sub-zone. At the same time, it establishes a probing model based on the cycle and generates the sub-zones with the help of the cycle rule. Lastly, the paper simulates the division and integration process based on nine intersections with the VISSIM. After division and integration of sub-zones with the distance+cycle principle, the average queuing length of all nine intersections reduces by 35.8 percent compared to isolated control strategy, and the average delay of those intersections reduces by 41 percent compared to isolated control strategy.

With the enlargement of IVIS's market penetration rate, the phenomenon of Braess paradox will appear. To avoid this phenomenon and lessen congestion, this paper analyses the causes of this phenomenon in detail, proposes a solution method based on Multi-agent system (MAS). This paper proposes conceptual solution architecture of three layers of agents and gives the corresponding algorithm. The system makes the IVIS agent and Traffic Guidance Center (TGC) agent coordinate with each other and gives the driver a both system optimum and user optimum route during traveling. Thus, vehicles are assigned evenly on the whole road network, so as to better avoid the phenomenon of Braess paradox. Then, this paper uses the Open Cybele version 1.2-agent infrastructure and TRIPS to validate the feasibility of the advised MAS and the algorithm. As a result, such system and algorithm prove to be a better method to avoid Braess paradox and alleviate congestion.