Ebook: Information Technology and Intelligent Transportation Systems

The 2nd International Conference on Information Technology and Intelligent Transportation Systems (ITITS 2017) was held in Xi'an on June 10–11, 2017, and provided a platform for professionals and researchers from industry and academia to present and discuss recent advances in the field of information technology and intelligent transportation systems. Intelligent transport systems vary in technologies applied, from basic management systems to more advanced application systems. Information technology plays a large role in intelligent transportation systems, including wireless communication; computational technologies; floating car data/cellular data: sensing technologies and video vehicle detection. The technology of intelligent transportation systems includes theoretic and applied topics such as emergency vehicle notification systems; automatic road enforcement; collision avoidance systems and some cooperative systems.

The conference will foster cooperation among organizations and researchers involved in these fields, invite well-known professors world-wide to further explore these topics, and discuss in-depth technical issues with the presenters. All papers were reviewed by 3–4 referees and the program chairs of the conference committee made a selection based on the score of each paper. This year, ITITS 2017 received more than 200 papers from 4 countries and 65 papers were accepted finally. ITITS 2017 was sponsored by Shaanxi Computer Society, Chang'an University and co-sponsored by Xi'an University of Technology, Northwestern Polytechnical University, CAS, Shaanxi Sirui Advanced Materials CO. LTD and Special Aircraft Engineering Research Institute.

We would like to thank the authors of papers and the reviewers for the expertise and contributions. The assistance provided by the conference committee members and all those involved in the organization of conference is gratefully acknowledged.

The lack of web services semantic description leads to inadequate services search results from services registries. We propose a novel approach to semantically cluster web services, and group the similar web services based on the services similarity matrix so as to improve services discovery and composition. The proposed approach uses WordNet-Similarity to compute the similarity of terms of service name, description, I/O parameters, and then re-weights the services vector to decide the similarity of services. The method based on web service semantics we introduced has an acceptable result.

The probability of flight conflict is increased because of the increasing of flight flow and uncertainty of flight route. Considering the problem that redundant operation which caused by a large number of non-related targets. A preprocessing algorithm before conflict detection was proposed. Aircrafts within the surveillance scope of Automatic Dependent Surveillance-Broadcast (ADS-B) IN were divided into 26 different regions, and the correlation between targets was distinguished by special rule of each region. Then the correlated targets were further processed, but uncorrelated ones were blocked. So the calculation of conflict analysis for surveilling surrounding targets was decreased. Above all, the processing principle that security first should be followed, and rather false alarm but never leakage alarm. Finally, the necessity and validity of the proposed algorithm is examined by using Monte Carlo experiment. The simulation results show that not less than 30% of 30 random objects are blocked. The proposed algorithm is effective and accurate for detecting the correlation of them.

Aiming at the lane change behavior recognition requirements of lane change warning system, natural lane change samples were captured by using a test vehicle. Steering angle and distance between vehicle and lane mark were used as characteristic parameters of lane change behavior. Support vector machine (SVM) method was used to establish recognizing model of lane change. According to the high-low identification accuracy of the different time window, 1.2 seconds was selected to be as the window length .The sample data in each time window were filtered by Kalman filter. Then, by using principal component analysis method, the first and second principal components were extracted from all principal components to be as the new variable. Support vector machine-bayesian filter identification model was built to identify general lane change behavior. Final recognition results show that the recognition rate for the real lane change samples can reach more than 95% and the proposed model can also meet the real time and reliability requirements of lane change warning system.

According to the actual operation data, the operation cost of a typical medium range single aisle commercial transport aircraft will increase 30 dollars if it stays on ground for one more minute, leading to 1 million dollars increase in its life cycle cost. For the purpose of decreasing cost, airlines require the airplanes can turnaround within a short time period. Boarding and deplaning time accounts for more than half of the total turnaround time, however the current estimation method uses empirical data and cannot evaluate the effects from the aircraft design parameters. An aircraft turnaround time estimation model is developed based on the discrete time simulation, which deems boarding and deplaning as a dynamic process. The interaction between one passenger and other passengers, and the interaction between passengers and cabin are taken into account. The model has been compared with the boarding and deplaning data suggested by aircraft manufacturers. A twin aisle airplane is studied and the sensitivity of cabin design parameters is investigated. The results show that the model is suitable for aircraft designers to determine aircraft design parameters to meet the constraint regarding to aircraft turnaround time.

Wireless Mesh Network is a new kind of wireless communication technology widely used in near-field communication, has obvious application advantage in position information sharing service. The paper introduce WMN's technical characteristics used in the fields of Wireless Personal Area Network, analyze WMN's application advantage compared with Ad hoc Network, discuss four kinds of WPAN's traditional application mechanism based on WMN. Based above, describe a new kind of WPAN standard based on WMN called IEEE 802.15.5. Then, put forward a WMN's application case used in vehicle navigation and positioning, has important practical guiding significance of instructing WMN used in the fields of position information sharing service.

In order to evaluate the various performance indexes of extended range electric vehicles, a parameter matching is proposed for a certain extended range electric vehicle. Based on Matlab / Simulink, on the basis of ADVISOR series hybrid electric vehicle model, modify and optimize vehicle dynamics models, motor models and battery models, and propose the control strategy, the dynamic and economic performance was researched in UDDS cycle condition. The results shown that when the motor torque is 0~200Nm, the engine torque output is 55~100Nm, the efficiency of the battery is kept above 90% under the CYC_UDDS cycle condition of the electric vehicle. With the original vehicle dynamics unchanged, the emissions performance and fuel consumption rates have been improved.

For providing a good condition of measuring, the gravimeter gyro-stabled platform plays an important part in the gravimeter system. By adopting the pure-inertial and the all-digital controlling technology of real-time leveling, the gravimeter gyro-stabled platform will be directed primarily towards isolating the angular motion of the carrier, and keeping the sensitive axis of the gravimeter parallel with the plumb line all the time. In the sea condition, the gravimeter gyro-stabled platform has a low precision in the disturbing of low frequency of sea waves, this paper introduces a leveling algorithm based on Mixed Sensitivity. By adopting a reasonable leveling bandwidth, performance bound function, controller weighting function and bounded uncertainty function, we achieve an optimal control to the leveling loop via the algorithm.

This paper introduces the technical characteristics of ZigBee and Bluetooth communication protocol, the development trend and some applications in the field of intelligent traffic vehicle communication. This paper discusses the condition that traffic information is sent from the road side to the vehicle and from the vehicle to the road side through ZigBee and Bluetooth communication technology. The model is established to analyze the corresponding transmission frequency and simulate it. Expect to make a positive role in promoting the development of intelligent transportation technology.

TLD is a real-time long-term tracking system that decomposes the tasks into three components: tracking, learning and detection. The learning estimates detector's errors and updates it to avoid these errors in the future. However, Current implementation of TLD trains only the detector and the tracker stay fixed. As a result, the tracker makes always the same errors. In our paper, we develop a novel training method which combines naive Bayes classifier with the optical flow based on the TLD algorithm to train the tracker. The proposed algorithm mainly consists of two stages: one stage for training and a second stage for tracking. For the training stage, we sample some positive samples near the current target location and negative samples far away from the object center to update the classifier from the current frame. For the tracking stage, Optical flow tracker estimates the object's motion between consecutive frames under the assumption that the frame-to-frame motion is limited and the object is visible. And then we sample a set of image patches, using the classifier to each patch. We determine the target with the maximal classification score. With these definitions, we conduct extensive experiments and comparisons for the proposed method. The comparisons and experiments well demonstrate the effectiveness of our work.

To face the changes of network security situation in industrial control field of power industry and the security needs of important information system and meet the requirements for special network security tools, we carry out the top design work of network attack and defense simulation range in power industry and build a network security test simulation platform which include the power monitoring system, an important information system which similar to the real production environment. In this paper, we list recent developments concerning the construction of network security attack and defense range system in power monitoring system at home and abroad. According to the overall scheme of power monitoring system for security. We found a highly simulated range environment containing all of these parts–sending, changing, matching, usage, scheduling, information, design the network security attack and defense platform architecture and ensure the safe, reliable and stable operation of the power system effectively.

EFI engine has the characteristics of DFCO. Sliding on the uphill with gear can save fuel and ensure safe driving. In this paper, a fuel saving and safety driving guidance system applied on the commercial vehicle is proposed. The uphill and downhill road information is predicted based on GPS and GIS. The fuel-efficient and safe speed tips are provided for drivers according to the models with the vehicle's structural parameters and running status parameters. In this paper, the taxiing equations of uphill and downhill are established, the taxiing distance is calculated according to the current vehicle speed and the slope. The vehicle's geographical position is obtained by GPS. The distance between the vehicle and the ramp top is calculated. Energy conservation calculation model and safety evaluation model are established based on energy conservation law. On a road of 8 km, it was found that the braking frequency was reduced by 50%, the energy dissipated by braking was reduced by 2.15% and fuel consumption was reduced by 3.62% after using the system.

With the rapid development of regional integration, the adjacent city mobility is becoming increasingly active, adjacent city masses have new requirements to set the public transport operation passenger line of the adjacent city. To grasp the passenger transport demand of the passenger transportation route in the adjacent city is an important prerequisite for the study of the adjacent city passenger transportation. Based on the analysis of passenger flow characteristics and influencing factors, the paper analyses the models and methods for forecasting passenger demand, according to the characteristics of passenger flow, a method to predict the trend of passenger flow and passenger flow in the public transport operation passenger line of the adjacent city is determined. It has important reference value for the construction of the adjacent city transport network, transport capacity and transportation policy.

Based on Euler-Bernoulli beam and structure dynamics theory and by means of numerical experimentation, taking a single-damaged simply supported beam as the research object, this paper obtains the frequencies of the beam under the conditions of different damage positions and damage degrees. With the concept of damage factor, rate of change of frequency(RCF), mean value of RCF(MRCF), amplitude of RCF(ARCF), and the ratio of RCF(RRCF), the paper researches frequency characteristics of a simply supported beam. The results show that the frequency and RCF sensitivities are related to damage degree and damage position, and that the RRCF sensitivities are relate to damage position only. The influence of damage degree on the frequency is greater than that of damage position, and that the RCF value variation of the beam is not a monotonic function with the increase of modal order when the damage position and damage degree are constant. The frequency and RCF of the beam at different damage position are oscillation curves, and the oscillation times and amplitude value of RCF curve varies with the change of modal order.

In this paper, an extended car-following model with consideration of the combination effect in heterogeneous urban traffic flow with slow and fast vehicles is proposed. The combination effect means the order of vehicles in a heterogeneous flow matters, since a fast vehicle would degenerate to a middle state between a fast vehicle and a slow vehicle when it follows a slow vehicle. Specifically, we consider three types of vehicle combinations in the urban traffic flow, namely fast vehicle following fast vehicle (FF), fast vehicle following slow vehicle (FS), and slow vehicle following fast/slow vehicle (SX). Linear stability analysis is conducted to obtain stability criterion, from which we can conclude that the higher penetration of the FS combination can increase the stability of traffic flow.

The article designs an APP-based intelligent service system based on the current university library seat utilization. As a development tool that connects the users with libraries, this system offers online reservation and other people-oriented services (e.g. information push and star-level services). In addition, the system also provides fully functional services with the combination of the QR code scanning and unlocking technology, raising the seat utilization rate to the most possible extent.

An expressway traffic incident severity detection model is established in this paper, which can effectively detect the traffic incidents and their severity. By analyzing the relationship between the severity of freeway traffic incidents and the number of lanes, flow, speed and duration of traffic events in the event lane, the following conclusions are drawn: (1) The traffic flow of traffic incident lane and non-traffic incident lane has multi-mode, sudden jump and other abrupt theoretical features When a traffic incident occurs; (2) The severity of traffic accidents controls the degree of sudden and sudden jump of traffic incident lane and non-traffic incident lane. Based on catastrophe theory, this paper proposes a discriminant model of traffic accident severity based on traffic flow velocity and flow rate as independent variables. The measured data of expressway traffic events verifies the effectiveness of the proposed model.

This paper deals with a method and system of scenario information model based on electric power scene. The construction method includes the following steps: (1) Collecting scene information, (2) Scenario information classification, (3) Information model construction, (4) The formation of power operations situational awareness system and scene applications. Based on the scenario information model of electric power operation scene, this paper describes the entity from the six dimensions of human, auxiliary equipment, environment, time, task and service, and finds out the relationship between entity, instance and entity, and constructs information model, To achieve the power of the task of service discovery, interpretation, query and unified scheduling, to provide the necessary services.

A reasonable location planning of emergency facility is an important work in the emergency management of urban rail transit. Based on the complex network theory, we propose a reliable emergency facility location model that aiming to improve the coverage level for the nodes with high vulnerability. This is mainly due to that the nodes with the different vulnerabilities in the network have different requirements for coverage level. We research on the node vulnerability of urban rail transit using complex network theory, and identifies the key nodes in the network before location planning. The vulnerable nodes in the network will be given higher weight to improve their coverage level in the location model, so that the equilibrium and efficiency of emergency are enhanced. To efficiently solve the model, we develop a heuristic based on Lagrangian relaxation. Finally, the model and heuristic are applied to the emergency facility location in urban rail transit (URT) network in Nanjing, China. The proposed method is effective and robust, and contributes greatly to the performance of emergency facility location planning in emergency management of URT.

In the Orthogonal Frequency Division Multiplexing (OFDM) system, a channel estimation algorithm based on least squares (LS) and forward error correction (FEC) iteration was proposed for the shortcoming of traditional LS algorithm. In this paper, LS algorithm and FEC algorithm were introduced, and the improved algorithm was explained in detail. The improved algorithm used the FEC correction performance to correct channel estimation results. Simulation results showed that the improved algorithm can effectively improve the performance of channel estimation.

Improving operation efficiency of container terminal, is important for terminal operators. Meanwhile, the air pollution problem is increasingly serious in container terminal, with the establishment of the Emission Control Areas (ECAs) of China in 2015, environmental protection pressure is increasing to terminal operators. In order to comply with the ECA regulation, optimizing the operation efficiency, reducing air pollution emissions, which, is an urgent problem to terminal management in China. This paper based on the characteristic of Container Terminal Operation System (CTOS), including berth allocation problem, truck dispatching problem, and yard allocation problem, establishes the architecture of CTOS based on the Multi Agents System. A model and simulation on a port container terminal is built on the JADE platform to support the decision-making of container terminal, which can reduce air pollution emissions in port, and maintain service levels. CTOS allows the container terminal operator to be more flexible in their decision to meet the ECA regulation.

This paper investigates flight delay propagation in the air transport networks. An integrate flight-based susceptible-infected-susceptible (FSIS) model is generated using the mechanism of epidemic spreading. Furthermore, the propagation probability in the FSIS model is analyzed through the regression model and later applied to China Easter Airline. The results show that propagation probability varies from different routes, which related to the flight frequency of airports, route distances, scheduled buffer times, and propagated delay times, and the FSIS model can efficiently reveal the process of flight delay propagation, and evaluate the number of delayed flights.

In allusion to the application of LCL filter in three-phase voltage rectifier circuit, this paper will apply LCL filter to battery energy storage system, compared with traditional single LC filter, we can use smaller inductance value to achieve better filtering effect, eliminating the problems caused by conventional filters, such as large volume, high cost, poor dynamic response of system. According to the requirements of the design of the whole system, by analyzing the circuit principle and control strategy of the system, using the three-phase voltage type PWM rectifier (VSR) and bidirectional DC/DC converter, through a simple design method of the parameters of the LCL filter, ultimately, the correctness of the theoretical analysis is verified by simulation and experiment and realize the constant power charging and discharging of the battery.

Knapsack problem is a typical combinatorial optimization problem, which has attracted wide attention because of its simple description, difficult solution and wide application background. For the knapsack problem, we proposed an improved quantum evolutionary algorithm. In this algorithm, the qubits are initialized according to the value densities of their corresponding items, the angle of Q-gate is determinated through direct comparison between the quantum chromosome and the optimal solution, random crossover method is taken to share information among chromosomes, and Hε gate is used to prevent from premature convergence. Finally, experiment demonstrates the effectiveness of the algorithm.

Objects detection is not only an important research direction in computer vision, but also the basis of object tracking and behavior detection. In this paper, we analyze the characteristics and principles of Binarized normed gradients (BING) algorithm, and propose an objects detection algorithm based on multi-BING feature model. At first, the proposed algorithm uses K-means clustering algorithm to cluster the training data, and then trains each category of images to establish the corresponding BING feature model. At the detection stage, multiple BING feature models are respectively used for testing. We collected all the detected results from all models as the final detection results. Experimental results demonstrate that the proposed algorithm effectively improves the object detection rate (DR) under various overlaps at the expense of a small amount of time by generating a small set of high-quality proposals.