Xisong Dong

Cyber-physical-social system in intelligent transportation

A cyber-physical system (CPS) is composed of a physical system and its corresponding cyber systems that are tightly fused at all scales and levels. CPS is helpful to improve the controllability, efficiency and reliability of a physical system, such as vehicle collision avoidance and zero-net energy buildings systems. It has become a hot R&D and practical area from US to EU and other countries. In fact, most of physical systems and their cyber systems are designed, built and used by human beings in the social and natural environments. So, social systems must be of the same importance as their CPSs. The indivisible cyber, physical and social parts constitute the cyber-physical-social system (CPSS), a typical complex system and its a challengeable problem to control and manage it under traditional theories and methods. An artificial systems, computational experiments and parallel execution (ACP) methodology is introduced based on which data-driven models are applied to social system. Artificial systems, i.e., cyber systems, are applied for the equivalent description of physical-social system (PSS). Computational experiments are applied for control plan validation. And parallel execution finally realizes the stepwise control and management of CPSS. Finally, a CPSS-based intelligent transportation system (ITS) is discussed as a case study, and its architecture, three parts, and application are described in detail.

Parallel Traffic Management System and Its Application to the 2010 Asian Games

Field data are important for convenient daily travel of urban residents, reducing traffic congestion and accidents, pursuing a low-carbon environment-friendly sustainable development strategy, and meeting the extra peak traffic demand of large sporting events or large business activities, etc. To meet the field data demand during the 2010 Asian (Para) Games held in Guangzhou, China, based on the novel Artificial systems, Computational experiments, and Parallel execution (ACP) approach, the Parallel Traffic Management System (PtMS) was developed. It successfully helps to achieve smoothness, safety, efficiency, and reliability of public transport management during the two games, supports public traffic management and decision making, and helps enhance the public traffic management level from experience-based policy formulation and manual implementation to scientific computing-based policy formulation and implementation. The PtMS represents another new milestone in solving the management difficulty of real-world complex systems.

Parallel Traffic Management System Helps 16th Asian Games

To overcome public transportation problems during the 16th Asian Games held in Guanhzhou China, a PtMS (Parallel Transportation Management System), a novel application of Intelligent Transportation Systems, was introduced for effective and convenient traffic management. Results show that PtMS has successfully enhanced public traffic management, raising it from experience-based policy formulation plus manual implementation to scientific computing-based policy generation plus implementation with intelligent systems.

A Kind of Novel ITS Based on Space-Air-Ground Big-Data

Based on the big-data collected from Space-Air-Ground, i.e. Space means satellite, Air means helicopter, the key technologies of novel ITS (Intelligent Transportation System) are investigated, including data acquisition sensor, dynamic data transmission, massive data storage, multi-source data fusion, massive data mining and analysis, etc. On this basis, the cloud computing platform of novel ITS is designed, including Space-Air-Ground bigdata acquisition & transmission subsystem, cloud computing platform, intelligent transportation application & service subsystem. With the help of the data visualization, data prediction, and decision making, the complete traffic big-data set including people (passenger, driver), vehicle, and road traffic environment, can create their core addedvalues. The applications of novel ITS include: providing transportation data services for traffic enterprise and business users, such as customized mining, and specific industry analysis; providing accurate transportation information services for the citizen; providing business model for all levels of users, such as data visualization and customized services.

Parallel Bus Rapid Transit (BRT) operation management system based on ACP approach

Bus Rapid Transit (BRT) is an effective way to increase urban traffic capacity. But its operation and scheduling optimization are difficult. In this article, Parallel BRT Operation Management System (PBOMS) is constructed based on ACP approach. It can detect the passengers quantity on station platforms in real-time, traffic flow besides stations or at intersections, and the queuing length of vehicles on the road lines. It can provide short-term passenger and traffic saturation prediction in order to arrange transportation management more accurately to relieve the congestion. It can assess, improve and optimize the emergency management during holidays, public events, accidents and other emergency situations. It can improve the quality of real-time scheduling functions by using the measurement results detected from traffic videos, and so on. This system has been piloted in Guangzhou Zhongshan Avenue BRT, which was applied for BRTs monitoring, warning, forecasting, emergency management, real-time scheduling and other purposes, to improve Guangzhou BRTs smoothness, safety, efficiency and reliability.

Research on bus rapid transit (BRT) and its real-time scheduling

With the fast development of the economy, the urban traffic demands increases rapidly, Bus rapid transit (BRT) system, a new type and high efficient bus operator system and a comprehensive mass transit system between the metro and regular bus systems, can alleviate traffic congestion, reduce resident traffic cost effectively, and improve transportation quality and efficiency, with its advantages becomes an effective way to improve urban traffic status. In this article, the definition, major elements, advantages, functions and development of BRT are provided, and a new real-time scheduling is given which is going to be applied to the Zhongshan Avenue BRT system in Guangzhou China.

Service composition execution optimization based on state transition matrix for cloud computing

It is difficult to select a composite service with the lowest actual executing cost using the existing methods for QoS-aware service composition in cloud computing. By analyzing the dynamic execution process of composite service with state transition matrix, this paper proposes a new QoS aware optimal service composition method. In view of the effect of composite services reliability on the composite service performance, the method regards the cost averaged for one time of successful execution of a composite as its actual executing cost, and then selects the composite services with the aim of minimizing the composite service execution cost. The simulation result shows that the proposed method is superior to other methods in execution cost.

Continuous Travel Time Prediction for Transit Signal Priority Based on a Deep Network

It has been recognized by many researchers that accurate bus travel time prediction is critical for successful deployment of traffic signal priority (TSP) systems. Although there exist a lot of studies on travel time prediction for Advanced Traveler Information Systems (ATIS), this problem for TSP purpose is a little different and the amount of literature is limited. This paper proposes a deep learning based approach for continuous travel time prediction problem. Parameters of the deep network are fine-tuned following a layer-by-layer pre-training procedure on a dataset generated by traffic simulations. Variables that may affect continuous travel time are selected carefully. Experiments are conducted to validate the performance of the proposed model. The results indicate that the proposed model produces prediction with mean absolute error less than 4 seconds, which is accurate enough for TSP operations. This paper also reveals that, except for obvious factors like speed, travel distance and traffic density, the signal time when the prediction is made is also an important factor affecting travel time.

Intelligent Technologies and Systems of Material Management

Material Management is the engine that drives its Supply Chain and Logistics of manufacturing enterprise or any other organization. With the economy development and technical progress, many Logistics are transforming from 1PL and 2PL and 3PL to 4PL and 5PL continuously, and many manufacturers are transforming from Mass Production to Mass Customization, and then to new manufacturing modes all the time, like Cloud Manufacturing, Social Manufacturing etc. So, Material Management should continuously apply the latest ICT & intelligent technologies or systems, like Barcode, RFID, IoT (Internet of Things ), GPS/BeiDou Navigation Satellite System, Cloud Computing , Big data , Parallel Control and Management , to realize its transformation and upgrade coordinately with its Supply Chain and Logistics.

A Parallel Transportation Management and Control System for Bus Rapid Transit Using the ACP Approach

Bus rapid transit (BRT) has been proved to be an effective tool to improve mass transit services. However, BRTs adaptive operations like management and scheduling under different scenarios are too complicated to implement using traditional methods. The ACP approach, which is based on holism and complex system theory and consists of artificial systems (A), computational experiments (C) and parallel execution (P), offers an efficient new method to cope with these complex systems, including BRT. In this paper, the parallel transportation management and control system for BRT (PTMS-BRT) is presented, which is designed and implemented using the ACP approach. PTMS-BRT integrates such functions as BRTs monitoring, warning, forecasting, incident management, and real-time scheduling, to provide its operations smoother, safer, more efficient, and reliable. It has been piloted successfully in Guangzhou BRT to demonstrate it as another successful example of parallel transportation systems.