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A simulation model of crowd evacuation based on the cellular automata is introduced. The implementation on GPU is focused in details. This model takes advantage of GPU to complete part of computing by certain allocation. Taking Guangzhou Tianhe stadium as an example, the model shows that the performance of computing has been significantly improved by parallel computing technique of GPU, which obtained nearly 15 times speed-up.

Information of Activities location is critical for traffic simulation based on activity. To replace time-consuming manual acquisition, this paper proposes an information extraction method based on ontology and frequent subtree to acquire place-related information from the Web automatically. A destination selection model based on Nested Logit is established to use this information in traffic simulation. To verify the method and model, information of places within Zhongguancun area is acquired from the Web, and then experiments with uniform design are carried out on artificial transportation systems and regression analysis is done.

Dynamic changes and uncertainty in traffic environments directly spawned lots of strategies about traffic signal control (TSC). Meanwhile, the differences in the traffic environment and demand of control have a significant impact on the performance of strategies about TSC. In order to enable dynamic selection of the most appropriate TSC agents for each specific traffic state in urban traffic transportation system, we firstly propose a survey about urban TSC, which helps us to understand the characteristics of TSC strategies. This survey focuses on the traffic environment about the application of TSC and the demand of TSC. Then, based on the aforementioned survey, we propose one recommendation mechanism for agent-based distributed and adaptive platform for transportation systems to adapt to traffic dynamic characteristic.

Artificial Transportation Systems (ATS) provide a comprehensive perspective to study actual transportation systems, which are a kind of open and complex giant system referring to diverse engineering and social disciplines. To make use of achievements from related research fields, ontology for ATS is constructed in this paper. Besides conceptual model involved in modeling and applications of ATS, the compatibility with other ontology is considered. Further, an ontological knowledge base with SOA (Service-Oriented Architecture) is designed to manage information and knowledge in ATS. The architecture and interfaces of the knowledge base are presented. Benefit from this, construction and applications of ATS can be conducted on a uniform information and knowledge platform. A case study about traffic jam pattern is demonstrated.

The AGV decision making subsystem directly affects the performance of the vehicle. The information it uses can be classified into “Objective Information” and “Subjective Information” two major groups. To fuse these two kinds of information, we propose a novel framework for decision in this paper. In the framework, an effective method based on the modified Dempster-Shafer evidence theory was used to make the fusion of the objective and subjective information. In addition, we used fuzzy logic to quantify the subjective information. The experiment shows the proposed method can solve the vagueness and uncertainty of information and achieve decision exactly and credibly.

For spectators and public transport demand during the 16th Asian Games and the first Asian Para Games held in Guangzhou in 2010, Aided Decision-Making System of Public Transportation Management for Guangzhou Asian Games had been developed to support public transport management decision. It can help public transport managers to enhance the level of public transport management from experience-based formulation and manual implementation to scientific computation-based formulation and automatic implementation by intelligent systems, to guarantee the traffic demand effectively during the games, and to improve the management of public transportation significantly.

At present service oriented resource configuration analysis and optimization research only takes computing resources into account. It fails to meet the requirement that enterprise run optimally in cloud manufacturing and SOE. This paper analyzes the relation between enterprise services and computing/manufacturing resources. Then the artificial enterprise model is built. Then various resource configuration schemes are loaded in it and the computational experiments are done to run these schemes. By comparing the experiment results the optimal scheme is obtained for the enterprise. Thus the demand of the enterprise is satisfied.

Bus Rapid Transit (BRT) is an effective way to improve urban traffic status. But, because of its complexity, it is difficult in its operation management and scheduling. In this article, based on ACP approach, Parallel BRT System is constructed, which can detect real-time passenger flow at stations, traffic flow at stations and intersections and queuing length of vehicles on the road; to provide short-term passenger and traffic saturation prediction in order to timely arrange transportation management and relieve congestion; to assess, improve and optimize the emergency management of holidays, events, accidents and other emergencies; to improve the quality of real-time scheduling functions based on the measurement results detected from videos, and so on. This system has been applied in Guangzhou Zhongshan Avenue BRT, which was applied for BRT's monitoring, warning, forecasting, emergency management, real-time scheduling and other needs, to guarantee BRT's smooth, safety, efficiency and reliability.

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 passenger's 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 BRT's monitoring, warning, forecasting, emergency management, real-time scheduling and other purposes, to improve Guangzhou BRT's smoothness, safety, efficiency and reliability.

To improve the operation efficiency and service levels of Bus Rapid Transit (BRT) systems, we propose a novel realtime BRT signal priority approach through two-stage green extension. For social justices, we control traffic signal lights under the people first principle after constructing BRT Internet of Things. This requests us to collect enough traffic information related to BRT vehicles, social vehicles, and in-vehicle passengers. We use DGPS/DR/MM to perceive BRT vehicles and use video cameras to perceive social vehicles and BRT passenger numbers. The perception data are then transmitted to the intersection signal controller through 3G wireless networks and optical fiber communication. In the application service layer, according to minimum green time, passive priority green time, and maximum green time, we divide green extension into two sequential stages based on different rules. In this way, we could balance traffic demands of BRT vehicles and social vehicles from each approach, and realize real-time BRT signal priority in a general sense.

Public traffic is required for the convenient travel, reducing traffic congestion and accidents, low-carbon, environmental protection, sustainable development, and traffic demand of giant sports and large business activities, etc. For public transport demand of the 16th Asian Games and the 2010 Asian Para Games held in Guangzhou in 2010, based on ACP approach, Parallel Public Transport Management And Control System (PPTMS) for Guangzhou Asian Games had been developed to support management decision of public transport. This system can help public transport managers to improve and enhance significantly the level of public transport management in Guangzhou, from experience-based formulation and manual implementation to scientific computation-based formulation and automatic implementation with intelligent systems, to guarantee the traffic demand effectively during the two Games.

BackgroundArtemisinin and its derivatives were reported to possess strong regulatory effects on inflammation and autoimmune diseases. This study was designed to examine the therapeutic effects and underlying mechanisms of SM934, a water-soluble artemisinin analogue, on lupus-prone female NZB × NZW F(1) mice.Methodology/principal findingsNZB/W F(1) mice were treated orally with SM934 for 3 or 6 months respectively to investigate the effect on clinical manifestations and immunological correlates. To further explore the mechanisms of SM934, ovalbumin (OVA)-immunized or interferon (IFN)-γ-elicited C57BL/6 mice were used. In vivo, treatment with SM934 for 3 or 6 months significantly delayed the progression of glomerulonephritis and increased the survival rate of NZB/W F(1) mice. Clinical improvement was accompanied with decreased Th1-related anti-double-strand DNA (dsDNA) IgG2a and IgG3 Abs, serum interleukin (IL)-17, and increased Th2-related anti-dsDNA IgG1 Ab, serum IL-10 and IL-4. SM934 treatment also suppressed the accumulation of effector/memory T cells, induced the apoptosis of CD4(+) T cells, while enhancing the development of regulatory T cells in NZB/W F(1) mice. In addition, SM934 treatment promoted the IL-10 production of macrophages from NZB/W F(1) mice, OVA-immunized C57BL/6 mice and IFN-γ-elicited C57BL/6 mice. In vitro, SM934 enhanced IL-10 production from primary macrophages stimulated with IFN-γ.Conclusions/significanceThe results of this study demonstrated that artemisinin analogue SM934 had therapeutic effects on lupus-prone female NZB/W F(1) mice by inhibiting the pathogenic helper T cell development and enhancing anti-inflammatory cytokine IL-10 production.

Traffic congestion leads to problems like delays, decreasing flow rate, and higher fuel consumption. Consequently, keeping traffic moving as efficiently as possible is not only important to economy but also important to environment. Traffic system is a large complex nonlinear stochastic system. Traditional mathematical methods have some limitations when they are applied in traffic control. Thus, computational intelligence (CI) technologies gain more and more attentions. Neural Networks (NNs) is a well developed CI technology with lots of promising applications in traffic signal control (TSC). In this paper, a neural network (NN) based signal controller is designed to control the traffic lights in an urban traffic road network. Scenarios of simulation are conducted under a microscopic traffic simulation software. Several criterions are collected. Results demonstrate that through online reinforcement training the controllers obtain better control effects than the widely used pre-time and actuated methods under various traffic conditions.

With the advantage of simulating the details of a transportation system, the “microsimulation” of a traffic system has long been a hot topic in the Intelligent Transportation Systems (ITS) research. The Cellular Automata (CA) and the Multi-Agent System (MAS) modeling are two typical methods for the traffic microsimulation. However, the computing burden for the microsimulation and the optimization based on it is usually very heavy. In recent years the Graphics Processing Units (GPUs) have been applied successfully in many areas for parallel computing. Compared with the traditional CPU cluster, GPU has an obvious advantage of low cost of hardware and electricity consumption. In this paper we build an MAS model for a road network of four signalized intersections and we use a Genetic Algorithm (GA) to optimize the traffic signal timing with the objective of maximizing the number of the vehicles leaving the network in a given period of time. Both the simulation and the optimization are accelerated by GPU and a speedup by a factor of 195 is obtained. In the future we will extend the work to large scale road networks.

Road traffic load balancing can avoid network congestion and improve traffic efficiency. This paper proposes a method of dynamic route guidance based on Maximum Flow Theory to balance traffic load of road network. A modified Ford-Fulkerson algorithm is used for searching the optimal route. In addition, the algorithm is implemented by using MapReduce primitives, which introduces Cloud Computing Platform for large-scale traffic network guidance. Computational experimental environment is built by integrating Artificial Transportation Systems (ATS) and Hadoop. Results in ATS and performances on Hadoop show that the method proposed can improve the traffic situation effectively.

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.

Objective SM934, an artemisinin derivative, possesses potent antiproliferative and antiinflammatory properties. The aim of this study was to examine the effects and explore the mechanisms of SM934 to treat autoimmune disease in lupus-prone female MRL/lpr mice. Methods In vitro, the effects of SM934 on the activation of polyclonal CD4+ T cells and the differentiation of naive CD4+ T cells were examined. In vivo, the preventative or therapeutic effects of SM934 in MRL/lpr mice were investigated. Ex vivo, the mechanisms of treatment were explored according to the immunologic correlates of disease. Results In vitro, SM934 inhibited interferon-γ (IFNγ) and interleukin-17 (IL-17) production from polyclonal CD4+ T cells activated by T cell receptor engagement and the differentiation of naive CD4+ T cells into Th1 and Th17 cells, but not Treg cells. In vivo, 12-week-old MRL/lpr mice treated with SM934 for 4 weeks showed significantly ameliorated proteinuria and renal lesion severity; decreased levels of blood urea nitrogen, serum IFNγ, and serum anti–double-stranded DNA antibodies; decreased spleen size; and a lower percentage of CD3+B220+CD4−CD8− T cells; 16-week-old MRL/lpr mice treated with SM934 for 8 weeks avoided severe proteinuria and survived longer. Ex vivo, SM934 treatment elevated the percentage of Treg cells, inhibited the development of Th1 and Th17 cells, and impeded the comprehensive activation of STAT-1, STAT-3, and STAT-5 proteins in splenocytes. Conclusion Taken together, the results of this study demonstrated that the artemisinin analog SM934 had therapeutic effects in lupus-prone female MRL/lpr mice by inhibiting both Th1 cell and Th17 cell responses. Moreover, this study indicated that both IFNγ and IL-17 are required for the elicitation and development of murine lupus.

This paper presents a novel automatic and dynamic camera calibration algorithm based on traffic visual surveillance. The algorithm can automatically calibrate the intrinsic and extrinsic parameters of camera, and offer enough guarantee to extract traffic real-time parameters. This paper firstly indicates the significance of applying automatic and dynamic calibration algorithm to intelligent transportation system, then establishes a mathematical model of calibration parameters between camera image and actual road. The algorithm is established from three view points, which are description, flow chart and algorithm description. Afterward this paper describes the experimental method and result based on this novel algorithm. Finally this paper indicates wide application foreground of this algorithm in intelligent transportation system.

Agents and interactions between them are two key roles in modeling artificial transportation systems. This paper presents a formal theory to describe interactions between agents, which, together with the well developed models to describe components as agents, completes the first step towards establishing the formal structure for artificial transportation systems. By describing individual agents and the interactions between them as independent simple sequence processes and directive communication channels respectively, we models the whole system as one sequential communications system, which is one special type of Petri net. The theory is flexible enough to model diversified interactions between agents, and the resultant model possesses favorable properties. A case study of modeling road network has been conducted for the purpose of illustration

R-tree is widely used in indexing of multidimensional and spatial data. When it is used in environment of COW (Cluster Of Workstations), to the best of our knowledge it is used in Master-Slave mode or its variants. Under this mode when an entry is accessed, it must be locked. The higher the locked entry in the R-tree, the more transactions will be stopped from accessing all the offspring of it. Therefore the degree of concurrency is paralyzed. Moreover, the Master will become the hotspot in parallel processing which can worsen the overall performance. In this paper we present an upgraded parallel R-tree model which is suitable for the environment of COW. Our parallel R-tree can not only balance the load among processors but also decrease the conflicts of intra-and inter-transactions. We can successfully prevent the emergence of hot spot from accessing the R-tree. The detailed searching algorithm and the load shipping algorithm of this parallel R-tree are given. Lastly we provide experimental results which show that the parallel R-tree performs well as expected.