865 resultados para Vehicule routing


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Passenger flow studies in airport terminals have shown consistent statistical relationships between airport spatial layout and pedestrian movement, facilitating prediction of movement from terminal designs. However, these studies are done at an aggregate level and do not incorporate how individual passengers make decisions at a microscopic level. Therefore, they do not explain the formation of complex movement flows. In addition, existing models mostly focus on standard airport processing procedures such as immigration and security, but seldom consider discretionary activities of passengers, and thus are not able to truly describe the full range of passenger flows within airport terminals. As the route-choice decision-making of passengers involves many uncertain factors within the airport terminals, the mechanisms to fulfill the capacity of managing the route-choice have proven difficult to acquire and quantify. Could the study of cognitive factors of passengers (i.e. human mental preferences of deciding which on-airport facility to use) be useful to tackle these issues? Assuming the movement in virtual simulated environments can be analogous to movement in real environments, passenger behaviour dynamics can be similar to those generated in virtual experiments. Three levels of dynamics have been devised for motion control: the localised field, tactical level, and strategic level. A localised field refers to basic motion capabilities, such as walking speed, direction and avoidance of obstacles. The other two fields represent cognitive route-choice decision-making. This research views passenger flow problems via a "bottom-up approach", regarding individual passengers as independent intelligent agents who can behave autonomously and are able to interact with others and the ambient environment. In this regard, passenger flow formation becomes an emergent phenomenon of large numbers of passengers interacting with others. In the thesis, first, the passenger flow in airport terminals was investigated. Discretionary activities of passengers were integrated with standard processing procedures in the research. The localised field for passenger motion dynamics was constructed by a devised force-based model. Next, advanced traits of passengers (such as their desire to shop, their comfort with technology and their willingness to ask for assistance) were formulated to facilitate tactical route-choice decision-making. The traits consist of quantified measures of mental preferences of passengers when they travel through airport terminals. Each category of the traits indicates a decision which passengers may take. They were inferred through a Bayesian network model by analysing the probabilities based on currently available data. Route-choice decision-making was finalised by calculating corresponding utility results based on those probabilities observed. Three sorts of simulation outcomes were generated: namely, queuing length before checkpoints, average dwell time of passengers at service facilities, and instantaneous space utilisation. Queuing length reflects the number of passengers who are in a queue. Long queues no doubt cause significant delay in processing procedures. The dwell time of each passenger agent at the service facilities were recorded. The overall dwell time of passenger agents at typical facility areas were analysed so as to demonstrate portions of utilisation in the temporal aspect. For the spatial aspect, the number of passenger agents who were dwelling within specific terminal areas can be used to estimate service rates. All outcomes demonstrated specific results by typical simulated passenger flows. They directly reflect terminal capacity. The simulation results strongly suggest that integrating discretionary activities of passengers makes the passenger flows more intuitive, observing probabilities of mental preferences by inferring advanced traits make up an approach capable of carrying out tactical route-choice decision-making. On the whole, the research studied passenger flows in airport terminals by an agent-based model, which investigated individual characteristics of passengers and their impact on psychological route-choice decisions of passengers. Finally, intuitive passenger flows in airport terminals were able to be realised in simulation.

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Collisions among trains and cars at road/rail level crossings (LXs) can have severe consequences such as high level of fatalities, injuries and significant financial losses. As communication and positioning technologies have significantly advanced, implementing vehicular ad hoc networks (VANETs) in the vicinity of unmanned LXs, generally LXs without barriers, is seen as an efficient and effective approach to mitigate or even eliminate collisions without imposing huge infrastructure costs. VANETs necessitate unique communication strategies, in which routing protocols take a prominent part in their scalability and overall performance, through finding optimised routes quickly and with low bandwidth overheads. This article studies a novel geo-multicast framework that incorporates a set of models for communication, message flow and geo-determination of endangered vehicles with a reliable receiver-based geo-multicast protocol to support cooperative level crossings (CLXs), which provide collision warnings to the endangered motorists facing road/rail LXs without barriers. This framework is designed and studied as part of a $5.5 m Government and industry funded project, entitled 'Intelligent-Transport-Systems to improve safety at road/rail crossings'. Combined simulation and experimental studies of the proposed geo-multicast framework have demonstrated promising outcomes as cooperative awareness messages provide actionable critical information to endangered drivers who are identified by CLXs.

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Forming peer alliances to share and build knowledge is an important aspect of community arts practice, and these co-creation processes are increasingly being mediated by the internet. This paper offers guidance for practitioners who are interested in better utilising the internet to connect, share, and make new knowledge. It argues that new approaches are required to foster the organising activities that underpin online co-creation, building from the premise that people have become increasingly networked as individuals rather than in groups (Rainie and Wellman 2012: 6), and that these new ways of connecting enable new modes of peer-to-peer production and exchange. This position advocates that practitioners move beyond situating the internet as a platform for dissemination and a tool for co-creating media, to embrace its knowledge collaboration potential. Drawing on a design experiment I developed to promote online knowledge co-creation, this paper suggests three development phases – developing connections, developing ideas, and developing agility – to ground six methods. They are: switching and routing, engaging in small trades of ideas with networked individuals; organising, co-ordinating networked individuals and their data; beta-release, offering ‘beta’ artifacts as knowledge trades; beta-testing, trialing and modifying other peoples ‘beta’ ideas; adapting, responding to technological disruption; and, reconfiguring, embracing opportunities offered by technological disruption. These approaches position knowledge co-creation as another capability of the community artist, along with co-creating art and media.

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For industrial wireless sensor networks, maintaining the routing path for a high packet delivery ratio is one of the key objectives in network operations. It is important to both provide the high data delivery rate at the sink node and guarantee a timely delivery of the data packet at the sink node. Most proactive routing protocols for sensor networks are based on simple periodic updates to distribute the routing information. A faulty link causes packet loss and retransmission at the source until periodic route update packets are issued and the link has been identified as broken. We propose a new proactive route maintenance process where periodic update is backed-up with a secondary layer of local updates repeating with shorter periods for timely discovery of broken links. Proposed route maintenance scheme improves reliability of the network by decreasing the packet loss due to delayed identification of broken links. We show by simulation that proposed mechanism behaves better than the existing popular routing protocols (AODV, AOMDV and DSDV) in terms of end-to-end delay, routing overhead, packet reception ratio.

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This special issue of Networking Science focuses on Next Generation Network (NGN) that enables the deployment of access independent services over converged fixed and mobile networks. NGN is a packet-based network and uses the Internet protocol (IP) to transport the various types of traffic (voice, video, data and signalling). NGN facilitates easy adoption of distributed computing applications by providing high speed connectivity in a converged networked environment. It also makes end user devices and applications highly intelligent and efficient by empowering them with programmability and remote configuration options. However, there are a number of important challenges in provisioning next generation network technologies in a converged communication environment. Some preliminary challenges include those that relate to QoS, switching and routing, management and control, and security which must be addressed on an urgent or emergency basis. The consideration of architectural issues in the design and pro- vision of secure services for NGN deserves special attention and hence is the main theme of this special issue.

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Process models define allowed process execution scenarios. The models are usually depicted as directed graphs, with gateway nodes regulating the control flow routing logic and with edges specifying the execution order constraints between tasks. While arbitrarily structured control flow patterns in process models complicate model analysis, they also permit creativity and full expressiveness when capturing non-trivial process scenarios. This paper gives a classification of arbitrarily structured process models based on the hierarchical process model decomposition technique. We identify a structural class of models consisting of block structured patterns which, when combined, define complex execution scenarios spanning across the individual patterns. We show that complex behavior can be localized by examining structural relations of loops in hidden unstructured regions of control flow. The correctness of the behavior of process models within these regions can be validated in linear time. These observations allow us to suggest techniques for transforming hidden unstructured regions into block-structured ones.

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Process models are usually depicted as directed graphs, with nodes representing activities and directed edges control flow. While structured processes with pre-defined control flow have been studied in detail, flexible processes including ad-hoc activities need further investigation. This paper presents flexible process graph, a novel approach to model processes in the context of dynamic environment and adaptive process participants’ behavior. The approach allows defining execution constraints, which are more restrictive than traditional ad-hoc processes and less restrictive than traditional control flow, thereby balancing structured control flow with unstructured ad-hoc activities. Flexible process graph focuses on what can be done to perform a process. Process participants’ routing decisions are based on the current process state. As a formal grounding, the approach uses hypergraphs, where each edge can associate any number of nodes. Hypergraphs are used to define execution semantics of processes formally. We provide a process scenario to motivate and illustrate the approach.

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During invasion and metastasis, cancer cells interact closely with the extracellular matrix molecules by attachment, degradation, and migration. We demonstrated previously the local degradation of fluorescently labeled gelatin matrix by cancer cells at invasive membrane protrusions, called invadopodia. Using the newly developed quantitative fluorescence-activated cell sorting-phagocytosis assay and image analysis of localized degradation of fluorescently labeled matrix, we document here that degradation and site- specific removal of cross-linked gelatin matrix is correlated with the extent of phagocytosis in human breast cancer cells. A higher phagocytic capacity is generally associated with increasing invasiveness, documented in other invasion and motility assays as well. Gelatin phagocytosis is time and cell density dependent, and it is mediated by the actin cytoskeleton. Most of the intracellular gelatin is routed to actively acidified vesicles, as demonstrated by the fluorescent colocalization of gelatin with acidic vesicles, indicating the intracellular degradation of the phagocytosed matrix in lysosomes. We show here that normal intracellular routing is blocked after treatment with acidification inhibitors. In addition, the need for partial proteolytic degradation of the matrix prior to phagocytosis is demonstrated by the inhibition of gelatin phagocytosis with different serine and metalloproteinase inhibitors and its stimulation by conditioned medium containing the matrix metalloproteinases MMP-2 and MMP-9. Our results demonstrate that phagocytosis of extracellular matrix is an inherent feature of breast tumor cells that correlates with and may even directly contribute to their invasive capacity. This assay is useful for screening and evaluating potential anti-invasive agents because it is fast, reproducible, and versatile.

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To date, designed topologies for DC-AC inversion with both voltage-buck and boost capabilities are mainly focused on two-level circuitries with extensions to three-level possibilities left nearly unexplored. Contributing to this area of research, this paper presents the design of a number of viable buck-boost three-level inverters that can also support bidirectional power conversion. The proposed front-end circuitry is developed from the Cuk-derived buck-boost two-level inverter, and by using the "alternative phase opposition disposition" (APOD) modulation scheme, the buck-boost three-level inverters can perform distinct five-level line voltage and three-level phase voltage switching by simply controlling the active switches located in the designed voltage boost section of the circuits. As a cost saving option, one active switch can further be removed from the voltage-boost section of the circuits by simply re-routing the gating commands of the remaining switches without influencing the ac output voltage amplitude. To verify the validity of the proposed inverters, Matlab/PLECS simulations were performed before a laboratory prototype was implemented for experimental testing.

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Recurrent congestion caused by high commuter traffic is an irritation to motorway users. Ramp metering (RM) is the most effective motorway control means (M Papageorgiou & Kotsialos, 2002) for significantly reducing motorway congestion. However, given field constraints (e.g. limited ramp space and maximum ramp waiting time), RM cannot eliminate recurrent congestion during the increased long peak hours. This paper, therefore, focuses on rapid congestion recovery to further improve RM systems: that is, to quickly clear congestion in recovery periods. The feasibility of using RM for recovery is analyzed, and a zone recovery strategy (ZRS) for RM is proposed. Note that this study assumes no incident and demand management involved, i.e. no re-routing behavior and strategy considered. This strategy is modeled, calibrated and tested in the northbound model of the Pacific Motorway, Brisbane, Australia in a micro-simulation environment for recurrent congestion scenario, and evaluation results have justified its effectiveness.

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Generally wireless sensor networks rely of many-to-one communication approach for data gathering. This approach is extremely susceptible to sinkhole attack, where an intruder attracts surrounding nodes with unfaithful routing information, and subsequently presents selective forwarding or change the data that carry through it. A sinkhole attack causes an important threat to sensor networks and it should be considered that the sensor nodes are mostly spread out in open areas and of weak computation and battery power. In order to detect the intruder in a sinkhole attack this paper suggests an algorithm which firstly finds a group of suspected nodes by analyzing the consistency of data. Then, the intruder is recognized efficiently in the group by checking the network flow information. The proposed algorithm's performance has been evaluated by using numerical analysis and simulations. Therefore, accuracy and efficiency of algorithm would be verified.

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This study quantifies the motivators and barriers to bikeshare program usage in Australia. An online survey was administered to a sample of annual members of Australia’s two bikeshare programs based in Brisbane and Melbourne, to assess motivations for joining the schemes. Non-members of the programs were also sampled in order to identify current barriers to joining bikeshare. Spatial analysis from Brisbane revealed residential and work locations of non-members were more geographically dispersed than for bikeshare members. An analysis of bikeshare usage in Melbourne showed a strong relationship between docking stations in areas with relatively less accessible public transit opportunities. The most influential barriers to bikeshare use related to motorized travel being too convenient and docking stations not being sufficiently close to home, work and other frequented destinations. The findings suggest that bikeshare programs may attract increased membership by ensuring travel times are competitive with motorized travel, for example through efficient bicycle routing and priority progression and, by expanding docking station locations, and by increasing the level of convenience associated with scheme use. Convenience considerations may include strategic location of docking stations, ease of signing up and integration with public transport.

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We present a new approach for creating and implementing an ad-hoc underwater acoustic sensor network based on connecting a small processor to the serial port of a commercial CDMA acoustic modem. The processor acts as a "node controller" providing the networking layer that the modems lack. The ad-hoc networking protocol is based on a modified dynamic source routing (DSR) approach and can be configured for maximising information throughput or minimising energy expenditure. The system was developed in simulation and then evaluated during field trials using a 10 node deployment. Experimental results show reliable multi-hop networking under a variety of network configurations, with the added ability to determine internode ranges to within 1.5 m for localisation.

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Network topology and routing are two important factors in determining the communication costs of big data applications at large scale. As for a given Cluster, Cloud, or Grid system, the network topology is fixed and static or dynamic routing protocols are preinstalled to direct the network traffic. Users cannot change them once the system is deployed. Hence, it is hard for application developers to identify the optimal network topology and routing algorithm for their applications with distinct communication patterns. In this study, we design a CCG virtual system (CCGVS), which first uses container-based virtualization to allow users to create a farm of lightweight virtual machines on a single host. Then, it uses software-defined networking (SDN) technique to control the network traffic among these virtual machines. Users can change the network topology and control the network traffic programmingly, thereby enabling application developers to evaluate their applications on the same system with different network topologies and routing algorithms. The preliminary experimental results through both synthetic big data programs and NPB benchmarks have shown that CCGVS can represent application performance variations caused by network topology and routing algorithm.

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In this paper, we introduce a path algebra well suited for navigation in environments that can be abstracted as topological graphs. From this path algebra, we derive algorithms to reduce routes in such environments. The routes are reduced in the sense that they are shorter (contain fewer edges), but still connect the endpoints of the initial routes. Contrary to planning methods descended from Disjktra’s Shortest Path Algorithm like D , the navigation methods derived from our path algebra do not require any graph representation. We prove that the reduced routes are optimal when the graphs are without cycles. In the case of graphs with cycles, we prove that whatever the length of the initial route, the length of the reduced route is bounded by a constant that only depends on the structure of the environment.