An expert system for air traffic flow management

An expert system for the air traffic flow management (ATFM) problem is presented. Two main prototypes have been constructed, one for timetable rescheduling that attempts to modify airline timetables to smooth traffic peaks at airports during rush-hours and another for centralized flow control that works to forecast the place, time and magnitude of the congestion and to propose mitigative actions. Simulations for the Brazilian ATFM, including the principal 14 airports, show the potential usefulness of the expert system.     

Integrating mobile agent technology with multi-agent systems for distributed traffic detection and management systems

Agent technology is rapidly emerging as a powerful computing paradigm to cope with the complexity in dynamic distributed systems, such as traffic control and management systems. However, while a number of agent-based traffic control and management systems have been proposed and the multi-agent systems have been studied, to the best of our knowledge, the mobile agent technology has not been applied to this field. In this paper, we propose to integrate mobile agent technology with multi-agent systems to enhance the ability of the traffic management systems to deal with the uncertainty in a dynamic environment. In particular, we have developed an IEEE FIPA compliant mobile agent system called Mobile-C and designed an agent-based real-time traffic detection and management system (ABRTTDMS). The system based on Mobile-C takes advantages of both stationary agents and mobile agents. The use of mobile agents allows ABRTTDMS dynamically deploying new control algorithms and operations to respond unforeseen events and conditions. Mobility also reduces incident response time and data transmission over the network. The simulation of using mobile agents for dynamic algorithm and operation deployment demonstrates that mobile agent approach offers great flexibility in managing dynamics in complex systems.     

An ontological model to support communications of situation-aware vehicles

In an Intelligent Transport System (ITS) environment, the communication component is of great importance to support interactions between vehicles and roadside infrastructure. Previous studies have focused on the physical capability and capacity of the communication technologies, but the equally important development of suitable and efficient semantic content for transmission received notably less attention. Ontology is one promising approach for context modelling in ubiquitous computing environments, and in the transport domain it can be used both for context modelling and semantic contents for vehicular communications. This paper explores the development of an ontological model implementing relative geo-semantic information messages to support vehicle-to-vehicle communications. The proposed ontology model contains classes, objects, their properties/relations as well as some functions and query templates to represent and update the information of dynamic vehicles, inter-vehicle interactions and behaviour. This model was developed through a scenario enabling the evaluation of traffic conflict resolution approaches, by implementing a set of decision-making processes for intelligent vehicles. Given the scope of the proposed ontology modelling, it shows how vehicular communications can be used to update each vehicle’s context model. This work can be easily extended for more complex interactions among vehicles and the infrastructure.     

上海轨道交通清分系统架构中应用云计算技术的探讨

通过对上海轨道交通清分系统构架的现状分析,明确清分、线路中央计算机、车站计算机等系统之间业务功能的调整方向。根据云计算技术的特点,阐述在城市轨道交通自动售检票系统中如何建立私有云计算系统、不同服务层次服务的对象以及实施的技术路线,并提出城市轨道交通自动售检票系统云计算构架的设想与模型。     

Validation of an agent based model using a participatory simulation gaming approach: The case of city logistics

Agent-based modeling is used for simulating the actions and interactions of autonomous entities aiming to assessing their effects on the system as a whole. At an abstract level, an agent-based model (ABM) is a representation of the many simple agents and interactions among them. The decision making of the agents is based on the rules given to them. In an ABM, the model output is the result of internal decision-making and may differ with alteration in the decision path. On the contrary, with the set of rules embedded in agents, their behavior is modeled to take a ‘certain action’ in a ‘certain situation’. It suggests that the internal decision making behavior of agents is truly responsible for the model output and thus it cannot be ignored while validating ABMs. This research article focuses on the validating agents’ behavior by evaluating decision-making processes of agents. For this purpose, we propose a validation framework based on a participatory simulation game. Using this framework we engage a human player (i.e. a domain stakeholder) to allow us to collect information about choices and validate the behavior of an individual agent. A proof-of-concept game is developed for a city logistics ABM to test the framework.     

Multi-agent simulation of individual mobility behavior in carpooling

Carpooling is an emerging alternative transportation mode that is eco-friendly and sustainable as it enables commuters to save time, travel resource, reduce emission and traffic congestion. The procedure of carpooling consists of a number of steps namely; (i) create a motive to carpool, (ii) communicate this motive with other agents, (iii) negotiate a plan with the interested agents, (iv) execute the agreed plans, and (v) provide a feedback to all concerned agents. In this paper, we present a conceptual design of an agent-based model (ABM) for the carpooling a that serves as a proof of concept. Our model for the carpooling application is a computational model that is used for simulating the interactions of autonomous agents and to analyze the effects of change in factors related to the infrastructure, behavior and cost. In our carpooling application, we use agent profiles and social networks to initiate our agent communication model and then employ a route matching algorithm, and a utility function to trigger the negotiation process between agents. We developed a prototype of our agent-based carpooling application based on the work presented in this paper and carried out a validation study of our results with real data collected in Flanders, Belgium.     

Monitoring Aircraft Turnaround Operations – Framework Development,Application and Implications for Airline Operations

Abstract

A real-time operation monitoring system – Aircraft Turnaround Monitoring System – is developed based on a system framework to monitor aircraft turnaround operations at an airport. Mobile computing devices (PDAs) and wireless network technology General Packet Radio Service (GPRS) are used to implement the real-time monitoring system for an airline. System implementation and test results indicate that real-time operation monitoring can potentially reduce delays occurring from airline operations. Proactive measures can be taken immediately by ground handling staff to reduce delays, once the risk of delays and potential delay propagation is identified. The availability of detailed operating data can help airlines identify the root delay causes from complex connections among aircraft, flight/cabin crew and passengers. In addition, these operating data also shed some light on the future development of aircraft routing algorithms in order to consider explicitly stochastic disruptions and delay propagation in airline schedule planning.     

A multi-agent architecture for cooperative inter-jurisdictional traffic congestion management

This paper describes , an innovative multi-agent architecture for the provision of real-time decision support to Traffic Operations Center personnel for coordinated, inter-jurisdictional traffic congestion management on freeway and surface street (arterial) networks. is composed of two interacting knowledge-based systems that perform cooperative reasoning and resolve conflicts, for the analysis of non-recurring congestion and the on-line formulation of integrated control plans. The two agents support incident management operations for a freeway and an adjacent arterial subnetwork and interact with human operators, determining control recommendations in response to the occurrence of incidents. The multi-decision maker approach adopted by reflects the spatial and administrative organization of traffic management agencies in US cities, providing a cooperative solution that exploits the agencies’ willingness to cooperate and unify their problem-solving capabilities, yet preserves the different levels of authority and the inherent distribution of data and expertise. The interaction between the agents is based on the functionally accurate, cooperative paradigm, a distributed problem solving approach aimed at producing consistent solutions without requiring the agents to have shared access to all globally available information. The cornerstone of this approach is the assumption that effective solutions can be efficiently obtained even when complete and up-to-date information is not directly available to the agents, thus reducing the need for complex data communication networks and synchronization time delays. The simulation-based evaluation of the system performance validates this assumption. The paper focuses on the distributed architecture of the agents and on their communication and decision making characteristics.     

Modeling the interaction between buses,passengers and cars on a bus route using a multi-agent system

This paper models part of a public transport network (PTN), specifically, a bus route, as a small-size multi-agent system (MAS). The proposed approach is applied to a case study considering a ‘real world’ bus line within the PTN in Auckland, New Zealand. The MAS-based analysis uses modeling and simulation to examine the characteristics of the observed system – autonomous agents interacting with one another – under different scenarios, considering bus capacity and frequency of service for existing and projected public transport (PT) demand. A simulation model of a bus route is developed, calibrated and validated. Several results are attained, such as when the PT passenger load is not close to bus capacity, this load has no effect on average passenger waiting time at bus stops. The model proposed can be useful to practitioners as a tool to model the interaction between buses and other agents.     

Large-scale dynamic transportation network simulation: A space-time-event parallel computing approach

This paper describes a computationally efficient parallel-computing framework for mesoscopic transportation simulation on large-scale networks. By introducing an overall data structure for mesoscopic dynamic transportation simulation, we discuss a set of implementation issues for enabling flexible parallel computing on a multi-core shared memory architecture. First, we embed an event-based simulation logic to implement a simplified kinematic wave model and reduce simulation overhead. Second, we present a space-time-event computing framework to decompose simulation steps to reduce communication overhead in parallel execution and an OpenMP-based space-time-processor implementation method that is used to automate task partition tasks. According to the spatial and temporal attributes, various types of simulation events are mapped to independent logical processes that can concurrently execute their procedures while maintaining good load balance. We propose a synchronous space-parallel simulation strategy to dynamically assign the logical processes to different threads. The proposed method is then applied to simulate large-scale, real-world networks to examine the computational efficiency under different numbers of CPU threads. Numerical experiments demonstrate that the implemented parallel computing algorithm can significantly improve the computational efficiency and it can reach up to a speedup of 10 on a workstation with 32 computing threads.     

Beyond tele-substitution: disaggregate longitudinal structural equations modeling of communication impacts

Information on the number and types of communication activities (including travel) engaged in over a period of four consecutive days, at two points in time about six months apart, was collected from 91 respondents in the context of the introduction of a community network to the city of Davis, California. Three major types of communication were measured: personal meetings (and in a separate but related measure, trips), transfer of an information object (in-house documents, regular mail, and express or overnight mail), and electronic (phone, fax, and e-mail). A system of structural equations was developed and estimated, expressing the number of instances of each type of communication at time 2 as a function of: the number of instances of each type at time 1, the elapsed time between measurements, and exogenous sociodemographic variables. All “own” lagged effects (that is, the effect of one communication type in wave 1 on the same type of communication in wave 2) were found to be positive and (except for information object delivery) highly significant. The “elapsed time” variable was always positive and (except for personal meetings and, in one model, information object delivery) significant; these effects indicate net generation of communication activities over time. Significant “cross” lagged effects (that is, the effect of one communication type in wave 1 on a different type in wave 2) were mostly positive, indicating the presence of some complementarity effects across modes. However, relationships specifically between electronic forms of communication and personal meetings or trips were not significant in either direction for the final models. Several exogenous variables were significant in logical ways.     

A Bayesian network approach for population synthesis

Agent-based micro-simulation models require a complete list of agents with detailed demographic/socioeconomic information for the purpose of behavior modeling and simulation. This paper introduces a new alternative for population synthesis based on Bayesian networks. A Bayesian network is a graphical representation of a joint probability distribution, encoding probabilistic relationships among a set of variables in an efficient way. Similar to the previously developed probabilistic approach, in this paper, we consider the population synthesis problem to be the inference of a joint probability distribution. In this sense, the Bayesian network model becomes an efficient tool that allows us to compactly represent/reproduce the structure of the population system and preserve privacy and confidentiality in the meanwhile. We demonstrate and assess the performance of this approach in generating synthetic population for Singapore, by using the Household Interview Travel Survey (HITS) data as the known test population. Our results show that the introduced Bayesian network approach is powerful in characterizing the underlying joint distribution, and meanwhile the overfitting of data can be avoided as much as possible.     

Enhanced high data rate communication system using embedded cooperative radar for intelligent transports systems

In maritime and aeronautical transports, intelligent systems such as AIS² or ADS-B³ are used for simultaneous location and data exchange. However nowadays, in guided transports domain, no commercial system is able to ensure the both functionalities. In this paper, we present the achievement of an original sensor allowing both localization and data communication inside the same system. They tend to improve reliability, safety and security on rails or facilitate new exploitation modes inside guided transports networks. Our laboratories, INRETS⁴ and DOAE⁵, achieved a mock-up of the radar system called CODIBDT⁶ the sensor is based on the principle of cooperative radar using a transponder inside targets. It uses a numerical correlation receiver and has a broad band of about 100 MHz for high data flow communications. An original coding technique, called 2πM,⁷ has been defined and implemented, which allows high data flow communication multiplexed with the localization functionality and ensure a multi-users access. This paper focuses on presenting simulations and experimental results, obtained with the realized mock-up in railway environment, in order to evaluate the system performances in terms of data flow, Bit Error Rate, computing time and complexity. The performances of the 2πM coding technique is compared to others techniques called SSS2⁸ and CPM⁹.     

A platoon based cooperative eco-driving model for mixed automated and human-driven vehicles at a signalised intersection

The advancements in communication and sensing technologies can be exploited to assist the drivers in making better decisions. In this paper, we consider the design of a real-time cooperative eco-driving strategy for a group of vehicles with mixed automated vehicles (AVs) and human-driven vehicles (HVs). The lead vehicles in the platoon can receive the signal phase and timing information via vehicle-to-infrastructure (V2I) communication and the traffic states of both the preceding vehicle and current platoon via vehicle-to-vehicle (V2V) communication. We propose a receding horizon model predictive control (MPC) method to minimise the fuel consumption for platoons and drive the platoons to pass the intersection on a green phase. The method is then extended to dynamic platoon splitting and merging rules for cooperation among AVs and HVs in response to the high variation in urban traffic flow. Extensive simulation tests are also conducted to demonstrate the performance of the model in various conditions in the mixed traffic flow and different penetration rates of AVs. Our model shows that the cooperation between AVs and HVs can further smooth out the trajectory of the latter and reduce the fuel consumption of the entire traffic system, especially for the low penetration of AVs. It is noteworthy that the proposed model does not compromise the traffic efficiency and the driving comfort while achieving the eco-driving strategy.     

Simulation studies of information propagation in a self-organizing distributed traffic information system

This paper investigates the feasibility of a self-organizing, completely distributed traffic information system based upon vehicle-to-vehicle communication technologies. Unlike centralized traffic information systems, the proposed system does not need public infrastructure investment as a prerequisite for implementation. Due to the complexity of the proposed system, simulation is selected as the primary approach in the feasibility studies. A simulation framework is built based on an existing microscopic traffic simulation model for the simulation studies. The critical questions for building the proposed market-driven system are examined both from communication requirements and traffic engineering points of view. Traffic information propagation both in freeway and arterial networks via information exchange among IVC-equipped vehicles is tested within the simulation framework. Results on the probability of successful IVC and traffic information propagation distance obtained from the simulation studies are generated and analyzed under incident-free and incident conditions for various roadway formats and parameter combinations. Comparisons between the speed of the incident information wave and the speed of the corresponding traffic shock wave due to the incident are analyzed for different scenarios as the most crucial aspect of the information propagation as a potential foundation for application in such a decentralized traffic information system.     

Intermodal transport in freight distribution: a literature review

There has been significant growth in research on intermodal transport in freight distribution since the 1990s. Differentiating itself from previously published literature reviews, this paper evaluates the current state of this research using Systematic Literature Review methodology. The complementary aims are: (a) to identify the research lines developed and to propose a criterion for classifying the literature, and (b) to discuss the empirical evidence that identifies existing interrelationships. The analysis has enabled three main lines of research to be identified. The first research line, basic principles of intermodal transport, groups together works related to the definition of intermodal transport and the results obtained using this transportation system. The second, improvements to the way that intermodal transport systems work, frames elements and variables that impact intermodal transport systems’ logistics efficiency, such as quality of service, information and communication systems, and freight planning and linkages among system operators to provide an adequate service. Finally, the third line, intermodal transport system modelling, identifies the main variables used to optimise these transport systems, the different focuses and approaches used in modelling, and the advantages and disadvantages of each focus. These research lines take in more specific sublines that incorporate articles that develop related research questions. Lastly, the discussion of the content of each of these research sublines enables us to identify gaps in the literature and comment on directions for future research.     

Multi-agent fuzzy signal control based on real-time simulation

In this paper a traffic signal control system based on real-time simulation, multi-agent control scheme, and fuzzy inference is presented. This system called HUTSIG is closely related to the microscopic traffic simulator HUTSIM, both have been developed by the Helsinki University of Technology. The HUTSIM simulation model is used both for off-line evaluation of the signal control scheme and for on-line modeling of traffic situations during actual control. Indicators are derived from the simulation model as input to the control scheme. In the presented control technique, each signal operates individually as an agent, negotiating with other signals about the control strategy. Here the decision making of the agents is based on fuzzy inference that allows a combination of various aspects like fluency, economy, environment and safety. The fuzzy implementation of the HUTSIG signal control system is developed under the FUSICO-project at Helsinki University of Technology.     

Perceptions of new electronic media for business communication

A model of communications media choice in business organizations is formulated based upon the results of exploratory interviews and the consumer choice literature. Choice is modelled as a function of organizational characteristics, individual characteristics, communication activity characteristics, communication initiator-recipient relationships and perceptions and feelings about available media. Hypotheses concerning media perceptions are developed from the exploratory interviews and tested using survey results from two firms in the Chicago region. The methodology developed in this research provides a useful approach to exploring preferences for and choices of communication media. As a paradigm for future research, it can be used to extend our understanding of communications media usage.     

线阵CCD油管螺纹测量系统程序开发

基于线阵CCD的油管外螺纹参数检测系统是一种先进的非接触式工业检测系统,包括硬件和软件两部分。针对该系统的重要组成部分———控制、计算程序的设计和开发进行了详细的阐述。该程序的开发基于Windows 2000,开发工具为C Builder 6.0,包括数据采集与存储、滤波、边界点选取、参数计算等多个模块。程序功能完整,界面友好,控制精确,计算结果能够满足测量系统的精度要求。     

Transportation — “Current on-board vehicle systems”

The paper reviews the current situation on-board microprocessor applications. It first describes the aspects of vehicle technology and performance that are the focus for on-board computing equipment, from engine management systems through to fully intergrated driver decision support. In the second section a wider perspective is taken by examining the interaction of the vehicle and its environment. The third and final section of the paper considers elements of communication which permit extensive transmission of vehicle and journey data for public and private use. The conclusion identifies factors which will influence the speed with which further applications will be adopted.