Investigations of Agents, Transportation and Data Communication Networks

车辆交通拥堵影响着人们日常生活的许多方面。它造成时间浪费、经济损失、燃料消耗增加和污染。由于资金、空间和环境的限制，扩展道路网络并不是解决拥堵、可靠性和安全性问题的可行方案。希望是设计智能交通系统（its）建立在信息和通信技术领域的进步，如车辆自组织网络（VANETs），原则上，可以允许车辆，交通信号灯，或路边单位交换信息和协调他们的行为。因此，车对车通信和信息技术进步的应用可以帮助优化交通流量，提高运输效率。然而，在许多这些进步能够以最理想的方式在现实生活中实施之前，必须通过仿真模型对其场景进行研究和分析。本研究开发了基于多智能体的仿真模型，用于在道路/街道网络改变之前评估设计方案，并研究这些变化对交通流量、拥堵和旅行时间的影响。本研究探讨如何应用资讯与通讯技术来进行车辆交通流量的监测、侦测、预测与控制。异常交通和拥堵问题的存在并不是车辆交通网络所特有的。在数据通信网络中也经常遇到。本研究建立数据通信网络，即分组交换网络（psn）的仿真模型，研究正常和异常流量条件下（如分布式拒绝服务攻击）的时空数据包流量动态。它研究了：(1)功能、结构和可扩展性如何影响psn的集体动态和性能；(2)聚合网络性能指标捕获异常条件引起的psn流量和拥塞动态变化的能力。此外，本研究还提出了以下新方法：(1)基于多尺度分析交通运输和数据通信网络的时空大尺度流量模式的异常交通检测方法；(2)基于对大尺度交通格局时空动态的理解，基于交通网络与数据通信网络的关联与协作的交通与拥堵控制策略；(3)车辆交通网络交通流管理中可实时实施的流量与拥塞控制策略、拥塞检测与预测方法。所讨论的研究涵盖了方法论和应用领域。在方法论领域，它还研究认知代理，重点是最小实体，无论是在存储方面还是在逻辑原语方面，都无法分析地表达概念，也无法使用清晰的值。所述的研究将产生新的结果，对方法的进步，对流动和拥堵现象的理论认识，以及对解决车辆运输和数据通信网络中一些具有经济价值的现实生活问题的实际应用具有重要意义。

Vehicular traffic congestion affects many aspects of everyday life. It causes waste of time, economic losses, increased fuel consumption & pollution. Due to financial, spatial and environmental constraints extending the road network is not feasible solution to solve congestion, reliability and safety problems. The hope is in designing Intelligent Transportation Systems (ITSs) build on progress in the area of information & communication technology such as Vehicular Ad Hoc Networks (VANETs) which in principle, could allow vehicles, traffic lights, or road side units to exchange information and to coordinate their behavior. Thus, vehicle-to-vehicle communication and applications of advances in information technologies could help to optimize traffic flow and make transportation more efficient. However, before many of these advances can be implemented in real life in the most optimal way their scenarios must be studied and analyzed via simulation models. This research develops multi-agent based simulation models to be used for evaluating design options prior to making changes in road/street networks and to study the effects of these changes on traffic flow and congestion, and travel times. This research investigates how application of information and communication technologies can be used for vehicular traffic flow monitoring, detection, forecasting and control. The problems of existence of anomalous traffic and congestion are not unique to vehicular transportation networks. Also, they are encountered in data communication networks everyday. This research develops simulation models of data communication networks, i.e. of Packet Switching Networks (PSNs) to study spatio-temporal packet traffic dynamics under normal and anomalous traffic conditions (e.g., under distributed denial of service attacks). It investigates: (1) how function, structure, and scalability affect collective dynamics and performance of PSNs; (2) how well aggregate network performance indicators capture changes in PSNs flow and congestion dynamics caused by anomalous conditions. Additionally, this research develops novel: (1) detection methods of anomalous traffic based on multiscale analysis of spatio-temporal large scale flow patterns in vehicular transportation and data communication networks; (2) flow and congestion control strategies based on the understanding of spatio-temporal dynamics of large scale flow patterns and on correlation and cooperation in vehicular transportation and data communication networks; (3) real-time implementable flow and congestion control strategies, congestion detection and forecasting methods for traffic flow management in vehicular transportation networks. The discussed research covers methodology and application domains. In the methodology domain it studies also cognitive agents with emphasis on minimal entities, both in terms of storage and in terms of logical primitives and unable to express concepts analytically and unable to use crisp values. The described research will produce novel results of importance to the advancement of methodology, theoretical understanding of flow and congestion phenomena and useful for practical applications to solve some real life problems of economical value in vehicular transportation and data communication networks.