基于多智能代理的交通信息相关问题研究
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摘要
本文对交通相关信息技术的多个领域进行了研究，包括交通模拟的路由导航算法设计及其架构、服务优先保障的算法设计及其架构、车辆折算系数分析和交通相关软件性能测试架构。
在基于多智能代理的路口中心型路由导航算法部分，设计了可应用于有目的地点的大规模车辆行为的模拟和人流疏导算法。在分析交通模拟领域现有的研究和常见问题综述基础上，结合计算机网络的数据流控制方法和协议，创造性地提出了仿真网络数据流控制方法来为车辆导航，并通过实验证明架构设计合理。随后就算法进行深入研究，引入符合一般道路模型的N正则随机图，设计了IBF*算法分析得出在合理的假设下算法导航的期望复杂度远低于最坏复杂度，提出了应用于交通路由领域的基于多维定标的智能路由算法。最后通过模拟系统进行了性能试验，并对算法正确性进行了数学证明。
在基于多智能代理的路口中心型优先通行算法部分，设计了针对特殊车辆的疏导算法。在前述研究基础上，针对交叉路口应该有可控的优先通行能力的要求，提出了基于智能代理的优先通行框架和算法，算法的设计参考了计算机网络中QoS的现有研究成果。通过对算法进行的模拟验证，证实了算法的可行性。该方法可以用于大规模交通流导航时，对于特殊对象的优先通行保障。新的算法框架基于交叉路口的智能处理，系统地解决了包括正确通行和优先通行在内的多个问题。在车辆折算系数研究部分，首次提出了如何采用基于高斯混合模型的多视图EM算法进行车辆折算系数聚类分析，给出了一种车辆折算系数的计算方法。通过某真实路段的大量车辆数据对算法进行了验证实验和分析，证明算法可以有效下降熵值，提高视图一致性，数据结果有效可信。
在网络通信流多智能代理用于应用系统性能评价研究部分，通过解决交通相关系统的性能评价问题，提出并实现了测试的框架和算法。在交通信息系统中，新型软件架构层出不穷，软硬件和网络通讯之间的相互作用日益复杂，加大了系统性能瓶颈查找的难度。本文研究如何采用多智能代理截取、分析和回放网络数据流测量软件性能。通过同时使用主动智能代理和被动智能代理，使得整个测试的各个分支具有通讯、协作的能力。通过在交通相关系统中的测试应用，证明此算法能有效地同时获取多项数据，且保持高效能的性能评价，系统架构具有一定的自动处理能力。本文的主要创新点在于以计算机网络协议和多智能代理技术作为为研究的工具方法，对交通相关的多个领域进行了跨越原有学科界限的研究。具体涉及的算法新型应用或者算法改进涵盖了Dijkstra算法、IBF*(Intersect-Bellman-Ford)*算法、N正则随机图、多维定标算法、FastMap算法、QoS(Quality of Service)算法和多视图EM聚类算法等。通过数学证明和模拟实验结合的方式，证明了架构设计和算法设计的可行性和有效性。
Several information technology issues related to traffic are studiedin this thesis.This include:intersection-centric route guidancealgorithm and architecture design for traffic simulation based onmulti-agents,intersection-centric priority algorithm and architecturefor traffic simulation based on multi-agents,multi-agent network flowarchitecture for traffic application performance evaluation,and vehicleconvert coefficient research.
At the part of intersection-centric route guidance algorithm andarchitecture design for traffic simulation based on multi-agents,algorithm which could be used in large scale vehicles and person' sevacuation when they have own destination addresses is proposed.Basedon the analysis and summarize of existing research of traffic simulationrouting,combined with data flow control methods and protocols of computernetworks,this paper creatively proposed network protocols could be usedin traffic simulation to simulate the relationship of roads and vehicles.After the function development practice proved that this architecture andalgorithm are practical,algorithm is studied in further.Road map relatedrandom map and IBF* algorithm proved that design' s complexityexpectation is much lower than the worst case.Multi-dimensional scalingis introduced into intelligent routing algorithm proposed in trafficrouting issue.Performance simulation result in simulation test provedthe correctness of algorithm.A mathematic proof is also given to proveit.
At the part of intersection-centric priority algorithm for trafficsimulation based on multi-agents,evacuate algorithm to special vehicleis proposed.Based on last chapter' s algorithm,a priority guaranteeframework and a priority algorithm run on intersection referenced withcomputer networks' QoS algorithm is proposed.For urgent or specialvehicles,controllable priority is new requirement.With the simulationverification of algorithm,the feasibility of it is proved.To large scale traffic flow evacuating,algorithm is useful to guarantee special objectsrunning.New algorithms are based on the intelligent agents ofintersections,so these algorithms framework systemly solves the correctguidance issue and the priority guarantee issues.At vehicle conversionfactor research part,using multi-view Expectation Maximizationalgorithm based on Gaussian mixture model to calculate vehicle convertcoefficient is proposed first time.With the real roads' vehicles datacolleted by video device,algorithm was trained by real data.This provedthat algorithm could reduce the value of entropy and improve view' sagreement rate,so the vehicle convert coefficient is believable.
At a multi-agents' network flow architecture for applicationperformance evaluation part,traffic related application perforce wasconsidered.With the new software architecture appearing,the applicationperformance evaluation and bottle neck finding becomes more difficultbecause of the complexity in software components and networks'interaction.This part is about how to use multi-agents on networks tocapture analysis and replay network data flow to evaluate the applicationperformance.Both active and passive agents cooperate to simulate andtest,they communicate and interact to find the performance result andthe bottle neck of the system.Through real traffic application systems'test practice,the advantage of this method is proved.This method cangive out multi-data at same time with high performance and have someautomatic functions.
In conclusion,the main innovation is to use internet protocols andmulti-agents as research platform to study traffic related routing area.Related algorithm' s new application and algorithm' s improvement andproof proposed include:Dijkstra algorithm,Intersect-Bellman-Ford *algorithm,n regular random graph,multi-dimensional scaling,FastmapAlgorithm,QoS algorithm,multi-view Expectation Maximization algorithmbased on Gaussian distribution hybrid model and so on.Simulation,mathematic proof and real system practice are used to prove the correctionof these architectures,methods and algorithms.
在基于多智能代理的路口中心型路由导航算法部分，设计了可应用于有目的地点的大规模车辆行为的模拟和人流疏导算法。在分析交通模拟领域现有的研究和常见问题综述基础上，结合计算机网络的数据流控制方法和协议，创造性地提出了仿真网络数据流控制方法来为车辆导航，并通过实验证明架构设计合理。随后就算法进行深入研究，引入符合一般道路模型的N正则随机图，设计了IBF*算法分析得出在合理的假设下算法导航的期望复杂度远低于最坏复杂度，提出了应用于交通路由领域的基于多维定标的智能路由算法。最后通过模拟系统进行了性能试验，并对算法正确性进行了数学证明。
在基于多智能代理的路口中心型优先通行算法部分，设计了针对特殊车辆的疏导算法。在前述研究基础上，针对交叉路口应该有可控的优先通行能力的要求，提出了基于智能代理的优先通行框架和算法，算法的设计参考了计算机网络中QoS的现有研究成果。通过对算法进行的模拟验证，证实了算法的可行性。该方法可以用于大规模交通流导航时，对于特殊对象的优先通行保障。新的算法框架基于交叉路口的智能处理，系统地解决了包括正确通行和优先通行在内的多个问题。在车辆折算系数研究部分，首次提出了如何采用基于高斯混合模型的多视图EM算法进行车辆折算系数聚类分析，给出了一种车辆折算系数的计算方法。通过某真实路段的大量车辆数据对算法进行了验证实验和分析，证明算法可以有效下降熵值，提高视图一致性，数据结果有效可信。
在网络通信流多智能代理用于应用系统性能评价研究部分，通过解决交通相关系统的性能评价问题，提出并实现了测试的框架和算法。在交通信息系统中，新型软件架构层出不穷，软硬件和网络通讯之间的相互作用日益复杂，加大了系统性能瓶颈查找的难度。本文研究如何采用多智能代理截取、分析和回放网络数据流测量软件性能。通过同时使用主动智能代理和被动智能代理，使得整个测试的各个分支具有通讯、协作的能力。通过在交通相关系统中的测试应用，证明此算法能有效地同时获取多项数据，且保持高效能的性能评价，系统架构具有一定的自动处理能力。本文的主要创新点在于以计算机网络协议和多智能代理技术作为为研究的工具方法，对交通相关的多个领域进行了跨越原有学科界限的研究。具体涉及的算法新型应用或者算法改进涵盖了Dijkstra算法、IBF*(Intersect-Bellman-Ford)*算法、N正则随机图、多维定标算法、FastMap算法、QoS(Quality of Service)算法和多视图EM聚类算法等。通过数学证明和模拟实验结合的方式，证明了架构设计和算法设计的可行性和有效性。
Several information technology issues related to traffic are studiedin this thesis.This include:intersection-centric route guidancealgorithm and architecture design for traffic simulation based onmulti-agents,intersection-centric priority algorithm and architecturefor traffic simulation based on multi-agents,multi-agent network flowarchitecture for traffic application performance evaluation,and vehicleconvert coefficient research.
At the part of intersection-centric route guidance algorithm andarchitecture design for traffic simulation based on multi-agents,algorithm which could be used in large scale vehicles and person' sevacuation when they have own destination addresses is proposed.Basedon the analysis and summarize of existing research of traffic simulationrouting,combined with data flow control methods and protocols of computernetworks,this paper creatively proposed network protocols could be usedin traffic simulation to simulate the relationship of roads and vehicles.After the function development practice proved that this architecture andalgorithm are practical,algorithm is studied in further.Road map relatedrandom map and IBF* algorithm proved that design' s complexityexpectation is much lower than the worst case.Multi-dimensional scalingis introduced into intelligent routing algorithm proposed in trafficrouting issue.Performance simulation result in simulation test provedthe correctness of algorithm.A mathematic proof is also given to proveit.
At the part of intersection-centric priority algorithm for trafficsimulation based on multi-agents,evacuate algorithm to special vehicleis proposed.Based on last chapter' s algorithm,a priority guaranteeframework and a priority algorithm run on intersection referenced withcomputer networks' QoS algorithm is proposed.For urgent or specialvehicles,controllable priority is new requirement.With the simulationverification of algorithm,the feasibility of it is proved.To large scale traffic flow evacuating,algorithm is useful to guarantee special objectsrunning.New algorithms are based on the intelligent agents ofintersections,so these algorithms framework systemly solves the correctguidance issue and the priority guarantee issues.At vehicle conversionfactor research part,using multi-view Expectation Maximizationalgorithm based on Gaussian mixture model to calculate vehicle convertcoefficient is proposed first time.With the real roads' vehicles datacolleted by video device,algorithm was trained by real data.This provedthat algorithm could reduce the value of entropy and improve view' sagreement rate,so the vehicle convert coefficient is believable.
At a multi-agents' network flow architecture for applicationperformance evaluation part,traffic related application perforce wasconsidered.With the new software architecture appearing,the applicationperformance evaluation and bottle neck finding becomes more difficultbecause of the complexity in software components and networks'interaction.This part is about how to use multi-agents on networks tocapture analysis and replay network data flow to evaluate the applicationperformance.Both active and passive agents cooperate to simulate andtest,they communicate and interact to find the performance result andthe bottle neck of the system.Through real traffic application systems'test practice,the advantage of this method is proved.This method cangive out multi-data at same time with high performance and have someautomatic functions.
In conclusion,the main innovation is to use internet protocols andmulti-agents as research platform to study traffic related routing area.Related algorithm' s new application and algorithm' s improvement andproof proposed include:Dijkstra algorithm,Intersect-Bellman-Ford *algorithm,n regular random graph,multi-dimensional scaling,FastmapAlgorithm,QoS algorithm,multi-view Expectation Maximization algorithmbased on Gaussian distribution hybrid model and so on.Simulation,mathematic proof and real system practice are used to prove the correctionof these architectures,methods and algorithms.
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