In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed sign...In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.展开更多
In this paper, a traffic signal control method based on fuzzy logic (FL), fuzzy-neuro (FN) and multi-objective genetic algorithms (MOGA) for an isolated four-approach intersection with through and left-turning movemen...In this paper, a traffic signal control method based on fuzzy logic (FL), fuzzy-neuro (FN) and multi-objective genetic algorithms (MOGA) for an isolated four-approach intersection with through and left-turning movements is presented. This method has an adaptive signal timing ability, and can make adjustments to signal timing in response to observed changes.The 'urgency degree' term, which can describe the different user's demand for green time is used in decision-making by which strategy of signal timing can be determined. Using a fuzzy logic controller, we can determine whether to extend or terminate the current signal phase and select the sequences of phases. In this paper, a method based on fuzzy-neuro can be used to predict traffic parameters used in fuzzy logic controller. The feasibility of using a multi-objective genetic algorithm ( MOGA) to find a group of optimizing sets of parameters for fuzzy logic controller depending on different objects is also demonstrated. Simulation results show that the proposed methed is effecfive to adjust the signal timing in response to changing traffic conditions on a real-time basis, and the controller can produce lower vehicle delays and percentage of stopped vehicles than a traffic-actuated controller.展开更多
Autonomous vehicle technology will transform fundamentally urban traffic systems.To better enhance the coming era of connected and autonomous vehicles,effective control strategies that interact wisely with these intel...Autonomous vehicle technology will transform fundamentally urban traffic systems.To better enhance the coming era of connected and autonomous vehicles,effective control strategies that interact wisely with these intelligent vehicles for signalized at-grade intersections are indispensable.Vehicle-to-infrastructure communication technology offers unprecedented clues to reduce the delay at signalized intersections by innovative information-based control strategies.This paper proposes a new dynamic control strategy for signalized intersections with vehicle-to-signal information.The proposed strategy is called periodic vehicle holding(PVH)strategy while the traffic signal can provide information for the vehicles that are approaching an intersection.Under preliminary autonomous vehicle(PAV)environment,left-turning and through-moving vehicles will be sorted based on different information they receive.The paper shows how PVH reorganizes traffic to increase the capacity of an intersection without causing severe spillback to the upstream intersection.Results show that PVH can reduce the delay by approximately 15%at a signalized intersection under relatively high traffic demand.展开更多
Traffic jam in large signalized road network presents a complex nature.In order to reveal the jam characteristics,two indexes,SVS(speed of virtual signal) and VOS(velocity of spillover),were proposed respectively.SVS ...Traffic jam in large signalized road network presents a complex nature.In order to reveal the jam characteristics,two indexes,SVS(speed of virtual signal) and VOS(velocity of spillover),were proposed respectively.SVS described the propagation of queue within a link while VOS reflected the spillover velocity of vehicle queue.Based on the two indexes,network jam simulation was carried out on a regular signalized road network.The simulation results show that:1) The propagation of traffic congestion on a signalized road network can be classified into two stages:virtual split driven stage and flow rate driven stage.The former stage is characterized by decreasing virtual split while the latter only depends on flow rate; 2) The jam propagation rate and direction are dependent on traffic demand distribution and other network parameters.The direction with higher demand gets more chance to be jammed.Our findings can serve as the basis of the prevention of the formation and propagation of network traffic jam.展开更多
The traffic performance of urban expressway is subject to non-recurring and recurring events, which may cause heavy congestion and vehicles long queuing on ramps. The low performance may bring more traffic delay to th...The traffic performance of urban expressway is subject to non-recurring and recurring events, which may cause heavy congestion and vehicles long queuing on ramps. The low performance may bring more traffic delay to the whole network of urban road. This paper presents a new method, the joint control of variable speed control and on-ramp metering, which attempts to improve the level of traffic operations on urban expressway. By analyzing traffic flow on urban expressway, an optimum control strategy of variable speed and on-ramp metering is established in the paper.展开更多
目前,空管各类安全管理信息化平台积累了大量非结构化文本数据,但未得到充分利用,为了挖掘空管不正常事件中潜藏的风险,研究利用收集的四千余条空管站不正常事件数据和自构建的4836个空管领域专业术语词,提出了一个基于空管专业信息词...目前,空管各类安全管理信息化平台积累了大量非结构化文本数据,但未得到充分利用,为了挖掘空管不正常事件中潜藏的风险,研究利用收集的四千余条空管站不正常事件数据和自构建的4836个空管领域专业术语词,提出了一个基于空管专业信息词抽取的双向编码器表征法和双向长短时记忆网络的深度学习模型(Bidirectional Encoder Representations from Transformers-Bidirectional Long Short-Term Memory,BERT-BiLSTM)。该模型通过对不正常事件文本进行信息抽取,过滤其中无用信息,并将双向编码器表征法(Bidirectional Encoder Representations from Transformers,BERT)模型输出的特征向量序列作为双向长短时记忆网络(Bidirectional Long Short-Term Memory,BiLSTM)的输入序列,以对空管不正常事件文本风险识别任务进行对比试验。试验结果显示,在风险识别试验中,基于空管专业信息词抽取的BERT-BiLSTM模型相比于通用领域的BERT模型,风险识别准确率提升了3百分点。可以看出该模型有效提升了空管安全信息处理能力,能够有效识别空管部门日常运行中出现的不正常事件所带来的风险,同时可以为空管安全领域信息挖掘相关任务提供基础参考。展开更多
Provisioning network resource to meet the quality of Service (QoS) demand is a key issue for future network services. Such functions may be realized by an admission control algorithm, which determines whether or not a...Provisioning network resource to meet the quality of Service (QoS) demand is a key issue for future network services. Such functions may be realized by an admission control algorithm, which determines whether or not a new traffic flow can be admitted into the network. It is widely accepted that many traffic flows have self-similar character that has detrimental influence on network performance. This characteristic has made old mathematical models invalid, and a new model must work with self-similar fractal instead. This paper applies Fractional Brownian Motion(FBM) model and integrates it into the comprehensive admission control scheme, which takes account of aggregated traffic behavior to get the statistical multiplexing performance gain. Experiment verifies that FBM model can be used to realistically describe packet traffic in modern packet networks and accurately predict their performance.展开更多
在异质交通流背景下,针对交通信号调度与车辆轨迹规划协同问题,本文提出集信号和轨迹于一体的融合控制模型。该模型采用竞争双深度Q网络算法(Dueling Double Deep Q Network, D3QN),通过深度强化学习技术对交通信号和车辆轨迹进行同步优...在异质交通流背景下,针对交通信号调度与车辆轨迹规划协同问题,本文提出集信号和轨迹于一体的融合控制模型。该模型采用竞争双深度Q网络算法(Dueling Double Deep Q Network, D3QN),通过深度强化学习技术对交通信号和车辆轨迹进行同步优化,旨在实现交通效率与生态驾驶的双重目标,并基于SUMO(Simulation of Urban Mobility)仿真平台对模型进行全面验证。仿真结果表明:与基准模型相比,单一优化策略虽然能在一定程度上改善交叉口性能,但存在整体效率提升受限的问题;本文提出的融合控制模型结合了宏观交通流与微观车辆行为的优化,使车均延误降低66.99%,燃油消耗减少11.26%,同时CO_(2)等污染物排放量也显著减少。进一步的敏感性分析揭示了系统性能随网联自动驾驶汽车(Connected and Autonomous Vehicles, CAV)渗透率的变化规律修正:当渗透率达到一定水平后,性能提升幅度逐渐减小,且模型在不同交通流量条件下均展现出稳定的优化效果,这一结果证实了该控制方法在城市交叉口环境中的适应性和鲁棒性。展开更多
基金Project(2014BAG01B0403)supported by the High-Tech Research and Development Program of China
文摘In order to balance the temporal-spatial distribution of urban traffic flow, a model is established for combined urban traffic signal control and traffic flow guidance. With consideration of the wide use of fixed signal control at intersections, traffic assignment under traffic flow guidance, and dynamic characteristics of urban traffic management, a tri-level programming model is presented. To reflect the impact of intersection delay on traffic assignment, the lower level model is set as a modified user equilibrium model. The middle level model, which contains several definitional constraints for different phase modes, is built for the traffic signal control optimization. To solve the problem of tide lane management, the upper level model is built up based on nonlinear 0-1 integer programming. A heuristic iterative optimization algorithm(HIOA) is set up to solve the tri-level programming model. The lower level model is solved by method of successive averages(MSA), the middle level model is solved by non-dominated sorting genetic algorithm II(NSGA II), and the upper level model is solved by genetic algorithm(GA). A case study is raised to show the efficiency and applicability of the proposed modelling and computing method.
基金This project was supported by China Postdoctoral Science Foundation: "Research on Traffic Signal Control Method for Urban Intersection Based on Intelligent Techniques, 2001" .
文摘In this paper, a traffic signal control method based on fuzzy logic (FL), fuzzy-neuro (FN) and multi-objective genetic algorithms (MOGA) for an isolated four-approach intersection with through and left-turning movements is presented. This method has an adaptive signal timing ability, and can make adjustments to signal timing in response to observed changes.The 'urgency degree' term, which can describe the different user's demand for green time is used in decision-making by which strategy of signal timing can be determined. Using a fuzzy logic controller, we can determine whether to extend or terminate the current signal phase and select the sequences of phases. In this paper, a method based on fuzzy-neuro can be used to predict traffic parameters used in fuzzy logic controller. The feasibility of using a multi-objective genetic algorithm ( MOGA) to find a group of optimizing sets of parameters for fuzzy logic controller depending on different objects is also demonstrated. Simulation results show that the proposed methed is effecfive to adjust the signal timing in response to changing traffic conditions on a real-time basis, and the controller can produce lower vehicle delays and percentage of stopped vehicles than a traffic-actuated controller.
文摘Autonomous vehicle technology will transform fundamentally urban traffic systems.To better enhance the coming era of connected and autonomous vehicles,effective control strategies that interact wisely with these intelligent vehicles for signalized at-grade intersections are indispensable.Vehicle-to-infrastructure communication technology offers unprecedented clues to reduce the delay at signalized intersections by innovative information-based control strategies.This paper proposes a new dynamic control strategy for signalized intersections with vehicle-to-signal information.The proposed strategy is called periodic vehicle holding(PVH)strategy while the traffic signal can provide information for the vehicles that are approaching an intersection.Under preliminary autonomous vehicle(PAV)environment,left-turning and through-moving vehicles will be sorted based on different information they receive.The paper shows how PVH reorganizes traffic to increase the capacity of an intersection without causing severe spillback to the upstream intersection.Results show that PVH can reduce the delay by approximately 15%at a signalized intersection under relatively high traffic demand.
基金Project(2012CB725402)supported by the State Key Development Program for Basic Research of ChinaProject(2012MS21175)supported by the National Science Foundation for Post-doctoral Scientists of ChinaProject(Bsh1202056)supported by the Excellent Postdoctoral Science Foundation of Zhejiang Province,China
文摘Traffic jam in large signalized road network presents a complex nature.In order to reveal the jam characteristics,two indexes,SVS(speed of virtual signal) and VOS(velocity of spillover),were proposed respectively.SVS described the propagation of queue within a link while VOS reflected the spillover velocity of vehicle queue.Based on the two indexes,network jam simulation was carried out on a regular signalized road network.The simulation results show that:1) The propagation of traffic congestion on a signalized road network can be classified into two stages:virtual split driven stage and flow rate driven stage.The former stage is characterized by decreasing virtual split while the latter only depends on flow rate; 2) The jam propagation rate and direction are dependent on traffic demand distribution and other network parameters.The direction with higher demand gets more chance to be jammed.Our findings can serve as the basis of the prevention of the formation and propagation of network traffic jam.
文摘The traffic performance of urban expressway is subject to non-recurring and recurring events, which may cause heavy congestion and vehicles long queuing on ramps. The low performance may bring more traffic delay to the whole network of urban road. This paper presents a new method, the joint control of variable speed control and on-ramp metering, which attempts to improve the level of traffic operations on urban expressway. By analyzing traffic flow on urban expressway, an optimum control strategy of variable speed and on-ramp metering is established in the paper.
文摘目前,空管各类安全管理信息化平台积累了大量非结构化文本数据,但未得到充分利用,为了挖掘空管不正常事件中潜藏的风险,研究利用收集的四千余条空管站不正常事件数据和自构建的4836个空管领域专业术语词,提出了一个基于空管专业信息词抽取的双向编码器表征法和双向长短时记忆网络的深度学习模型(Bidirectional Encoder Representations from Transformers-Bidirectional Long Short-Term Memory,BERT-BiLSTM)。该模型通过对不正常事件文本进行信息抽取,过滤其中无用信息,并将双向编码器表征法(Bidirectional Encoder Representations from Transformers,BERT)模型输出的特征向量序列作为双向长短时记忆网络(Bidirectional Long Short-Term Memory,BiLSTM)的输入序列,以对空管不正常事件文本风险识别任务进行对比试验。试验结果显示,在风险识别试验中,基于空管专业信息词抽取的BERT-BiLSTM模型相比于通用领域的BERT模型,风险识别准确率提升了3百分点。可以看出该模型有效提升了空管安全信息处理能力,能够有效识别空管部门日常运行中出现的不正常事件所带来的风险,同时可以为空管安全领域信息挖掘相关任务提供基础参考。
文摘Provisioning network resource to meet the quality of Service (QoS) demand is a key issue for future network services. Such functions may be realized by an admission control algorithm, which determines whether or not a new traffic flow can be admitted into the network. It is widely accepted that many traffic flows have self-similar character that has detrimental influence on network performance. This characteristic has made old mathematical models invalid, and a new model must work with self-similar fractal instead. This paper applies Fractional Brownian Motion(FBM) model and integrates it into the comprehensive admission control scheme, which takes account of aggregated traffic behavior to get the statistical multiplexing performance gain. Experiment verifies that FBM model can be used to realistically describe packet traffic in modern packet networks and accurately predict their performance.
文摘在异质交通流背景下,针对交通信号调度与车辆轨迹规划协同问题,本文提出集信号和轨迹于一体的融合控制模型。该模型采用竞争双深度Q网络算法(Dueling Double Deep Q Network, D3QN),通过深度强化学习技术对交通信号和车辆轨迹进行同步优化,旨在实现交通效率与生态驾驶的双重目标,并基于SUMO(Simulation of Urban Mobility)仿真平台对模型进行全面验证。仿真结果表明:与基准模型相比,单一优化策略虽然能在一定程度上改善交叉口性能,但存在整体效率提升受限的问题;本文提出的融合控制模型结合了宏观交通流与微观车辆行为的优化,使车均延误降低66.99%,燃油消耗减少11.26%,同时CO_(2)等污染物排放量也显著减少。进一步的敏感性分析揭示了系统性能随网联自动驾驶汽车(Connected and Autonomous Vehicles, CAV)渗透率的变化规律修正:当渗透率达到一定水平后,性能提升幅度逐渐减小,且模型在不同交通流量条件下均展现出稳定的优化效果,这一结果证实了该控制方法在城市交叉口环境中的适应性和鲁棒性。
