为了在保证路段行人过街安全与过街需求的前提下,同时提升路段车辆运行效率,充分考虑了车队离散到达与路段行人过街的动态影响,建立了路段行人过街感应式信号控制方法。首先,基于Robertson车队离散模型,以车头时距对上游到达车队进行动...为了在保证路段行人过街安全与过街需求的前提下,同时提升路段车辆运行效率,充分考虑了车队离散到达与路段行人过街的动态影响,建立了路段行人过街感应式信号控制方法。首先,基于Robertson车队离散模型,以车头时距对上游到达车队进行动态划分,并根据路段行人过街点位预测下游车辆排队状态;以车队离散度选择下游到达车队中车辆作为信号优化输入参数建立感应控制方法,同时分析了路段行人过街位置对配时方案的影响;然后,通过SUMO软件的交通控制接口(traffic control interface,TraCI)搭建仿真环境,以车辆与行人的综合平均延误,分别对路段单向与双向交通环境的信号配时方案进行仿真验证与对比分析。结果表明,相比传统感应控制而言,优化后的感应控制在单向交通与双向交通情况下,行人与车辆综合平均延误分别降低5.56%、7.06%。展开更多
The time resolution of the existing traffic flow prediction model is too big to be applied to adaptive signal timing optimization.Based on the view of the platoon dispersion model,the relationship between vehicle arri...The time resolution of the existing traffic flow prediction model is too big to be applied to adaptive signal timing optimization.Based on the view of the platoon dispersion model,the relationship between vehicle arrival at the downstream intersection and vehicle departure from the upstream intersection was analyzed.Then,a high-resolution traffic flow prediction model based on deep learning was developed.The departure flow rate from the upstream and the arrival flow rate at the downstream intersection was taking as the input and output in the proposed model,respectively.Finally,the parameters of the proposed model were trained by the field data,and the proposed model was implemented to forecast the arrival flow rate of the downstream intersection.Results show that the proposed model can better capture the fluctuant traffic flow and reduced MAE,MRE,and RMSE by 9.53%,39.92%,and 3.56%,respectively,compared with traditional models and algorithms,such as Robertson's model and artificial neural network.Therefore,the proposed model can be applied for realtime adaptive signal timing optimization.展开更多
In order to improve the smoothness of traffic flow on bidirectional two-lane highways, an analytical method is proposed to optimize the minimum spacing of the signalized intersections. The minimum signal spacing is de...In order to improve the smoothness of traffic flow on bidirectional two-lane highways, an analytical method is proposed to optimize the minimum spacing of the signalized intersections. The minimum signal spacing is determined by two parts, including the necessary distance for stabilizing the traffic flow after it passes through the signalized intersections and the length of the upstream functional area of intersection. For the former, based on the platoon dispersion theory, the stable distance determination problem of traffic flow is studied and a model of dispersion degrees varying with the distance from the upstream intersection is presented, in which the time headway is intended to yield the shifted negative exponential distribution. The parameters of the model for medal and collector highways are estimated respectively based on the field data. Then, the section at which the slope of dispersion degree curve equals -0.1 is regarded as the beginning of the dispersion stable state. The length of the intersection upstream functional area is determined by three parts, including the distance traveled during perception-reaction time, the distance traveled while a driver decelerates to a stop, and the queue storage length. Based on the above procedures, the minimum signal spacing of each highway category is proposed.展开更多
In order to reduce average arterial vehicle delay, a novel distributed and coordinated traffic control algorithm is developed using the multiple agent system and the reinforce learning （RL）. The RL is used to minimi...In order to reduce average arterial vehicle delay, a novel distributed and coordinated traffic control algorithm is developed using the multiple agent system and the reinforce learning （RL）. The RL is used to minimize average delay of arterial vehicles by training the interaction ability between agents and exterior environments. The Robertson platoon dispersion model is embedded in the RL algorithm to precisely predict platoon movements on arteries and then the reward function is developed based on the dispersion model and delay equations cited by HCM2000. The performance of the algorithm is evaluated in a Matlab environment and comparisons between the algorithm and the conventional coordination algorithm are conducted in three different traffic load scenarios. Results show that the proposed algorithm outperforms the conventional algorithm in all the scenarios. Moreover, with the increase in saturation degree, the performance is improved more significantly. The results verify the feasibility and efficiency of the established algorithm.展开更多
文摘为了在保证路段行人过街安全与过街需求的前提下,同时提升路段车辆运行效率,充分考虑了车队离散到达与路段行人过街的动态影响,建立了路段行人过街感应式信号控制方法。首先,基于Robertson车队离散模型,以车头时距对上游到达车队进行动态划分,并根据路段行人过街点位预测下游车辆排队状态;以车队离散度选择下游到达车队中车辆作为信号优化输入参数建立感应控制方法,同时分析了路段行人过街位置对配时方案的影响;然后,通过SUMO软件的交通控制接口(traffic control interface,TraCI)搭建仿真环境,以车辆与行人的综合平均延误,分别对路段单向与双向交通环境的信号配时方案进行仿真验证与对比分析。结果表明,相比传统感应控制而言,优化后的感应控制在单向交通与双向交通情况下,行人与车辆综合平均延误分别降低5.56%、7.06%。
文摘The time resolution of the existing traffic flow prediction model is too big to be applied to adaptive signal timing optimization.Based on the view of the platoon dispersion model,the relationship between vehicle arrival at the downstream intersection and vehicle departure from the upstream intersection was analyzed.Then,a high-resolution traffic flow prediction model based on deep learning was developed.The departure flow rate from the upstream and the arrival flow rate at the downstream intersection was taking as the input and output in the proposed model,respectively.Finally,the parameters of the proposed model were trained by the field data,and the proposed model was implemented to forecast the arrival flow rate of the downstream intersection.Results show that the proposed model can better capture the fluctuant traffic flow and reduced MAE,MRE,and RMSE by 9.53%,39.92%,and 3.56%,respectively,compared with traditional models and algorithms,such as Robertson's model and artificial neural network.Therefore,the proposed model can be applied for realtime adaptive signal timing optimization.
基金The National Natural Science Foundation of China(No.5120810051308192)
文摘In order to improve the smoothness of traffic flow on bidirectional two-lane highways, an analytical method is proposed to optimize the minimum spacing of the signalized intersections. The minimum signal spacing is determined by two parts, including the necessary distance for stabilizing the traffic flow after it passes through the signalized intersections and the length of the upstream functional area of intersection. For the former, based on the platoon dispersion theory, the stable distance determination problem of traffic flow is studied and a model of dispersion degrees varying with the distance from the upstream intersection is presented, in which the time headway is intended to yield the shifted negative exponential distribution. The parameters of the model for medal and collector highways are estimated respectively based on the field data. Then, the section at which the slope of dispersion degree curve equals -0.1 is regarded as the beginning of the dispersion stable state. The length of the intersection upstream functional area is determined by three parts, including the distance traveled during perception-reaction time, the distance traveled while a driver decelerates to a stop, and the queue storage length. Based on the above procedures, the minimum signal spacing of each highway category is proposed.
基金The National Key Technology R&D Program during the 11th Five-Year Plan Period of China (No. 2009BAG17B02)the National High Technology Research and Development Program of China (863 Program) (No. 2011AA110304)the National Natural Science Foundation of China (No. 50908100)
文摘In order to reduce average arterial vehicle delay, a novel distributed and coordinated traffic control algorithm is developed using the multiple agent system and the reinforce learning （RL）. The RL is used to minimize average delay of arterial vehicles by training the interaction ability between agents and exterior environments. The Robertson platoon dispersion model is embedded in the RL algorithm to precisely predict platoon movements on arteries and then the reward function is developed based on the dispersion model and delay equations cited by HCM2000. The performance of the algorithm is evaluated in a Matlab environment and comparisons between the algorithm and the conventional coordination algorithm are conducted in three different traffic load scenarios. Results show that the proposed algorithm outperforms the conventional algorithm in all the scenarios. Moreover, with the increase in saturation degree, the performance is improved more significantly. The results verify the feasibility and efficiency of the established algorithm.
