考虑展宽段的路段排队长度检测算法

为了实时估计路段车辆排队长度,利用铺设在路段上的检测器,提出了一种车辆排队估计方法,对车辆排队进行实时跟踪。该方法考虑了一般的道路拓扑结构,路段排队的演化过程分为四个阶段：初始排队阶段、排队蔓延阶段、排队上溯阶段和堵塞路段阶段,不同阶段的排队利用不同的信息,通过不同的模型进行推算,通过实地调查验证,可以高效实时追踪路段排队的演化。     

基于DSP交通数据采集系统的设计

传统的交通数据采集主要依靠道路上的车辆检测传感器来检测，文章提出基于图像处理与识别的交通数据采集方案。该方案能方便、快捷地测出等待车队的队长、车型等信息，交通数据通过USB接口存储到闪存盘上，控制中心通过分析交通数据，可有针对地进行交通诱导控制决策。     

路段排队最远点估计方法研究

城市拥堵的发生过程一般是某路段发生拥堵,然后扩散至其他路段进而形成区域拥堵.因而,如果能够在排队上溯至交叉口之前估计出路段排队长度并实施控制,就可以在一定程度上缓解拥堵.为了得到路段实时排队最远点,文中利用点信息对路段上的排队演化进行研究.从分析路段排队形成时的道路交通流运行特征入手,研究了道路交通流运行状态与固定点数据之间的映射关系,提出了分别利用单固定点信息、双固定点估计连续流形成的排队最远点.利用仿真软件对其进行验证,并研究了不同的采样间隔对算法的影响,结果表明,该算法可以在一定的采样间隔下得到较好的结果.     

Probe vehicle lane identification for queue length estimation at intersections

Vehicles instrumented with Global Positioning Systems, also known as GPS probe vehicles, have become increasingly popular for collecting traffic flow data. Previous studies have explored the probe vehicle data for estimating speeds and travel time; however, there is very limited research on predicting queue dynamics from such data. In this research, a methodology was developed for identifying the lane position of the GPS-instrumented vehicles when they are standing in the queue at signalized intersections with multiple lanes, particularly in the case of unequal queue. Various supervised and unsupervised clustering methods were tested on data generated from a microsimulation model. Among the tested methods, the Optimal Bayes Rule that utilizes probability density functions estimated using bivariate statistical mixture models was found to be effective in identifying the lanes. The methodology for lane identification was tested for queue length estimation. This research confirms that the lane identification is an important step required prior to the queue length estimation. The accuracies of the models for lane identification and queue length estimation were evaluated at varying levels of demand and probe vehicle market penetrations. In general, as the market penetration increases, the accuracy improves as expected. The result shows that 40% market penetration rate is adequate to reach about 90% accuracy.     

基于均衡交通压力及VISSIM仿真的信号灯配时及应用研究

交通供需矛盾的激化突出表现在城市路网的节点（交叉口）上,对于大城市的干道来说饱和交叉口成为制约信号协调效果的瓶颈。从分析饱和车流的特性入手,基于排队长度消散或有侧重均衡交通压力的思想提出了在传统信号配时失效的情况下一种利用VISSIM反馈评价参数调整绿信比优化的方法,并针对这种方法进行信号协调控制的应用研究。     

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首先分析了快速路入口匝道排队导致地面交通拥堵的现象,然后综合考虑快速路主线交通流密度和入口匝道排队长度两个因素,提出了一种基于神经元自适应PID控制的快速路入口匝道控制策略。与传统的入口匝道调节方法ALINEA相比,新方法将快速路系统和平面道路系统有机的结合起来,仅略微地增加快速路交通流密度,且对快速路的负面影响较小,有效降低了入口匝道排队长度并消除了入口匝道回溢现象与快速路交通拥挤的反复振荡现象,对于实际应用中的随机干扰具有良好的抑制能力,提高了整个交通网络的运行效率。最后通过仿真对新方法进行了说明和验证。     

拥挤交通流当量排队长度变化率模型

为了描述拥挤交通流中车辆排队的演化规律,以基于二流理论建立的当量排队长度模型为依据,运用微积分方法,针对单车道路段和多车道路段分别推导出当量排队长度变化率模型,并利用VISSIM模拟数据对模型进行了验证.结果表明:当交通流处于拥挤状态时,当量排队长度变化率近似等于交通波波速;采样间隔内当量排队长度变化率与实际排队长度变化率接近,误差法和熵方法证明,采样间隔越大,两者越接近,因此,提出的模型可以定量描述拥挤交通流中车辆排队的演化速率.     

电子收费系统资源优化方法

以排队论、非集计理论为理论基础,分别以系统平均延误最小、系统总成本最小、系统效益增量与成本增量之比最大为目标,对多收费方式收费系统进行资源优化.通过简单的数值案例说明其应用,为电子收费系统的建设提供参考.     

交通事件下快速路拥堵蔓延消散时空范围模型

研究了交通事件下拥堵蔓延消散的时空范围分析方法与模型,交通事件引发的拥堵会以某一初始蔓延速度向上游蔓延,直至达到最大蔓延边界后开始消散.通过对事件下拥堵蔓延速度的影响因素进行量化分析,建立了时变的拥堵蔓延速度模型;然后通过收集处理数据,进行参数估计;最后利用实际数据,进行了模型的实例应用,对不同情况下的交通拥堵蔓延消散规律进行了研究.该模型可预测交通事件下的交通拥堵边界和持续时间,便于交管部门制定缓堵策略.     

Estimating probability distributions of dynamic queues

Queues are often associated with uncertainty or unreliability, which can arise from chance or climatic events, phase changes in system behaviour, or inherent randomness. Knowing the probability distribution of the number of customers in a queue is important for estimating the risk of stress or disruption to routine services and upstream blocking, potentially leading to exceeding critical limits, gridlock or incidents. The present paper focuses on time-varying queues produced by transient oversaturation during demand peaks where there is randomness in arrivals and service. The objective is to present practical methods for estimating a probability distribution from knowledge of the mean, variance and utilisation (degree of saturation) of a queue available from computationally efficient, if approximate, time-dependent calculation. This is made possible by a novel expression for time-dependent queue variance. The queue processes considered are those commonly used to represent isolated priority (M/M/1) and signal-like (M/D/1) systems, plus some statistical variations within the common Pollaczek-Khinchin framework. Results are verified by comparison with Markov simulation based on recurrence relations.