基于相位相序优化的道路交叉口设计方法

相位相序的优化与交叉口设计有很大的关联性.很多信号控制交叉口优化主要是从交叉口的几何条件、最佳信号周期等因素来考虑,而忽略了相位相序这一重要的影响因素,导致很多交叉口存在交通安全隐患.从交叉口与相位相序优化的关系人手,系统地优化分析道路交叉口,合理安排相位.实践证明,该方法可以减少交通安全隐患,同时为道路交叉口优化提供根据.     

城市交通协调控制系统的相位相序优化设计

优化协调控制交叉口的信号周期与绿信比可提高车辆通行效率,但在较小的近似优化解空间内难以获得最佳的绿波带宽,为了减少交叉口车辆延误,利用相位相序调整扩大协调控制优化解空间,提出了基于多种群遗传算法的相位相序优化设计方法。根据交通工程理论建立车辆延误模型,以干线交叉口车辆平均延误最小为协调控制效益评价指标,对石河子市中心北三路3个交叉口的协调控制案例展开研究,采用多种群遗传算法,对干线交叉口的相位相序进行自动寻优,并通过VISSIM仿真验证。结果表明,所提出的方法可提高组合遍历法的有效性,并且可降低车辆平均延误时间24.2%,达到提高协调控制效益的目的,具有一定的实际可行性。     

基于相位相序优化的双向绿波协调控制模型

在干线交通各交叉口的周期时长和绿信比等参数已经确定的情况下,基于相位相序进行双向绿波协调控制策略的优化.通过分析上下行方向所在相位的绿灯启亮时刻之间的关系并建立其与绿灯时间的模型,针对具有重叠的协调相位及其特定的取值区间进行相位相序的优化,并将干线左转车流与支路车流提供通行权的非协调相位纳入干线协调中以形成更为合理的组合方案来实现绿波带宽的最大化.仿真结果表明:该方法在一定条件下可以提高绿灯时间利用效率,提高交叉口通行效率.     

基于相位优化的公交优先单点控制策略研究

建立了公交专用道公交独立相位,从交叉口控制策略的各种协同关系出发,系统分析了动态公交相位的优先级关系,提出了公交相位剩余时间的二次分配问题,建立了公交相位实时在线控制逻辑框架,实现了公交相位与社会相位之间的优化组合,最后运用VISSIM进行了系统仿真和效果评价,结果表明优化策略实现了交叉口公交优先和交通畅通有序的控制效果.     

多目标多约束混合流水车间插单重调度问题研究

研究了多目标多阶段混合流水车间的紧急订单插单重调度问题,综合考虑工件批量、刀具换装时间、运输能力等约束.先以最小化订单完工时间和最小化总运输时间为双目标建立静态初始订单调度模型,再针对紧急订单插单干扰,增加最小化总加工机器偏差值目标,建立三目标重调度优化模型,并分别用NSGA-Ⅱ算法与融合基于事件驱动的重调度策略和重排插单策略的NSGA-Ⅲ算法对两个模型进行求解.最后,以某实际船用管类零件生产企业为案例,先对NSGA-Ⅱ算法和NSGA-Ⅲ算法的性能进行评估,得到NSGA-Ⅱ算法更适用于解决双目标优化问题而NSGA-Ⅲ算法在解决三目标优化问题时表现更优的结论,再将所建模型与所提算法应用于该企业的十组插单案例中,所得优化率接近三分之一,验证了实用性和有效性.     

非协调四结点平面等参位移元新列式方法

本文导出一种等参协调元位移函数的新的表示方法,在此基础上建立起了构造等参非协调元的新方法。作为实例,构造两个可以给出单刚显式的四结点平面非协调新单元。     

基于半感应绿波的二次时间分配算法及仿真研究

基于半感应绿波控制策略,分析协调相位与感应相位运行时间关系.针对相位优化产生的感应余量和协调相位弹性调节量等时间结余,研究了相位时间二次分配问题,建立了二次时间分配算法.结合实际交通调查数据仿真分析二次分配算法对绿波交通整体运行控制的合理性,结果表明二次分配算法可有效解决线协调控制存在的绿波损失问题.     

左转保护相位、许可相位设置条件分析

该文在运用已有研究成果的基础上,提出了一种在信号交叉口建立左转保护相位的方法;用定性分析和定量分析相结合的方法分别对左转保护相位、许可相位的设置条件和判定形式做出了分析,建立了左转保护相位、许可相位的判定流程图。     

基于载波相位的GPS测量数据处理方法研究

针对目前工程测量实际中对点位精度要求的进一步提高,提出对不同载波相位的GPS测量数据运用单差模型进行处理,有效地减小或消除由卫星系统引起的测量误差,以期为提高工程测量技术提供参考。     

带浅埋基础的单桩沉降的一种解法

在双折线模型基础上推导单桩桩侧摩阻力的分布 ,以Mindlin课题的弹性理论解求解桩底土体的沉降 ,推导了一系列单桩沉降的解析表达式 ,计算结果可直接用于单桩分析。     

Extensible prototype learning for real-time traffic signal control

Congestion resolution continues to remain a challenge even though various signal control systems have been developed for traffic-intersection control. To address this issue, reinforcement learning (RL)-based approaches that focus on solving the associated data-driven problems have been proposed. However, only a few methods have been developed and applied to dual-ring traffic signal control systems. Therefore, we develop an RL-based traffic signal control model for such a system to efficiently allocate the green interval in different oversaturation states of the conflicting phases. The proposed model employs a deep deterministic policy gradient algorithm to optimize the green value in the continuous action space. Further, we develop an extensible prototype learning framework for application to new intersections without additional transfer learning. The proposed model is validated based on morning peak hours in a simulation environment that reflects the actual intersection phase system and minimum green time constraints. The proposed model achieves an average 20% intersection delay reduction, compared with the fixed control method.     

Optimal allocation of area in hierarchical road networks

This paper deals with the hierarchical road network design using a continuous model. The model is based on a grid road network where roads are classified into three types: access roads, minor arterial roads, and major arterial roads. Using a continuous approximation in which the distance is measured as the rectilinear distance, we obtain a simple approximation for the total travel time. We then find the optimal allocation of area taken up by roads at each level of the hierarchy so as to minimize the sum of the travel and construction costs. The result demonstrates how the total traffic volume, the traffic composition, and the unit construction cost affect the optimal road area. The optimal area of major arterial roads increases with the total traffic volume and the proportions of inward, outward, and through traffic and decreases with the unit construction cost.     

A Generalized Integrated Corridor Diversion Control Model for Freeway Incident Management

This article presents a generalized diversion control model for freeway incident management that is capable of concurrently optimizing the detour rates and arterial signal timings over multiple roadway corridor segments between the freeway and its neighboring arterial. To capture various operational complexities due to the interactions between multiple diversions, this study has developed an extended corridor traffic flow model and integrated it in the overall optimization process. A biobjective control model is developed to maximize the utilization of available corridor capacity while not significantly increasing the total time spent by travelers on the detour route to ensure their compliance to the routing guidance. Genetic algorithm integrated with the rolling time horizon approach is employed to solve the proposed model. Case studies with a stretch of the I‐94 corridor westbound from downtown Milwaukee to Waukesha have demonstrated the potential of the developed model for use in nonrecurrent congestion management.     

Simulation-based optimization method for arterial signal control considering traffic safety and efficiency under uncertainties

This paper proposes an arterial signal control stochastic simulation-based optimization model with traffic safety and efficiency as biobjectives and solves it by a biobjective surrogate-based promising area search (BOSPAS) method. In this model, traffic safety and efficiency are indexed by the average potential collision energy (APCE) and the vehicular throughput of the arterial road, respectively, and the arterial signal control plan is designed in a ring-and-barrier structure. In the BOSPAS method, each solution is evaluated by traffic simulation only once and stochastic evaluation noises of the sampled solutions are smoothed by a shrinking ball method to approximate their biobjective expectations. Based on the solutions and their estimated biobjective values, two surrogate models of biobjectives are constructed and optimized to obtain the nondominated solutions, which will guide the establishment of the joint promising area for sampling in the next iteration. In the numerical experiments, BOSPAS is first tested to outperform three other counterparts (i.e., nondominated sorting genetic algorithm II [NSGA-II], biobjective efficient global optimization [BOEGO], and biobjective promising area search [BOPAS]) by a stochastic FON function from the aspects of convergence and diversity. It is then applied to optimize the signal control plan of an arterial road with six four-leg signalized intersections in Changsha, China. The numerical results show that the nondominated solutions by BOSPAS perform better than those by NSGA-II, BOEGO, and BOPAS under limited simulation budgets, and also mostly outperform three solutions by Synchro, MAXBAND, and MULTIBAND, especially in reducing APCE. In contrast with the field-implemented signal plan, the optimized ones by BOSPAS improve the APCE and the vehicular throughput of the arterial road by at most 50.2% and 24.8%, respectively. Moreover, considering the vehicular throughput of arterial road as one objective may have a negative effect on the vehicular throughput of the overall road network. In conclusion, BOSPAS is promising to address biobjective optimization problems characterized by costly evaluation, high dimensions, and stochastic noises.     

A Genetic Algorithm Approach for Optimizing Traffic Control Signals Considering Routing

Abstract:   It is well known that coordinated, area-wide traffic signal control provides great potential for improvements in delays, safety, and environmental measures. However, an aspect of this problem that is commonly neglected in practice is the potentially confounding effect of drivers re-routing in response to changes in travel times on competing routes, brought about by the changes to the signal timings. This article considers the problem of optimizing signal green and cycle timings over an urban network, in such a way that the optimization anticipates the impact on traffic routing patterns. This is achieved by including a network equilibrium model as a constraint to the optimization. A Genetic Algorithm (GA) is devised for solving the resulting problem, using total travel time across the network as an illustrative fitness function, and with a widely used traffic simulation-assignment model providing the equilibrium flows. The procedure is applied to a case study of the city of Chester in the UK, and the performance of the algorithms is analyzed with respect to the parameters of the GA method. The results show a better performance of the signal timing as optimized by the GA method as compared to a method that does not consider rerouting. This improvement is found to be more significant with a more congested network whereas under a relatively mild congestion situation the improvement is not very clear.     

连续交通道路的理念与设计

针对快速路投资大、隔断城区、景观差等问题,提出连续交通理念,按照连续路与相交道路功能等级的不同把交叉口形式划分为4个等级;通过控制土地利用强度等规划措施达到控制交通容量的目的,应用交通信号联动控制理论,实行“绿波交通”。     

交通流量的混沌特性分析及预测模型研究

基于混沌动力系统的相空间重构和非线性系统的Volterra级数,分析交通流量的混沌特性,研究了一种交通流量的自适应预测模型。在合理选取嵌入维数和延滞时间实现交通流量时间序列相空间重构的基础上,应用小数据量法计算重构交通流量时间序列的最大Lyapunov指数,根据该指数值对交通流量的混沌特性进行分析,并采用庞卡莱截面法对分析结果进行验证;构建交通流量的Volterra预测模型,并采用LMS自适应算法对模型系数进行调整。通过对实际采集的高速公路交通流量数据的仿真研究表明,小数据量法能对交通流混沌特性进行准确判别,构建的二阶Volterra自适应预测模型能够有效地预测交通流量的变化。因此,在判定交通流量存在混沌特性时,可以应用论文构建的二阶Volterra自适应预测模型对其进行准确的预测。     

公路隧道交通拥堵疏散决策技术研究

针对公路隧道发生事故后交通拥堵疏散问题,结合隧道事故等级、事故处理时间、车辆行驶速度,引入交通流、交通波模型,依托重庆某特长公路隧道实际交通量数据,建立公路隧道交通拥堵疏散决策模型,分析公路隧道交通拥堵状态下的疏散控制,通过实例计算和模型仿真,验证了模型的准确性和适用性。结果表明:公路隧道交通拥堵疏散决策模型可非常准确地预判隧道发生各级事故后交通拥堵时间、排队长度等交通特征,依托模型预测结果,可快速制定高效交通诱导方案,实现交通管控和疏散,让公路隧道及所属路段快速恢复高效运行,为公路隧道的安全、高效运营管理提供决策支持。     

城市公共交通准时性影响因素研究

分析了影响公交准时性的关键因素,结合福州市公交调查,提出影响公交在途运行时间可靠性的主要指标有公交车辆中途停靠站延误、交叉口延误和站点间的交通拥堵延误,以根据实际情况提出针对公交准时性的改善措施。     

交通流的有序运动与混沌运动相互转化现象的仿真研究

用Matlab软件编制皮埃莱(Bieriey)模型来产生仿真交通流。在一定的参数组合下,仿真研究了交通流车队中前后车辆之间的车头间距的变化过程。分析了这种车头间距变化过程的曲线。给出该曲线的二维(间距差与速度差)和三维(间距差、速度差、时间)相图。从相图上可以明显地看出存在奇怪吸引子,这说明基于跟驰模型产生的交通流存在着混沌现象。从相图还可以清楚地看出交通流混沌运动与有序运动之间的转化过程。联系交通流的实际情况,对仿真结果做了分析。