Signal control optimization for automated vehicles at isolated signalized intersections

Traffic signals at intersections are an integral component of the existing transportation system and can significantly contribute to vehicular delay along urban streets. The current emphasis on the development of automated (i.e., driverless and with the ability to communicate with the infrastructure) vehicles brings at the forefront several questions related to the functionality and optimization of signal control in order to take advantage of automated vehicle capabilities. The objective of this research is to develop a signal control algorithm that allows for vehicle paths and signal control to be jointly optimized based on advanced communication technology between approaching vehicles and signal controller. The algorithm assumes that vehicle trajectories can be fully optimized, i.e., vehicles will follow the optimized paths specified by the signal controller. An optimization algorithm was developed assuming a simple intersection with two single-lane through approaches. A rolling horizon scheme was developed to implement the algorithm and to continually process newly arriving vehicles. The algorithm was coded in MATLAB and results were compared against traditional actuated signal control for a variety of demand scenarios. It was concluded that the proposed signal control optimization algorithm could reduce the ATTD by 16.2–36.9% and increase throughput by 2.7–20.2%, depending on the demand scenario.     

Robust traffic assignment model: Formulation,solution algorithms and empirical application

ABSTRACT

The deterministic traffic assignment problem based on Wardrop's first criterion of traffic network utilization has been widely studied in the literature. However, the assumption of deterministic travel times in these models is restrictive, given the large degree of uncertainty prevalent in urban transportation networks. In this context, this paper proposes a robust traffic assignment model that generalizes Wardrop's principle of traffic network equilibrium to networks with stochastic and correlated link travel times and incorporates the aversion of commuters to unreliable routes.

The user response to travel time uncertainty is modeled using the robust cost (RC) measure (defined as a weighted combination of the mean and standard deviation of path travel time) and the corresponding robust user equilibrium (UE) conditions are defined. The robust traffic assignment problem (RTAP) is subsequently formulated as a Variational Inequality problem. To solve the RTAP, a Gradient Projection algorithm is proposed, which involves solving a series of minimum RC path sub-problems that are theoretically and practically harder than deterministic shortest path problems. In addition, an origin-based heuristic is proposed to enhance computational performance on large networks. Numerical experiments examine the computational performance and convergence characteristics of the exact algorithm and establish the accuracy and efficiency of the origin-based heuristic on various real-world networks. Finally, the proposed RTA model is applied to the Chennai road network using empirical data, and its benefits as a normative benchmark are quantified through comparisons against the standard UE and System Optimum (SO) models.     

基于响应面和遗传算法的柴油机瞬态过程喷油参数优化

基于台架试验数据,利用响应面法建立了某工程机械用柴油机瞬态过程喷油参数与性能的近似高精度模型,基于此模型采用遗传算法对瞬态过程喷油参数分别进行离线优化研究。结果表明:采用单目标优化确定的燃油消耗率(BSFC)、NO_x比排放量和颗粒质量(PM)比排放量的优化极限分别可达180.23g/(kW·h),8.92g/(kW·h)和0.011 8g/(kW·h),相对原机可降低多达4.5%,34.0%和37.3%。双目标优化的Pareto解集表明,相比于同时优化BSFC和NO_x比排放量,BSFC和PM比排放量更容易同时得到优化。采用权重因子适应度函数的三目标优化结果对应的BSFC,NO_x比排放量及PM比排放量分别为184.70g/(kW·h),12.62g/(kW·h)和0.012 2g/(kW·h),较原机分别降低2.1%,6.6%和35.3%。改进优化模型后,性能优化Pareto解集对应的BSFC和PM比排放量水平都非常接近其优化极限,但NO_x比排放量相对其优化极限仍然较高。     

基于小波和粒子群算法的HEV行驶状况辨识方法研究

针对混合动力汽车(HEV)行驶状况(道路坡度和整车载荷)变化难以有效识别,导致驱动系统控制策略不能有效满足驾驶员意图问题,以混联式HEV为研究对象,提出了基于小波滤波和粒子群算法的HEV行驶状况辨识方法。首先建立了汽车行驶状况辨识模型,采用最小二乘法确立了优化目标函数,其次研究了基于小波滤波和粒子群算法的HEV行驶状况辨识原理,最后进行了行驶状况粒子群智能算法辨识试验。在采集实车数据的基础上,对实车数据进行小波滤波,并运用行驶状况辨识方法对道路坡度和整车载荷进行了辨识,并对辨识结果进行小波滤波,结果表明,试验工况下整车载荷辨识的相对误差绝对平均值为2.71%,道路坡度辨识的相对误差绝对平均值为3.85%,验证了所提出方法的有效性。     

国Ⅴ柴油机SCR系统结构对尿素结晶影响研究

针对某国Ⅴ商用柴油车SCR系统中出现的结晶问题,综合应用CFD模拟和台架试验进行分析研究,提出一系列结构优化和改进方案,改善了SCR前流场状态以及流体的流动均匀性和尿素均匀性,基本消除了排气系统在实际工况下的结晶风险,提高了全系统的抗结晶能力,保证了SCR系统的正常运行。通过对模拟结果和台架试验数据的比对分析,研究了流场分布以及混合器结构对结晶形成产生的影响。     

Singular perturbation composite control of a free-floating flexible dual-arm space robot

The Free-floating Flexible Dual-arm Space Robot is a highly nonlinear and coupled dynamics system. In this paper, the dynamic model is derived of a Free-floating Flexible Dual-arm Space Robot holding a rigid payload. Furthermore, according to the singular perturbation method, the system is separated into a slow subsystem representing rigid body motion of the robot and a fast subsystem representing the flexible link dynamics. For the slow subsystem, based on the second method of Lyapunov, using simple quantitative bounds on the model uncertainties, a robust tracking controller design is used during the trajectory tracking phase. The optimal control method is designed in the fast subsystem to guarantee the exponential stability. With the combination of the two above, the system can track the expected trajectory accurately, even though with uncertainty in model parameters, and its flexible vibration gets suppressed, too. Finally, some simulation tests have been conducted to verify the effectiveness of the proposed methods.     

动力总成悬置支架多目标拓扑优化和强度分析

基于Optistruct,以支架的最小柔度、最大固有频率作为优化目标函数;以应力、体积作为约束函数,对一发动机后拉杆安装支架进行拓扑优化,优化结果表明:在满足悬置支架强度和模态要求下,质量减少了12%。     

基于Moldflow的仪表面罩熔接线验证与结构优化

建立了分析模型,应用Moldflow软件对仪表面罩进行了注塑仿真分析。分析结果表明了熔接线位置,将其与实际零件熔接线缺陷进行了对比验证;同时从仪表面罩结构设计角度提出了可行性解决方案,并总结了在零件结构设计过程中导致熔接线缺陷的关键要素。对比验证结果表明:模流分析能有效指导优化仪表面罩结构,从而减少零件试模次数,提升零件质量,降低制造成本,缩短设计周期。     

某商用车散热器面罩开裂分析与改进

为解决散热器面罩开裂问题,提出了焊点优化方案和散热器面罩加强板外置/加强板内置方案,并进行了模块化设计,制定了2组改进措施。有限元分析结果表明:2种改进措施与原状态相比,均有良好应力改善效果,满足应力要求。     

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研究了高峰时段列车运行的衔接协调对换乘站候车客流量的优化问题。首先分析了换乘站各站台候车客流的组成因素,确定出各运行方向的换乘站台内客流量随时间变化的规律。然后,以时段内换乘站候车客流量的最大值最小为目标,建立优化模型。模型以站台最大可容纳候车人数为约束条件,以各方向列车在换乘站的到达时刻为调整对象,实现了高峰时段换乘站内聚集客流的优化。最后,针对验证案例,设计了遗传算法进行求解,得出了协调较优解,并给出与较劣解的对比分析。结果表明,该优化方法能够有效降低换乘站内的候车客流人数,可为网络化的优化协调工作提供参考。