基于灰色评价理论的自适应最优路径选择

充分考虑了驾驶员在路径选择中的不同要求,依据层次分析法和灰色评价理论建立了一种根据驾驶员的偏好自适应选择最优路径的方法,并设计了相应的决策支持系统,为智能交通流诱导系统的进一步发展铺平了道路。     

进气管长度可变系统的研究

分析了进气管长度可变系统的构成、主要技术参数和工作原理,指出了此系统的优点、发展趋势和故障检查方法。     

连续刚构桥双薄壁墩参数优化研究

考虑侧向风压产生扭转及温度变化产生纵向变形的作用，通过对双薄壁墩连续刚构桥的受力分析，探讨了双薄壁墩设计的影响因素，以非线性规划为基础，应用罚函数法对双薄壁墩参数进行优化研究。     

模糊自整定PID参数控制器及其在汽车测试设备中的应用

在汽车的控制及测试设备中，广泛使用常规的ＰＩＤ控制器，由于它不具备在线整定ＰＩＤ参数的功能，因此在参数时变较大的系统，其性能难以满足要求。为此本文应用模糊控制技术实现了ＰＩＤ控制器的参数在线自整定，获得了比较理想的效果。本文以汽车传动轴试验台为例，详细地阐述了模糊控制器的设计原理及计算机软件设计方法。     

分段线性变参数控制在数字式自动找平控制系统中的应用

为了验证分段线性变参数控制在自动找平控制系统中的应用前景,对自动找平控制系统的结构、控制方式进行了介绍;分析了分段线性控制方式的工作原理及特点,在实验室建立了沥青混凝土摊铺机数字式自动找平控制系统试验台,设计了3套试验方案,即普通电磁阀方案、高速开关阀方案和分段线性控制方案;对这3种控制方案进行了试验比较,得出了在阶跃干扰作用下,3种控制方案的响应速度及产生超调时的超调量。结果表明:分段线性控制方案具有较快的响应速度,但在系统产生超调时,其超调量相对较大。     

鱼雷发动机三组元比例控制器数值模拟

利用计算流体力学软件Pumplinx模拟鱼雷发动机中三组元比例控制器的内部流场,分析计算中不同压差情况下对比例控制器性能的影响,以及叶片与定子间间隙大小对于比例控制器性能的影响,同时对不同叶片数目下性能进行对比。计算结果表明:由于比例控制器为被动旋转马达结构,其转速和流量均随时间呈周期性脉动变化,随着工作压差增大,转速脉动幅度基本保持不变,而流量和扭矩脉动幅值增加;随着间隙增大,泄漏量增大,但流量、扭矩、转速脉动幅值大幅降低,出口流量较为平稳;叶片数目增多后比例控制器转速降低、排量降低。由计算结果推断出目前比例控制器的最优叶片数目为4。本文可为进一步研究比例控制器精度问题提供参考。     

Methods to reduce dimensionality and identify candidate solutions in multi-objective signal timing problems

Adjusting traffic signal timings is a practical way for agencies to manage urban traffic without the need for significant infrastructure investments. Signal timings are generally selected to minimize the total control delay vehicles experience at an intersection, particularly when the intersection is isolated or undersaturated. However, in practice, there are many other potential objectives that might be considered in signal timing design, including: total passenger delay, pedestrian delays, delay inequity among competing movements, total number of stopping maneuvers, among others. These objectives do not tend to share the same relationships with signal timing plans and some of these objectives may be in direct conflict. The research proposes the use of a new multi-objective optimization (MOO) visualization technique—the mosaic plot—to easily quantify and identify significant tradeoffs between competing objectives using the set of Pareto optimal solutions that are normally provided by MOO algorithms. Using this tool, methods are also proposed to identify and remove potentially redundant or unnecessary objectives that do not have any significant tradeoffs with others in an effort to reduce problem dimensionality. Since MOO procedures will still be needed if more than one objective remains and MOO algorithms generally provide a set of candidate solutions instead of a single final solution, two methods are proposed to rank the set of Pareto optimal solutions based on how well they balance between the competing objectives to provide a final recommendation. These methods rely on converting the objectives to dimensionless values based on the optimal value for each specific objectives, which allows for direct comparison between and weighting of each. The proposed methods are demonstrated using a simple numerical example of an undersaturated intersection where all objectives can be analytically obtained. However, they can be readily applied to other signal timing problems where objectives can be obtained using simulation outputs to help identify the signal timing plan that provides the most reasonable tradeoff between competing objectives.     

Nonlinear pricing in linear cities with elastic demands

Nonlinear road pricing charges each traveler based on his/her trip’s corresponding particular attribute level. In order to help authorities in designing road pricing systems at a strategic level, this paper attempts to address two fundamental questions: (i) what is the value of pricing’s nonlinearity for mitigating traffic congestion? (ii) if a nonlinear toll function is implemented, should it be convex, concave or other shape? Specifically, we consider distance-based pricing in linear cities. For linear monocentric cities with heterogeneous travelers, we show that the system optimal distance-based pricing indeed exhibits nonlinearity. It is proved that: (i) the cost-based system optimal toll function is monotonically increasing and concave with respect to the traveled distance; (ii) the time-based system optimal toll function always exists and is unique. If the initial proportion of each traveler group is invariant along a corridor and the demand function is of exponential type, then the time-based system optimal toll function enables the travelers, living further away from a city center, to face a lower toll level per unit distance. For a linear polycentric city, we demonstrate: (i) there always exists the system optimal differentiated (in terms of city centers) toll functions; (ii) it is highly possible that the system optimal non-differentiated toll function does not exist. Hence, we further propose an optimal toll design model, prove the Lipschitz continuity of its objective and adopt a global-optimization algorithm to solve it.     

Distributed MPC for cooperative highway driving and energy-economy validation via microscopic simulations

Traffic congestion and energy issues have set a high bar for current ground transportation systems. With advances in vehicular communication technologies, collaborations of connected vehicles have becoming a fundamental block to build automated highway transportation systems of high efficiency. This paper presents a distributed optimal control scheme that takes into account macroscopic traffic management and microscopic vehicle dynamics to achieve efficiently cooperative highway driving. Critical traffic information beyond the scope of human perception is obtained from connected vehicles downstream to establish necessary traffic management mitigating congestion. With backpropagating traffic management advice, a connected vehicle having an adjustment intention exchanges control-oriented information with immediately connected neighbors to establish potential cooperation consensus, and to generate cooperative control actions. To achieve this goal, a distributed model predictive control (DMPC) scheme is developed accounting for driving safety and efficiency. By coupling the states of collaborators in the optimization index, connected vehicles achieve fundamental highway maneuvers cooperatively and optimally. The performance of the distributed control scheme and the energy-saving potential of conducting such cooperation are tested in a mixed highway traffic environment by the means of microscopic simulations.     

A traffic-condition-based route guidance strategy for a single destination road network

Most of existing route guidance strategies achieves user optimal equilibrium by comparing travel time. Measuring travel time, however, might be uneasy on an urban road network. To contend with the issue, the paper mainly considers easily obtained inflow and outflow of a link and road capacity as input, and proposes a route guidance strategy for a single destination road network based on the determination of free-flow or congested conditions on alternative routes. An extended strategy for a complex network and a feedback approximation for avoiding forecast are further explored. Weaknesses of the strategy are also explicitly analyzed. To test the strategy, simulation investigations are conducted on two networks with multiple parallel routes. The results indicate that the strategy is able to provide stable splitting rates and to approximate user optimal equilibrium in different conditions, in particular when traffic demand is high. This strategy has potential to be applied in an urban road network due to its simplicity and easily obtained input data. The strategy is also applicable for single destination if some alternatives and similar routes are available.