基于MATLAB的汽车操纵稳定性分析

文章利用MATLAB软件强大的计算能力和绘图功能,通过建立汽车操纵稳定性分析模型,对汽车稳态响应和前轮角阶跃输入下的瞬态响应进行了求解分析。结果表明：轮胎的侧偏刚度（绝对值）越大,汽车的操作稳定性就越好;横摆角速度的固有频率越高越好;稳定性因素K应小于0,使汽车有适度的不足转向,有利于行车安全。     

基于MATLAB与ARM的数据通信系统

针对传统单片机与上位机的数据采集与通信系统的速度与外扩展局限性,文章构建了一种基于ARM与以MATLAB为上位机的通信系统。该系统主要运用MAT-LAB新增的设备控制工具箱实现STM32与MATLAB之间的串口通信,简化了流程,提高了工作效率。通过应用该系统对ADXL345采集的加速度信号与MATLAB进行实时通信试验,结果表明该系统通信准确、运行稳定,可用于桥梁结构的健康监测数据传递。     

基于MATLAB基础上的发动机万有特性曲线的建立

发动机性能的好坏直接影响着整车运行的平顺性、安全性、稳定性等,要全面评价发动机性能,万有特性曲线则是一个很好的工具。万有特性曲线是以发动机转速为横坐标,以扭矩或平均有效压力为纵坐标,在坐标系内画出等燃油消耗率曲线和等功率曲线[1]。绘制万有特性曲线的方法有很多种,MATLAB语言是其中之一。本文利用强大的MATLAB绘图工具,绘制了发动机的万有特性曲线,经分析,该方法是一个有效的精确度较高的方法。     

基于MATLAB与CAESAR Ⅱ的管道系统优化设计

文中利用MATLAB和CAESARⅡ实现管道应力分析和最优设计。首先,提出了利用CAESARⅡ和MATLAB进行管道系统应力分析和设计的思路。然后,以简单管道系统为例,应用0.618法和遗传算法分别进行管道系统的单目标和多目标的优化设计,实现了管道设计半自动化动态优化,为实现管道设计自动化提供参考。     

基于信号配时的路网交通流分析及优化研究

文章以南宁市四条主干道上七个交叉口组成的闭合路网为优化对象,通过交叉口交通流量分析,利用R.Kimber饱和流量计算法和F.Webster交叉口信号配时理论,初步拟定车辆延误最小的信号配时方案,然后使用遗传算法优化配时方案,最后利用VISSIM进行交通仿真,验算服务水平指标的变化,验证该优化方案。     

基于最优化方法的边坡稳定可靠度计算分析

文章基于可靠度原理,结合最优化方法和传递系数法求解边坡可靠度指标最小值的优化问题,采用MATLAB软件编写了边坡可靠度通用计算程序,并以贵州省某边坡为例,对其可靠度指标进行计算,同时通过"安全概率"对该边坡的安全性进行了评价。     

船舶溢油故障树分析与事故案例查询系统开发研究

根据故障树分析理论,基于MATLAB/GUI平台,构建了船舶溢油故障树分析与事故案例查询系统。该系统可实现针对船舶溢油事故发生原因和概率的定性和定量分析、及事故案例的多条件筛选查询功能。利用构建的系统对船舶碰撞导致溢油事故故障树模型进行了最小割集、顶事件概率和底事件重要度的求解分析,结果表明该系统操作简便,计算耗时少,结果准确,可以为船舶溢油事故风险分析提供辅助工具,具有很好的实用价值。     

基于Petri网的地铁信号系统可靠性分析

地铁信号系统是地铁系统的中枢神经,同时也是提高地铁运营水平的重要保障。在分析信号系统功能及故障类型的基础上,划分了设备重要度水平。通过地铁信号系统Petri网5大对象子类框架的搭建,分析研究了信号系统重要设备发生故障的情况下,系统各子类的动态Petri网可靠性模型。     

基于VISSIM仿真的交叉口信号配时优化分析

随着我国城市化发展和车辆保有量的增加,城市交通负荷也随之急剧增长,现有交通信号配时方案与交通需求不能很好地匹配.为了缓解交通延误、提高道路通行效率,文章以石河子市北五路一东二路交叉口为例,利用交通仿真软件VISSIM对该交叉口建立微观道路交通流模型并进行仿真优化分析.结果 表明,优化后交叉口排队长度、车辆延误等指标明显...     

基于声电类比法的管系气柱固有频率的计算

基于平面波动理论与电学系统方程的等价,建立管道气柱单元声学等效电路.采用MATLAB/SIMULINKL软件,通过谐振法对气柱系统进行电路仿真,得到其各阶固有频率,并与传递矩阵法计算结果相比较,误差很小,说明采用声电类比法计算气柱固有频率是有效的.     

A real-time traffic signal control system: architecture, algorithms, and analysis

The paper discusses a real-time traffic-adaptive signal control system referred to as RHODES. The system takes as input detector data for real-time measurement of traffic flow, and “optimally” controls the flow through the network. The system utilizes a control architecture that (1) decomposes the traffic control problem into several subproblems that are interconnected in an hierarchical fashion, (2) predicts traffic flows at appropriate resolution levels (individual vehicles and platoons) to enable pro-active control, (3) allows various optimization modules for solving the hierarchical subproblems, and (4) utilizes a data structure and computer/communication approaches that allow for fast solution of the subproblems, so that each decision can be downloaded in the field appropriately within the given rolling time horizon of the corresponding subproblem. The RHODES architecture, algorithms, and its analysis are presented. Laboratory test results, based on implementation of RHODES on simulation models of actual scenarios, illustrate the effectiveness of the system.     

Multi-agent fuzzy signal control based on real-time simulation

In this paper a traffic signal control system based on real-time simulation, multi-agent control scheme, and fuzzy inference is presented. This system called HUTSIG is closely related to the microscopic traffic simulator HUTSIM, both have been developed by the Helsinki University of Technology. The HUTSIM simulation model is used both for off-line evaluation of the signal control scheme and for on-line modeling of traffic situations during actual control. Indicators are derived from the simulation model as input to the control scheme. In the presented control technique, each signal operates individually as an agent, negotiating with other signals about the control strategy. Here the decision making of the agents is based on fuzzy inference that allows a combination of various aspects like fluency, economy, environment and safety. The fuzzy implementation of the HUTSIG signal control system is developed under the FUSICO-project at Helsinki University of Technology.     

基于MOVES的机动车排放分析及控制措施研究

随着我国经济建设的快速发展,人民生活水平的不断提高,城市交通网络的不断拓展,汽车保有量的快速增长,机动车排放污染问题已经成为城市和区域大气污染中增长最为快速的污染源.本文分析了机动车污染物的危害并应用EPA开发的MOVES2010b分析了机动车污染物排放特性.从环保监管、车辆技术更新、交通组织优化等方面提出了相应的机动车减排措施.     

Multi-modal traffic signal control with priority,signal actuation and coordination

Both coordinated-actuated signal control systems and signal priority control systems have been widely deployed for the last few decades. However, these two control systems are often conflicting with each due to different control objectives. This paper aims to address the conflicting issues between actuated-coordination and multi-modal priority control. Enabled by vehicle-to-infrastructure (v2i) communication in Connected Vehicle Systems, priority eligible vehicles, such as emergency vehicles, transit buses, commercial trucks, and pedestrians are able to send request for priority messages to a traffic signal controller when approaching a signalized intersection. It is likely that multiple vehicles and pedestrians will send requests such that there may be multiple active requests at the same time. A request-based mixed-integer linear program (MILP) is formulated that explicitly accommodate multiple priority requests from different modes of vehicles and pedestrians while simultaneously considering coordination and vehicle actuation. Signal coordination is achieved by integrating virtual coordination requests for priority in the formulation. A penalty is added to the objective function when the signal coordination is not fulfilled. This “soft” signal coordination allows the signal plan to adjust itself to serve multiple priority requests that may be from different modes. The priority-optimal signal timing is responsive to real-time actuations of non-priority demand by allowing phases to extend and gap out using traditional vehicle actuation logic. The proposed control method is compared with state-of-practice transit signal priority (TSP) both under the optimized signal timing plans using microscopic traffic simulation. The simulation experiments show that the proposed control model is able to reduce average bus delay, average pedestrian delay, and average passenger car delay, especially for highly congested condition with a high frequency of transit vehicle priority requests.     

An eco-driving system for electric vehicles with signal control under V2X environment

The benefit of eco-driving of electric vehicles (EVs) has been studied with the promising connected vehicle (i.e. V2X) technology in recent years. Whereas, it is still in doubt that how traffic signal control affects EV energy consumption. Therefore, it is necessary to explore the interactions between the traffic signal control and EV energy consumption. This research aims at studying the energy efficiency and traffic mobility of the EV system under V2X environment. An optimization model is proposed to meet both operation and energy efficiency for an EV transportation system with both connected EVs (CEVs) and non-CEVs. For CEVs, a stage-wise approximation model is implemented to provide an optimal speed control strategy. Non-CEVs obey a car-following rule suggested by the well-known Intelligent Driver Model (IDM) to achieve eco-driving. The eco-driving EV system is then integrated with signal control and a bi-objective and multi-stage optimization problem is formulated. For such a large-scale problem, a hybrid intelligent algorithm merging genetic algorithm (GA) and particle swarm optimization (PSO) is implemented. At last, a validation case is performed on an arterial with four intersections with different traffic demands. Results show that cycle-based signal control could improve both traffic mobility and energy saving of the EV system with eco-driving compared to a fixed signal timing plan. The total consumed energy decreases as the CEV penetration rate augments in general.     

Store-and-forward based methods for the signal control problem in large-scale congested urban road networks

The problem of designing network-wide traffic signal control strategies for large-scale congested urban road networks is considered. One known and two novel methodologies, all based on the store-and-forward modeling paradigm, are presented and compared. The known methodology is a linear multivariable feedback regulator derived through the formulation of a linear-quadratic optimal control problem. An alternative, novel methodology consists of an open-loop constrained quadratic optimal control problem, whose numerical solution is achieved via quadratic programming. Yet a different formulation leads to an open-loop constrained nonlinear optimal control problem, whose numerical solution is achieved by use of a feasible-direction algorithm. A preliminary simulation-based investigation of the signal control problem for a large-scale urban road network using these methodologies demonstrates the comparative efficiency and real-time feasibility of the developed signal control methods.     

The development of taiwan arterial traffic‐adaptive signal control system and its field test: A taiwan experience

This Taiwan traffic‐adaptive arterial signal control model borrowed its traffic flow framework mainly from a British traffic‐adaptive control model with a cyclic traffic progression function, i.e. SCOOT (Split Cycle Office Optimisation Technique). The new arterial control model can take into account delays of both major and minor streets and make real‐time signal timing decisions with optimal two‐way signal offsets, so as to create the best arterial signal operation performance. It has been developed to be an online real‐time software for both simulation testing and field validation. Through simulation, it was found that the performance when operating this newly developed real‐time arterial traffic‐adaptive model was significantly better than when using the optimal fixed‐time arterial timing plan. On the aspect of field testing, three signalized intersections located in East District, Tainan City, Taiwan were selected to be the test sites. Fairly good traffic control performance has been demonstrated in that it can effectively reduce travel delays of the control arterial as a whole. Additional discussions about how to combine travel delay and the total number of vehicle stops into a new control performance index have also been included to make the new traffic‐adaptive model more flexible and reasonable to meet the expectations of different driver groups in the arterial system.