纯电动商用车异质队列的多目标控制

队列行驶的研究能有效解决商用车货运安全、能耗浪费和环境污染等问题,但现有研究多基于单一跟车目标控制的匀质队列,这在货运场景中无法达到很好的控制效果。本文中构造了纯电动异质商用车队列,为其设计了分布式非线性模型预测控制器。根据道路环境信息和车辆跟车、安全、舒适和节能等特性,分别建立了领航车和跟随车的控制器模型,实现异质队列的多目标控制。为验证所提出控制方法的有效性,由5辆动力学特性相异的商用车组成队列,并搭建了控制仿真平台进行Trucksim/Simulink联合仿真。结果表明,本文中提出的控制算法能有效实现异质商用车队列的多目标控制,与PID定速巡航控制相比,能耗可降低5.3%以上。     

Platoon recognition using connected vehicle technology

This article presents a mathematical model for real-time platoon recognition using the connected vehicle (CV) technology. Platoon information is a crucial part of traffic signal coordination and is difficult to obtain with traditional technologies such as loop detectors. The past work on platoon recognition using CV is very limited and lacked verification on the applicable range or evaluation of the performance of algorithms. The proposed algorithm is focused on estimating platoon characteristics for signal coordination and adaptive signal control with CV's vehicle-to-vehicle communication and an onboard GPS device. First, the detected platoon is identified by a modified critical time-headway. Then, platoon size and starting and ending times are estimated. Lastly, the filtering process for “qualified” detected platoon is proposed to optimize detectability. The results show that the proposed algorithm can estimate well in various traffic conditions and under both fixed-time and actuated signal control without the need for recalibration. Furthermore, two analytical models to estimate the detection rate are proposed and shown to be close to the numerical results and can be used to estimate the required market penetration ratio for the application without field experiments or microscopic simulation. The accuracy of both the recognition algorithm and detection rate estimation is obtained without relying on inputs that are hard to obtain in practice. Accordingly, the proposed algorithm can be an important part of adaptive signal control focusing on real-time coordination in CV environment.     

车-车协同下无人驾驶车辆的换道汇入控制方法

多车协同驾驶是智能车路系统领域的研究热点之一,可有效降低道路交通控制管理的复杂程度,减少环境污染的同时保障道路交通安全。基于多车协同驾驶控制结构,提出了一种无人驾驶车辆换道汇入的驾驶模型及策略,系统分析了多车协同运行状态的稳定条件。在综合分析无人驾驶车辆换道汇入的协作准则、安全性评估后,基于高阶多项式方法,结合车辆运行特性,通过引入乘坐舒适性的指标函数,设计得到无人驾驶车辆换道汇入的有效运动轨迹。通过研究汇入车辆与车队中汇入点前、后各车辆的运动关系,详细分析车辆发生碰撞的类型和影响因素,给出避免碰撞的条件准则,从而确保无人驾驶车辆汇入过程中多车行驶的安全性和稳定性。基于车辆运动学建立车辆位置误差模型,结合系统大范围渐进稳定的条件,选取线速度和角速度作为输入,应用李雅普诺夫稳定性理论和Backstepping非线性控制算法,设计了无人驾驶车辆换道汇入后的路径跟踪控制器。仿真试验和实车试验结果表明：所设计的换道汇入路径是可行、安全的,控制器具有良好的跟踪效果,纵向和横向的距离误差在15 cm以内,方向偏差的相对误差在10%以内。研究结果为智能车路系统中的多车状态变迁与协同驾驶研究提供了参考,可服务于未来道路交通安全设计和评价。     

Safety Oriented Maneuvers for IVHS

The IVHS architecture of the California PATH program organizes traffic into platoons of closely spaced vehicles. Platoons are formed and broken up by two longitudinal control maneuvers, the merge and the split. A third longitudinal maneuver, decelerate to change lane, allows a platoon switching from one lane to another to enter its new lane at a safe spacing and speed. The maneuvers, particularly the merge, can be potentially hazardous. In a merge, the cars in the trail platoon are moving faster than those in the lead platoon, while the gap separating the two platoons is smaller than usual. A sudden deceleration by the lead platoon could cause a high-speed collision. If the relative velocities of the merging platoons can be constrained so that they are guaranteed never to collide at a high relative velocity, the merge can be considered safe. A maximum safe velocity for the trail platoon can be found for any given spacing and lead-platoon velocity. This paper presents a merge maneuver in which the velocity of the trail platoon never exceeds the maximum safe velocity. The controller switches among several feedback control laws that keep the velocity of the trail platoon inside a safe region and within comfort limits on jerk and acceleration, under normal circumstances. This merge maneuver can be considered to be the fastest merge strategy mat does not violate bounds on safety and comfort. The controller is also more robust to changes in the vehicles' acceleration capability than those that use a desired open-loop trajectory

The control approach used for the merge maneuver can be applied to the other maneuvers to ensure that they never result in a collision. The switching controllers for the split and decelerate to change lane maneuvers that are safe and yield a more comfortable ride than those that track a timed trajectory are also presented.     

降低交通排放的干线协调信号控制优化方法

为降低干线道路系统的交通排放量,基于机动车比功率改进红绿灯期间排放因子的标定方法,进而以相位有效绿灯时间为决策变量,构建使机动车排放总量最小化的干线交叉口群时空资源优化模型.分析相邻交叉口间车队延误与相位差的关系,改进以车队延误最小为目标的相位差优化模型.为验证模型,设计一个案例,根据传统方法获得参考配时方案,借助Vissim软件标定红绿灯期间的排放因子,并使用所提方法获得优化配时方案.结果显示,每种污染物绿灯期间的排放因子均明显高于红灯期间;与参考配时方案相比,优化配时方案下各交叉口车辆延误和排放量均减少8~11%.所提模型能同时降低干线交叉口群的车辆延误和交通排放量,可用于优化干线协调信号控制方案,进而缓解交通拥堵.      

基于非线性模型预测控制的车辆纵向队列协调控制

本文中针对基于分层控制结构的车辆队列上、下层控制缺少联系的问题,提出了车辆队列跟驰与个体车辆动力学稳定性协调控制的思路,其基本思想是在保证队列中个体车辆安全稳定行驶的同时,尽可能实现队列跟驰控制的目标。基于非线性模型预测控制(nonlinear model predictive control,NMPC)方法设计了车辆队列协调控制方案,设计了包括跟驰间距误差、跟驰速度误差以及车速与车轮圆周速度差3个子目标的优化目标函数,将队列跟驰与车辆动力学稳定性的协调控制转化为约束优化控制问题;基于序列二次规划(sequential quadratic programming,SQP)方法进行求解,得到车辆前、后轴的制动/驱动力矩来实现上层决策输出的期望跟驰加速度。基于由3车辆组成的非线性队列模型对控制方案进行了仿真分析,结果表明,所提出的基于NMPC的车辆队列协调控制策略可以在大范围操纵工况下,在保证车辆安全稳定行驶的基础上实现队列的跟驰控制。     

网联自动驾驶车辆通过信号交叉口的速度轨迹优化

以网联自动驾驶汽车(Connected Autonomous Vehicle,CAV)为研究对象,研究了CAV车队通过城市信号交叉口的速度轨迹优化控制策略.基于最优控制理论,采用CAV的自动驾驶模型描述车间相互作用,以所有CAV车辆在行驶过程中的总油耗为优化目标,根据信号灯的配时信息建立模型约束,通过优化CAV头车的速...     

路段上集群智能网联汽车的车队形成机制

智能网联汽车是解决城市交通问题的关键技术之一,对于未来城市智能交通体系建设有着关键作用。集群的智能网联汽车已经具备了涌现的基本条件,设计科学合理的交互规则,可以实现车辆的自组织,分布式涌现控制。以微观仿真软件VISSIM及C2X模块为研究平台,修改驾驶模型参数,在C2X模块中编程实现3条交互规则:速度一致、尽量靠近、避免碰撞,在仿真软件中构建单车道仿真模型,运行仿真实验,统计车辆在路段上不同距离形成车队情况,利用车头时距分布的熵值来衡量车流的有序性。仿真结果表明,车辆在运行至50s后初步形成车队,随着时间的增加,形成的车队越稳定,车流熵值在路段上随距离增加而减小,说明形成车队后更加有序,在路段上呈现出涌现现象。     

车队认知能力增强的通信区块间隙优化方法

为了在单车超越车队的过程中缩短超车车辆与车队间通信范围，减少车队通信压力，锁定影响车辆入队的关键车队区块，同时通过将待进入关键区块的车队进行间隙优化调整，为驾驶人提供定制化换道入队引导服务，提出了基于驾驶人超车风格特征参数的车队内信息传输关键区块锁定算法，通过分析影响驾驶人换道入队位置范围的关键因素，将驾驶人换道入队过程分为本车道速度调整过程与入队速度调整过程，利用非参数贝叶斯算法获取驾驶人超车换道特征数据并提出基于关键区块所在车队位置序列的车辆间隙优化调整策略。研究结果表明：超车车辆加速度、与前车预计碰撞时间、与车队相对速度是影响驾驶人换道入队范围的关键因素；通过非参数贝叶斯算法将超车车辆运行数据分类获取的驾驶人换道入队驾驶操作基元，可准确提供驾驶人行为特征关键参数；通过将驾驶人换道特征分为48个子类型，可锁定驾驶人换道入队范围且车队关键区块范围随着超车车辆与车队速度差值不同在各个特征类型上呈现不同变化趋势；针对驾驶人入队特征对待进入车队关键区块的车辆间隙进行优化调整，不仅可以为驾驶人提供可接受的驾驶辅助信息，同时减少了车队间隙产生过程中车辆加速度范围，提升了车队运行的舒适性。     

队列车辆碰撞严重性及车队排布策略

针对自动驾驶车辆队列发生不可避免碰撞的事故场景,研究以整体碰撞严重性达到最低为目标的车队排布策略.首先根据引发事故的障碍物是否会明显影响领航车运动,将碰撞划分为队内碰撞和队外碰撞.队列几何构型一定时,针对均质化队列发生一维碰撞过程建立理论模型,计入碰撞前车辆对前车紧急制动的感应及自车进行紧急制动的过程,计算并定义时间截...     

队列行驶车辆间距对气动特性的影响

为了研究车辆前后间距和车辆数目对智能交通系统中队列行驶车辆气动特性的影响,首先对单辆车进行数值模拟,并将模拟结果与风洞试验结果进行对比,然后对两辆车在5种不同间距下以及3～7辆车在固定间距下队列行驶的情况分别进行了数值模拟及分析。研究表明:单辆车数值模拟结果与风洞试验结果基本吻合。队列行驶车辆随着车辆间距的减小,各车阻力系数不断降低。在固定间距下,随着队列中车辆数目的增加,平均阻力系数可降低20%～30%,阻力最低的车大致处于车队的中心位置。     

基于模拟道路的自治电动小车列队通信系统设计

基于车路协调的汽车列队技术是解决各种交通问题的最佳方案之一。文中以1个1：10模拟真实道路作为试验平台,在此基础上设计自治小车列队通信系统,并且利用ZIGBEE无线通信技术,演示了汽车列队控制,实现了车车之间无线通信,主控制台的实时控制。     

Worst-case scenario development based on Sine with Dwell test and evaluation for vehicle dynamics controller in UCC HILS

The current test methods are insufficient to evaluate and ensure the safety and reliability of vehicle systems for all possible dynamic situations, including the worst case scenarios such as rollover, spin-out and so on. Although the known NHTSA Sine with Dwell steering maneuvers have been applied for the vehicle performance assessment, they are not enough to estimate other possible worst case scenarios. Therefore, it is crucial for us to verify the various worst case scenarios, including the existing severe steering maneuvers. This paper includes useful worst case scenarios based upon the existing worst case scenarios mentioned above and worst case evaluation for the vehicle dynamic controller in a simulation basis and UCC HILS. The only human steering angle was selected as a design parameter here and optimized to maximize the index function to be expressed in terms of both yaw rate and side slip angle. The obtained scenarios were enough to generate the worst case scenario to meet NHTSA worst case definition. It has been concluded that the new procedure in this paper is adequate to create other feasible worst case scenarios for a vehicle dynamic control system.     

车路协同下车队避让紧急车辆的换道引导方法

为保证紧急车辆更安全、高效地到达紧急事故现场,基于车路协同系统,提出车队避让紧急车辆的换道引导策略。针对目标车道无车辆、有车辆和有车队3种不同场景,分别提出确保紧急车辆快速通过的协同换道策略。通过协同换道策略引导紧急车辆前方行驶的车队和目标车道的车辆改变速度以调整车辆间距,使其满足换道安全距离,依据换道轨迹规划使车队完成换道,并提出紧急车辆发送紧急避让信号的位置方法,计算当不影响紧急车辆的速度情况下,其发送紧急避让信号时与车队尾车的最短距离。利用SUMO交通仿真软件,实现车路协同环境下3种不同场景车队避让紧急车辆的换道引导,并比较目标车道为车队的场景下,车队换道至目标车队的每个空档中（方式A）和车队换道至目标车队的同一个空档中（方式B）2种不同的换道引导策略。研究结果表明：目标车道有车队的场景下,方式B的协同换道时间更短,发送紧急信号的位置距车队尾车82 m,较方式A的87 m更近,对周围车辆影响更小,因此此场景采用方式B的协同换道策略;在目标车道无车辆、有车辆和有车队3种场景下,紧急车辆分别距车队尾车71,71,82 m时发送紧急避让信号,其可以维持期望速度,验证了最短距离与车辆速度的关系式;与未使用换道引导策略的情况相比,紧急车辆的速度提高,延误减少。     

Decoupled robust control of vehicular platoon with identical controller and rigid information flow

Platoon driving has potential to significantly benefit road traffic. This study presents a decoupled robust control strategy for a vehicular platoon with identical feedback controller and rigid information topology. The node dynamics of vehicle with a lower-level controller is assumed to be covered by a multiplicative uncertainty model. The vehicular platoon control system is skillfully decomposed into an uncertain part and a diagonal system by applying linear transformation and eigenvalue decomposition on information flow graph. Then the requirements of robust stability and distance tracking error are equivalent to the H-infinity norm of decoupled sub-systems. Comparative simulations with a non-robust controller and different communication topologies are conducted to demonstrate the robust stability and distance tracking performances of the proposed method.     

A real-time multi-vehicle simulator for longitudinal controller design

This paper presents a new multi-vehicle simulator for platoon simulation. The main new feature of the developed simulator is a network structure for the real-time simulation of multiple vehicles, each with a detailed powertrain and engine model. It has a small initial delay, which is determined by the number of connected PCs, but the actual simulation is performed and displayed in real-time after this initial and one-time delay. Several longitudinal controllers, including a PID controller with gain scheduling, an adaptive controller, and a fuzzy controller, are also implemented in the simulator. Various system parameters can be modified interactively in the simulator screen, which is very useful for simulating a platoon of heterogeneous vehicles, in which vehicles with different dynamics and different longitudinal controllers may be involved. The simulator provides an excellent tool to develop vehicle longitudinal controllers and to study platoon behaviors. The developed simulator is also effective in testing the effects of nonlinearities neglected in the controller design phase, such as actuator delays and gear shifting schedule.     

双车道公路超车两难区域研究

基于超车行为分析,提出了双车道公路超车行为的两难区域概念,在该区域内超车车辆既无法完成超车动作又不能在避免与对向车辆相撞前安全避让。应用运动学理论建立了下游车队规模、车速、设计车速与两难区域范围以及安全超车视距之间的关系,发现与超越单车的视距要求相比,超越车队所需的安全视距较大,且随着设计车速、下游车队规模以及车速的增大而增大。并发现当流量或车速较大时,两难区域出现的概率较大,且因驾驶者错误估计引发交通事故的机会增多。最后给出了不同下游车队规模条件下安全超车的速度限制及视距要求,为制定安全行车策略以及道路安全管理提供了理论依据。     

A real-time multi-vehicle simulator for longitudinal controller design

This paper presents a new multi-vehicle simulator for platoon simulation. The main new feature of the developed simulator is a network structure for the real-time simulation of multiple vehicles, each with a detailed powertrain and engine model. It has a small initial delay, which is determined by the number of connected PCs, but the actual simulation is performed and displayed in real-time after this initial and one-time delay. Several longitudinal controllers, including a PID controller with gain scheduling, an adaptive controller, and a fuzzy controller, are also implemented in the simulator. Various system parameters can be modified interactively in the simulator screen, which is very useful for simulating a platoon of heterogeneous vehicles, in which vehicles with different dynamics and different longitudinal controllers may be involved. The simulator provides an excellent tool to develop vehicle longitudinal controllers and to study platoon behaviors. The developed simulator is also effective in testing the effects of nonlinearities neglected in the controller design phase, such as actuator delays and gear shifting schedule.     

Fuzzy Logic Traction Controllers and their Effect on Longitudinal Vehicle Platoon Systems

This paper presents two fuzzy logic traction controllers and investigates their effect on longitudinal platoon systems. A fuzzy logic approach is appealing for traction control because of the nonlinearity and time-varying uncertainty involved in traction control systems

The fuzzy logic traction controllers we present regulate brake torque to control wheel slip, which is the normalized difference between wheel and vehicle speed. One fuzzy controller estimates the peak slip corresponding to the maximum tire-road adhesion coefficient and regulates wheel slip at the peak slip. The controller is attractive because of its ability to maximize acceleration and deceleration regardless of road condition. However, we find through simulations the controller's performance degrades in the presence of time-varying uncertainties. The other fuzzy logic controller regulates wheel slip at any desired value. Through simulations we find the controller robust against changing road conditions and uncertainties. The target slip is predetermined and not necessarily the peak slip for all road conditions. If the target slip is set low, stable acceleration and deceleration is guaranteed, regardless of road condition

We also study the effect of traction control on longitudinal vehicle platoon systems using simulations. The simulations include acceleration and deceleration maneuvers on an icy road. The results indicate traction control may substantially improve longitudinal platoon performance, especially when icy road conditions exist.     

面向新型混合交通流的快速路合流区通行能力建模

面向人类驾驶和具备协同自适应巡航功能的网联自动驾驶组成的新型混合交通流,考虑道路交通特性、道路结构以及匝道汇入前主线交通状态等因素的交互作用机理,基于概率统计理论解析网联自动驾驶渗透率和编队长度间的耦合关系,进一步基于间隙接受理论分析匝道汇入交通对合流区通行能力的折减效应,建立快速路合流区通行能力模型,定量描述不同道路...