A memetic algorithm with adaptive hill climbing strategy for dynamic optimization problems

Dynamic optimization problems challenge traditional evolutionary algorithms seriously since they, once converged, cannot adapt quickly to environmental changes. This paper investigates the application of memetic algorithms, a class of hybrid evolutionary algorithms, for dynamic optimization problems. An adaptive hill climbing method is proposed as the local search technique in the framework of memetic algorithms, which combines the features of greedy crossover-based hill climbing and steepest mutation-based hill climbing. In order to address the convergence problem, two diversity maintaining methods, called adaptive dual mapping and triggered random immigrants, respectively, are also introduced into the proposed memetic algorithm for dynamic optimization problems. Based on a series of dynamic problems generated from several stationary benchmark problems, experiments are carried out to investigate the performance of the proposed memetic algorithm in comparison with some peer evolutionary algorithms. The experimental results show the efficiency of the proposed memetic algorithm in dynamic environments.     

车辆自适应巡航控制策略研究与仿真

为了保证车辆自适应巡航控制(ACC)系统的安全性、跟踪效果和稳定性,基于车辆安全距离模型建立了车辆自适应巡航控制模型,在Trucksim中搭建CACC跟驰控制系统;通过Simulink与Trucksim联合仿真,验证系统的可行性.仿真结果表明,在车辆编队的行驶过程中,前后车的车距始终在设定的安全距离范围内波动,具有良好...     

基于Eclipse平台的车辆自适应巡航控制仿真

自适应巡航控制是一种先进的汽车辅助驾驶系统,可以减轻驾驶员的工作量并且可以提高驾驶的便利性和安全性。目前一般都是通过MatLab仿真曲线来检验车辆自适应巡航控制算法的控制效果,但该方式不够直观形象。基于Eclipse平台,用JAVA语言搭建一个具有动态效果的车辆巡航控制仿真平台。该平台可以模拟多种典型驾驶工况,直观有效地展现车辆自适应巡航控制算法的结果。最后,在该仿真平台上设计最优PD控制算法和智能驱动驾驶（IDM）控制算法验证车辆自适应巡航控制结果。结果表明,该Eclipse仿真平台能够有效地模拟多种驾驶工况,且能够直观有效地验证多种车辆自适应巡航控制算法的结果。     

Real-time optimization of energy consumption under adaptive cruise control for connected HEVs

This paper presents a real-time energy optimization algorithm for a hybrid electric vehicle (HEV) that operates with adaptive cruise control (ACC). Real-time energy optimization is an essential issue such that the HEV powertrain system is as efficient as possible. With connected vehicle technique, ACC system shows considerable potential of high energy efficiency. Combining a classical ACC algorithm, a two-level cooperative control scheme is constructed to realize real-time power distribution for the host HEV that operates in a vehicle platoon. The proposed control strategy actually provides a solution for an optimal control problem with multi objectives in terms of string stable of vehicle platoon and energy consumption minimization of the individual following vehicle. The string stability and the real-time optimization performance of the cooperative control system are confirmed by simulations with respect to several operating scenarios.     

异构通信网联车系统鲁棒协同自适应巡航控制

考虑异构通信下的不确定网联车系统协同自适应巡航控制(CACC)问题,提出一种网联车系统鲁棒协同自适应巡航控制器设计方法.采用伯努利随机过程和具有可变输入延迟的跟踪模型描述具有参数不确定性和丢包及时延的异构通信网联车系统.为降低CACC控制器设计的复杂性,采用分散输出反馈控制结构和线性矩阵不等式技术,求解不确定异构通信网联车系统的CACC控制器.进一步,利用时滞系统方法和频域分析,建立保证闭环系统稳定和网联车辆系统弦稳定结果.最后通过一组四车辆三信道的网联车辆系统的仿真实验验证所提方法的有效性.     

Driver behaviour with adaptive cruise control

This paper reports on the evaluation of adaptive cruise control (ACC) from a psychological perspective. It was anticipated that ACC would have an effect upon the psychology of driving, i.e. make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but workload might be reduced and driving might be less stressful. Drivers were asked to drive in a driving simulator under manual and ACC conditions. Analysis of variance techniques were used to determine the effects of workload (i.e. amount of traffic) and feedback (i.e. degree of information from the ACC system) on the psychological variables measured (i.e. locus of control, trust, workload, stress, mental models and situation awareness). The results showed that: locus of control and trust were unaffected by ACC, whereas situation awareness, workload and stress were reduced by ACC. Ways of improving situation awareness could include cues to help the driver predict vehicle trajectory and identify conflicts.     

Driver behaviour with adaptive cruise control

This paper reports on the evaluation of adaptive cruise control (ACC) from a psychological perspective. It was anticipated that ACC would have an effect upon the psychology of driving, i.e. make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but workload might be reduced and driving might be less stressful. Drivers were asked to drive in a driving simulator under manual and ACC conditions. Analysis of variance techniques were used to determine the effects of workload (i.e. amount of traffic) and feedback (i.e. degree of information from the ACC system) on the psychological variables measured (i.e. locus of control, trust, workload, stress, mental models and situation awareness). The results showed that: locus of control and trust were unaffected by ACC, whereas situation awareness, workload and stress were reduced by ACC. Ways of improving situation awareness could include cues to help the driver predict vehicle trajectory and identify conflicts.     

Data-iteration cooperative adaptive cruise control of mixed heterogeneous vehicle platoons with unknown dynamic characteristics

This paper considers the cooperative adaptive cruise control (CACC) problem of mixed heterogeneous vehicle platoons composed of human-driven and CACC vehicles with unknown dynamic characteristics and an alternative to CACC for platooning of the heterogeneous vehicle platoon is presented. Adaptive dynamic programming is firstly used to learn the dynamic characteristics of acceleration of vehicles from the sampled data. Then the data-iteration optimal CACC controller is computed to ensure that each CACC vehicle can reach a desired inter-vehicle distance and desired common velocity with no prior knowledge of the dynamics of vehicles in the mixed platoon. Moreover, the string stability of the mixed vehicle platoon is derived by establishing some sufficient conditions on the acceleration transfer function of adjacent vehicles. Two simulation experiments of a six-vehicle mixed platoon are used to illustrate the effectiveness of the proposed CACC method.     

模糊PID控制器在自适应巡航控制系统中的应用

车辆的油门控制算法是自适应巡航控制系统(ACC：Adaptive Cruise Control)中的核心算法之一。这里采用的模糊PID算法(Fuzzy PID)是对常用的两输入单输出模糊控制算法的改进。通过使用Matlab／Simulink建立车辆动力学模型和控制器模型,对控制器的性能进行了仿真分析,验证了算法的合理性。     

仿驾驶员多目标决策自适应巡航鲁棒控制

针对目前市场上自适应巡航(adaptive cruise control,ACC)用户使用率低与驾乘人员接受度差的问题,发展了一种多目标自适应巡航控制算法,基于模型预测控制(model predictive control,MPC)理论,综合协调动态追踪性、燃油经济性、驾乘舒适性以及跟车安全性四项存在着一定冲突的控制目标,采用二次型性能指标以及线性不等式约束的形式,将纵向期望加速度决策问题转化成带约束的在线二次规划问题.引入误差修正项,建立闭环反馈校正机制,以补偿模型失配带来的预测误差,同时采用松弛向量法扩展求解可行域,规避了硬约束下二次规划非可行解问题.进一步,各工况下所强化的性能指标与约束空间不同,采用性能指标权重微校与约束空间边界松弛的策略,设计出3种工作模式ACC,以适应熟练驾驶群体的跟驰习惯.仿真结果表明,前车组合工况下,多模式多目标ACC控制能够实现各工作模式之间的无缝切换,并实现良好的期望跟车目的,从而增强ACC系统对复杂道路交通环境的适应性.     

Longitudinal control algorithm for automated vehicle merging

This paper considers longitudinal control of automated vehicle merging in a mathematical approach for automated highway systems. Merging manoeuvre is defined as one vehicle in the merging lane to be inserted in the middle between two vehicles in the main lane at fixed merging point which is the intersection of those two lanes. The main lane vehicles can change speed. To achieve this, the merging vehicle must properly adjust its speed and acceleration such that it reaches the merging point at the right time with the same speed and acceleration as the main lane vehicles. This problem is a little similar to but different from the well-known missile interception problem. The longitudinal control problem is proposed for different road layouts, based on which a unified mathematical model is established. Then a new concept, virtual platooning, is introduced, which effectively avoids a two-point boundary value problem . Based on this concept, an analytic solution with mathematical proof is provided. It is also discretized as a recursive algorithm for real-time use. A dynamic real-time simulation is published at PATH website. This algorithm has been successfully implemented with automated cars.     

跨座式捷运车辆编组分布式固定时间协同巡航控制

为解决跨座式捷运车辆编组协同巡航控制问题,本文提出了基于固定时间理论的跨座式捷运车辆编组分布式协同巡航控制方法.首先,文章建立了跨座式捷运车辆编组动力学模型,明确了编组队列的控制目标,构建了分布式固定时间协同巡航控制架构,提出了跨座式捷运车辆编组分布式固定时间协同巡航控制方法.然后,本文运用代数图论描述编组间的通讯拓扑关系,应用了分布式固定时间终端滑模估计器估计领航编组的位置和速度,设计了分布式固定时间滑模控制器,并基于Lyapunov稳定性理论证明了控制器的稳定性.最后,文章进行了加速–巡航常规工况仿真实验,验证了所提出控制方法的有效性.     

多配送中心危险货物配送路径鲁棒优化

针对危险货物配送路径对不确定因素敏感度较高的问题,提出了鲁棒性可调的多配送中心危险货物配送路径鲁棒优化方法。首先,以最小化运输风险和最小化运输成本为目标,根据Bertsimas鲁棒离散优化理论,建立鲁棒优化模型;然后,在改进型强度Pareto进化算法（SPEA2）的基础上设计一种三段式编码的多目标遗传算法进行求解,在遗传操作中对不同染色体段分别采用不同的交叉和变异操作,有效避免了种群进化过程中不可行解的产生;最后,以庆阳市西峰区部分路网为例进行实证研究,并将配送方案落实到运输过程的路段中,形成具体的运输路径。研究结果表明：在多配送中心下,运用该鲁棒优化模型及算法,能快速得到具有较好鲁棒性的危险货物配送路径。     

Driver usage and understanding of adaptive cruise control

Automation, in terms of systems such as adaptive/active cruise control (ACC) or collision warning systems, is increasingly becoming a part of everyday driving. These systems are not perfect though, and the driver has to be prepared to reclaim control in situations very similar to those the system easily handles by itself. This paper uses a questionnaire answered by 130 ACC users to discuss future research needs in the area of driver assistance systems. Results show that the longer drivers use their systems, the more aware of its limitations they become. Moreover, the drivers report that ACC forces them to take control intermittently. According to theory, this might actually be better than a more perfect system, as it provides preparation for unexpected situations requiring the driver to reclaim control.     

Experimental evaluation of decentralized cooperative cruise control for heavy-duty vehicle platooning

In this paper, we consider the problem of finding decentralized controllers for heavy-duty vehicle (HDV) platooning by establishing empiric results for a qualitative verification of a control design methodology. We present a linear quadratic control framework for the design of a high-level cooperative platooning controller suitable for modern HDVs. A nonlinear low-level dynamical model is utilized, where realistic response delays in certain modes of operation are considered. The controller performance is evaluated through numerical and experimental studies. It is concluded that the proposed controller behaves well in the sense that experiments show that it allows for short time headways to achieve fuel efficiency, without compromising safety. Simulation results indicate that the model mimics real life behavior. Experiment results show that the dynamic behavior of the platooning vehicles depends strongly on the gear switching logic, which is confirmed by the simulation model. Both simulation and experiment results show that the third vehicle never displays a bigger undershoot than its preceding vehicle. The spacing errors stay bounded within 6.8 m in the simulation results and 7.2 m in the experiment results for varying transient responses. Furthermore, a minimum spacing of −0.6 m and −1.9 m during braking is observed in simulations and experiments, respectively. The results indicate that HDV platooning can be conducted at close spacings with standardized sensors and control units that are already present on commercial HDVs today.     

Analysis of vehicle requirements in a general automated guided vehicle system based transportation system

This paper considers a new model of automated guided vehicle system arising from modern transportation systems. The objective is to minimize the vehicle number in order to guarantee the stability of the system. An approximately analytical method is proposed and a numerical example based on simulation is also presented to illustrate the method.     

Analysis of vehicle requirements in a general automated guided vehicle system based transportation system

This paper considers a new model of automated guided vehicle system arising from modern transportation systems. The objective is to minimize the vehicle number in order to guarantee the stability of the system. An approximately analytical method is proposed and a numerical example based on simulation is also presented to illustrate the method.     

提高车辆安全性的输出反馈自适应控制

研究含有时变参数的车辆动力学模型的输出跟踪控制问题.控制目标是使车辆的横摆角速度和质心侧偏角分别跟踪理想的设定值,通过反推方法设计输出反馈自适应控制器.控制器的输出为主动横摆力矩,通过控制主动横摆力矩来控制车辆的输出响应跟踪理想的输出信号,从而提高车辆的安全性.仿真结果表明,该控制器能更好地适应车速和路况的变化,鲁棒性强.     

Making adaptive cruise control (ACC) limits visible

Previous studies have shown adaptive cruise control (ACC) can compromise driving safety when drivers do not understand how the ACC functions, suggesting that drivers need to be informed about the capabilities of this technology. This study applies ecological interface design (EID) to create a visual representation of ACC behavior, which is intended to promote appropriate reliance and support effective transitions between manual and ACC control. The EID display reveals the behavior of ACC in terms of time headway (THW), time to collision (TTC), and range rate. This graphical representation uses emergent features that signal the state of the ACC. Two failure modes—exceedance of braking algorithm limits and sensor failures—were introduced in the driving contexts of traffic and rain, respectively. A medium-fidelity driving simulator was used to evaluate the effect of automation (manual, ACC control), and display (EID, no display) on ACC reliance, brake response, and driver intervention strategies. Drivers in traffic conditions relied more appropriately on ACC when the EID display was present than when it was not, proactively disengaging the ACC. The EID display promoted faster and more consistent braking responses when braking algorithm limits were exceeded, resulting in safe following distances and no collisions. In manual control, the EID display aided THW maintenance in both rain and traffic conditions, reducing the demands of driving and promoting more consistent and less variable car-following performance. These results suggest that providing drivers with continuous information about the state of the automation is a promising alternative to the more common approach of providing imminent crash warnings when it fails. Informing drivers may be more effective than warning drivers.     

基于L1自适应的自动空中加油对接段飞行控制技术

在自动空中加油(AAR,automated aerialre fueling)对接过程中,加油机后方拖出的加油软管锥套受到加油机和受油机的双重气动干扰,呈现不规则摆动运动,受油机要实现与加油锥套的精确对接,要求其飞行控制系统具有鲁棒性和快速的自适应能力,为此提出采用自适应控制器方案,该方案以线性二次调节器(linear quadraticregulator,LQR)比例积分型控制器作为稳定闭环,在此基础上加入自适应控制器,仿真结果表明,采用自适应控制器的受油机自动空中加油飞行控制系统可以实现规定时间内的精确加油对接,既满足瞬态性能要求,又满足稳态精度要求,同时,还解决了由自适应参数跳动带来的舵机操纵过于频繁的问题.该方法可有效提高对接过程中受油机飞行控制系统的抗干扰能力,能够满足自动空中加油对接段的飞行控制要求.