The prediction of projectile-target intersection for moving tank based on adaptive robust constraint-following control and interval uncertainty analysis

To improve the hit probability of tank at high speed,a prediction method of projectile-target intersection based on adaptive robust constraint-following control and interval uncertainty analysis is proposed.The method proposed provides a novel way to predict the impact point of projectile for moving tank.First,bidirectional stability constraints and stability constraint-following error are constructed using the Udwadia-Kalaba theory,and an adaptive robust constraint-following controller is designed considering uncertainties.Second,the exterior ballistic ordinary differential equation with uncertainties is integrated into the controller,and the pointing control of stability system is extended to the impact-point control of projectile.Third,based on the interval uncertainty analysis method combining Chebyshev polynomial expansion and affine arithmetic,a prediction method of projectile-target intersection is proposed.Finally,the co-simulation experiment is performed by establishing the multi-body system dynamic model of tank and mathematical model of control system.The results demonstrate that the prediction method of projectile-target intersection based on uncertainty analysis can effectively decrease the uncertainties of system,improve the prediction accuracy,and increase the hit probability.The adaptive robust constraint-following control can effectively restrain the uncertainties caused by road excitation and model error.

Novel Distance Measures on Hesitant Fuzzy Sets Based on Equal-Probability Transformation and Their Application in Decision Making on Intersection Traffic Control

The purpose of this study is to reduce the uncertainty in the calculation process on hesitant fuzzy sets(HFSs).The innovation of this study is to unify the cardinal numbers of hesitant fuzzy elements(HFEs)in a special way.Firstly,a probability density function is assigned for any given HFE.Thereafter,equal-probability transformation is introduced to transform HFEs with different cardinal numbers on the condition into the same probability density function.The characteristic of this transformation is that the higher the consistency of the membership degrees in HFEs,the higher the credibility of the mentioned membership degrees is,then,the bigger the probability density values for them are.According to this transformation technique,a set of novel distance measures on HFSs is provided.Finally,an illustrative example of intersection traffic control is introduced to show the usefulness of the given distance measures.The example also shows that this study is a good complement to operation theories on HFSs.

Adaptive neuro-fuzzy interface system for gap acceptance behavior of right-turning vehicles at partially controlled T-intersections

Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in India. Limited priority is observed at a few intersections, where priorities are perceived by drivers based on geom etry, traffic volume, and speed on the approaches of intersection. Analyzing such intersections is complex because the overall traffic behavior is the result of drivers, vehicles, and traffic flow characteristics. Fuzzy theory has been widely used to analyze similar situations. This paper describes the application of adaptive neurofuzzy interface system （ANFIS） to the modeling of gap acceptance behavior of rightturning vehicles at limited priority Tintersections （in India, vehicles are driven on the left side of a road）. Field data are collected using video cameras at four Tintersections having limited priority. The data extracted include gap/lag, subject vehicle type, conflicting vehicle type, and driver＇s decision （accepted/rejected）. ANFIS models are developed by using 80 % of the extracted data （total data observations for major road right turning vehicles are 722 and 1,066 for minor road right turning vehicles） and remaining are used for model vali dation. Four different combinations of input variables are considered for major and minor road right turnings sepa rately. Correct prediction by ANFIS models ranges from 75.17 % to 82.16 % for major road right turning and 87.20 % to 88.62 % for minor road right turning. Themodels developed in this paper can be used in the dynamic estimation of gap acceptance in traffic simulation models.

NSGA-Ⅱ based traffic signal control optimization algorithm for over-saturated intersection group

In order to improve the efficiency of traffic signal control for an over-saturated intersection group, a nondominated sorting genetic algorithm Ⅱ（NSGA-Ⅱ） based traffic signal control optimization algorithm is proposed. The throughput maximum and average queue ratio minimum for the critical route of the intersection group are selected as the optimization objectives of the traffic signal control for the over-saturated condition. The consequences of the efficiency between traffic signal timing plans generated by the proposed algorithm and a commonly utilized signal timing optimization software Synchro are compared in a VISSIM signal control application programming interfaces （SCAPI） simulation environment by using real filed observed traffic data. The simulation results indicate that the signal timing plan generated by the proposed algorithm is more efficient in managing oversaturated flows at intersection groups, and, thus, it has the capability of optimizing signal timing under the over-saturated conditions.

Double-directional control bolt support technology and engineering application at large span Y-type intersections in deep coal mines

Under deep and complex geological conditions,severe deformation occurs at intersection points of Y-type roadways with large cross sections during engineering projects in coal mines,especially at junction arches.Based on in-situ investigations and theoretical studies,we have summarized typical forms of destruction and identified high stress and unrestricted support at both sides of junction arch as its main causes.In this study,we also presented double-directional control bolt support technology for a large Y-type span intersection,applied to deep intersection engineering in the Jiahe Coal Mine,which has proved effective.

Coordinated control method of intersection traffic light in one-way road based on V2X

One-way roads have potential for improving vehicle speed and reducing traffic delay.Suffering from dense road network,most of adjacent intersections’distance on one-way roads becomes relatively close,which makes isolated control of intersections inefficient in this scene.Thus,it is significant to develop coordinated control of multiple intersection signals on the one-way roads.This paper proposes a signal coordination control method that is suitable for one-way arterial roads.This method uses the cooperation technology of the vehicle infrastructure to collect intersection traffic information and share information among the intersections.Adaptive signal control system is adopted for each intersection in the coordination system,and the green light time is adjusted in real time based on the number of vehicles in queue.The offset and clearance time can be calculated according to the real-time traffic volume.The proposed method was verified with simulation results by VISSIM traffic simulation software.The results compared with other methods show that the coordinated control method proposed in this paper can effectively reduce the average delay of vehicles on the arterial roads and improve the traffic efficiency.

Dynamic signal control for at-grade intersections under preliminary autonomous vehicle environment

Autonomous vehicle technology will transform fundamentally urban traffic systems.To better enhance the coming era of connected and autonomous vehicles,effective control strategies that interact wisely with these intelligent vehicles for signalized at-grade intersections are indispensable.Vehicle-to-infrastructure communication technology offers unprecedented clues to reduce the delay at signalized intersections by innovative information-based control strategies.This paper proposes a new dynamic control strategy for signalized intersections with vehicle-to-signal information.The proposed strategy is called periodic vehicle holding(PVH)strategy while the traffic signal can provide information for the vehicles that are approaching an intersection.Under preliminary autonomous vehicle(PAV)environment,left-turning and through-moving vehicles will be sorted based on different information they receive.The paper shows how PVH reorganizes traffic to increase the capacity of an intersection without causing severe spillback to the upstream intersection.Results show that PVH can reduce the delay by approximately 15%at a signalized intersection under relatively high traffic demand.

Coordinated Control of Traffic Signals for Multiple Intersections

The proper phase difference of traffic signals for adjacent intersections could decrease the time of operational delay. Some theorems show how to minimize the total average delay time for vehicle operating at adjacent intersections under given conditions. If the distance and signal cycles of adjacent intersections satisfy with specific conditions, the total average delay time would achieve zero. If the signal cycles of adjacent intersections and the phase difference of them are co-prime numbers, the total average delay time would be a constant. In general, if signal cycles of adjacent intersections and the phase difference of them are reducible numbers, the minimum total average delay time would be solved by the given algorithm. Numerical experiments have verified the rationality of these theorems.

The Study of Fuzzy Line Control for Multiple Intersections

The line control for multiple intersections is a hot spot in the area of transportation. According to the principle of system analysis and coordination, a method about fuzzy line control for multiple intersections is proposed. The system is made of two control units, one is the basic control unit for every single intersection, and the other is used for the function of coordination.

Vehicle conflict resolution algorithm at non-signalized crossing based on inter-vehicle communication

A vehicle conflict detection and resolution method is proposed based on the concept of vehicle infrastructure integration （VII） system to prevent vehicle accident beforehand at blind cross- ing. After analyzing traffic conflict characteristics and vehicle collision scenarios at intersection, a vehicle dynamics model and an inter-vehicle communication method are discussed. In the inter-vehi- cle communication environment, the relative relationship between two encountered vehicles are de- signed. Then vehicle conflict detection and resolution algorithms under two conflict scenarios are put forward to represent the conflict-free movements of vehicles with adjusting vehicle velocity at cross- ing. Finally, simulation studies are carried out and the results prove that the proposed algorithms are effective for vehicle conflict resolution at blind crossing.

非理想相贯焊缝自动化焊接的运动控制研究

为了实现对加工装配存在误差的大构件相贯焊缝的多层多道自动化焊接,在介绍四轴联动焊接机器人结构及工作原理的基础上,建立了集斜交、偏置的通用相贯焊缝数学模型,提出一种连续控制焊枪位置参数及姿态调整值的计算方法,利用关键点示教+分段空间圆弧插补确定焊枪位置,主法面二分角法给出焊枪姿态,最后采用PC机+运动控制卡的方式构成伺服控制系统,驱动电机执行运动控制算法。该运动控制算法通用性较强,对管管焊缝工程化应用具有重要的参考价值。

基于生态驾驶的自动驾驶汽车交叉路口控制策略研究

为了进一步提高自动驾驶汽车在交叉路口行驶时的燃油经济性,基于模型预测控制(MPC)理论,量化分析了车辆安全性、经济性、舒适性等多性能指标函数及约束,并设计了以经济性为主的交叉路口自动驾驶汽车生态驾驶控制器。仿真结果表明,所提出的控制策略能够保证良好的安全性和舒适性,与LQR控制器相比,在有前车影响和无前车影响工况下的百公里油耗分别降低15.83%和34.98%。

网联车辆编队的信号灯路口通行控制策略

为提高信号灯路口场景下车辆编队的安全性和通行效率,提出V2X环境下网联车辆编队的信号灯路口通行控制策略。在信号灯路口上游设置一段控制区,以车辆编队领航车在信号灯路口排队疏散后到达信号灯路口为目标,对进入控制区的车辆编队速度进行优化。考虑速度变化对车辆编队纵向安全距离的影响,引入分布式模型预测控制理论,建立固定跟车时距控制策略下编队车辆的速度跟随控制模型,并采用加权二次型性能泛函将速度跟随控制问题转化为易于在线求解的凸二次规划问题。通过PreScan/Simulink软件仿真将信号灯路口通行控制策略与固定跟车时距控制策略进行对比,以验证速度跟随控制模型的有效性,结果表明:信号灯路口通行控制策略能够避免车辆间碰撞冲突,并可以减少编队车辆在信号灯路口的通行耗时,在保证安全性的同时提高了通行效率。

基于A2C的匝道相联交叉口信号控制优化

城市快速路的交通运行效率对于整个城市的顺畅通行至关重要,在早晚高峰期间,受限于相连接辅路的交通承载能力,快速路上较大的交通流量无法顺利从出口匝道驶入目标路段,在匝道上形成排队现象,严重时会导致匝道回溢,使快速路上车道由于被占用而产生交通瓶颈,造成较大的交通出行损失.利用深度强化学习算法进行出口匝道相关联的道路交叉口信号控制优化,将信号灯设为智能体,通过设置检测器,将快速路出口匝道及交叉口的交通运行情况作为智能体获取的状态信息,引入以辅路与出口匝道剩余通行能力之比为动态修正参数的奖励函数,在保证匝道交通运行效率下,完成交叉口信号优化过程.以中国北京市东三环快速路及某关联交叉口为例,借助交通仿真平台SUMO(simulation of urban mobility)及Traci库搭建仿真环境进行实验.结果表明,基于改进A2C(advantage actor critic)算法的信号控制方法在控制效果上优于传统信号控制以及基于深度Q网络(deep Q-network,DQN)算法的信号控制方法,在出行高峰期间能够有效降低匝道回溢的发生概率,有效改善辅道相联交叉口的通行效率.

基于物联网的城市交叉路段交通信号智能控制方法

城市交叉路段交通信号采集系统采集到的信号频谱中线谱信号较少,导致采集速度较慢。为了解决上述问题,提出基于物联网的城市交叉路段交通信号智能控制方法。系统硬件选用FL2440微处理器处理数据,通过YHSG-86G的传感器放大信号。利用双通道模式输出通信数字,选择具备三路HDMI信号与一路HDMI信号自动切换功能的嵌入器。采用GH89S信号采集器提高系统对交通信号的采集效率。在硬件设计的基础上,引入模糊关联规则算法对交通信号数据进行挖掘,通过数据分类、挖掘交叉路段交通信号数据、信号标识、信号存储获取交通信号数据。以此实现城市交叉路段交通信号智能控制。实验结果表明,所提方法能够更清晰地显示出信号频谱中的线谱信号,提高信号的采集速度。

基于强化学习的交叉口智能网联车多目标通行控制方法

针对传统控制方法下的智能网联车辆(connected and autonomous vehicle,CAV)在动态交通环境中通行能耗较高且效率较低等问题,研究了基于强化学习的CAV通行控制方法,旨在降低车辆能源消耗,提升车辆通行效率以及行驶舒适度。通过考虑CAV与交叉口信控系统的信息交互和物理环境,收集信号相位和信号配时(SPaT)以及前车速度和位置等信息,构建强化学习框架的状态空间。以电池能量回收的上限作为边界条件,建立CAV的行驶能耗模型,并基于车辆行驶的关键特征指标,如单位时间电能能耗、通行距离以及加速度变化率,设计多目标加权奖励函数。利用层次分析法确定各指标的权重,进而采用深度确定性策略梯度算法对模型进行训练,并通过梯度下降方法对算法参数进行调整和更新。采用SUMO平台开展仿真实验,实验结果表明:在设计的算法控制下的CAV各方面行驶性能最为均衡,相较于DQN算法电能消耗和加速度变化率均值分别降低了9.22%和18.77%;相较于Krauss跟驰模型行程时间缩短了8.39%。本研究提出的CAV通行控制方法在降低车辆能耗、提高行驶效率和舒适性等方面具有较好的可行性和有效性。

平行流交叉口车道控制与信号配时组合优化

为了提升平行流交叉口实际应用的灵活性,提出车道控制与信号配时组合优化方法,将单向、非对称双向、对称双向、三向、四向设置与布设方向组合共16种方案整合到优化模型中,通过修正交通冲突矩阵自动生成相位相序方案.构建混合整数线性规划模型,实现交叉口设置方案选择、车道分配和信号配时的组合优化.结果表明,在各种流量场景下,对称双向、三向、四向设置方案相较于常规交叉口分别能够提升约20%、20%、50%的通行能力,单向、非对称双向设置方案通行能力与常规交叉口接近,说明平行流交叉口不宜采用单向、非对称双向设置.四向设置方案通行能力的提升幅度最大,最大值能达到70.51%.对称双向和三向设置方案的通行能力提升相差不大,但三向设置在不对称流量场景中的表现优于对称双向设置.

融合注意力机制LSTM网络的城市交叉口信号控制

随着国内机动车保有量的快速提升,城市道路交叉口场景在高密度车流情况下易导致长距离拥堵。为降低交叉口车流拥堵长度,深度强化学习逐渐应用于交叉口信号的控制。而现有交叉口信号控制策略存在对车流状态信息的权重特征欠考虑及时序特征难提取的问题,因此基于深度Q学习(deep Q-learning,DQL)算法提出了一种改进DQL算法,利用注意力机制增强长距离拥堵状态信息的权值,进一步采用长短期记忆网络(long short-term memory,LSTM)学习车流的历史数据,改进了DQL算法对数据不同部分重要性考虑不足及历史数据信息提取欠佳的问题。实验结果表明,所提改进DQL算法与原算法相比,能够降低20%的车辆累计等待时间并且减少21.2%的车辆平均排队数目,提高了交叉口的车辆通行效率。

基于冲突相位组的自动驾驶交叉口行人过街控制方法

【目的】在无信号控制的自动驾驶环境下,自动驾驶车辆的通行轨迹将与过街行人产生大量冲突,如何利用交通控制手段使行人安全通过交叉口,并避免对自动驾驶车辆的通行造成较大的干扰,是亟待解决的关键问题。【方法】本文提出一种基于冲突相位组的自动驾驶交叉口行人过街控制方法,将到达交叉口的车辆流向分为4个冲突相位组,在各相位组内单独分配通行时间,基于冲突相位组对自动驾驶车辆和行人过街的通行时间进行建模;在穿插式通行模式的基础上,使用行人信号灯保障行人过街需求,建立考虑行人二次过街的自动驾驶交叉口交通控制模型。模型以交叉口各流向需求量与实际交通量乘积之和最大为目标,以各流向允许车辆通行的时间比例和行人信号灯状态为决策变量,综合考虑交通流量、行人和车辆通行权等约束,建立混合整数线性规划模型(mixed-integer linear program,MILP),该控制模型可为各流向的车辆和行人分配通行权。【结果】本文模型的车均延误较定时控制方案的降低26.74%,较单次过街模型的降低11.53%,人均延误较定时控制方案的降低51.66%,较单次过街模型的降低36.20%。这表明本文模型能有效提升交叉口的通行效率。【结论】本文模型能根据自动驾驶车辆和行人的通行需求,对交叉口时空通行权进行分配,有效保障行人过街安全。

信号交叉口跟驰模型及其参数标定研究

为了更好地运用跟驰模型描述车辆在信号交叉口的通行过程,提出一种考虑信号灯变化对车流瞬时冲击的交叉口全速度差和加速度(full velocity difference and acceleration at intersection,FVDA-I)模型,并根据车辆轨迹数据标定了跟驰模型参数。首先,构建位置-时间临界轨迹来判断车辆能否在绿灯时间内通过交叉口,并提出转弯车辆优化速度。然后,使用S-G滤波器对车辆位置进行平滑拟合,结合期望最大化(expectation maximum,EM)算法标定模型参数。最后,运用FVDA-I模型估计车辆在交叉口的通行时间以验证模型的有效性。仿真结果表明:相较于改进全速度差(full velocity difference,FVD)模型,FVDA-I模型具有头车启动舒适缓慢、跟随车辆启动快、车队总通行时间短的特点,通行效率提高了11.3%,车辆的通行时间与实际采样轨迹的估计时间对比误差小于10%。