Connected variable speed limits control and car-following control with vehicle-infrastructure communication to resolve stop-and-go waves

The vision of intelligent vehicles traveling in road networks has prompted numerous concepts to control future traffic flow, one of which is the in-vehicle actuation of traffic control commands. The key of this concept is using intelligent vehicles as actuators for traffic control systems. Under this concept, we design and test a control system that connects a traffic controller with in-vehicle controllers via vehicle-to-infrastructure communication. The link-level traffic controller regulates traffic speeds through variable speed limits (VSL) gantries to resolve stop-and-go waves, while intelligent vehicles control accelerations through vehicle propulsion and brake systems to optimize their local situations. It is assumed that each intelligent vehicle receives VSL commands from the traffic controller and uses them as variable parameters for the local vehicle controller. Feasibility and effectiveness of the connected control paradigm are tested with simulation on a two-lane freeway stretch with intelligent vehicles randomly distributed among human-driven vehicles. Simulation shows that the connected VSL and vehicle control system improves traffic efficiency and sustainability; that is, total time spent in the network and average fuel consumption rate are reduced compared to (uncontrolled and controlled) scenarios with 100% human drivers and to uncontrolled scenarios with the same intelligent vehicle penetration rates.     

路网环境下考虑大型车混入率的事故疏散诱导模型

大型车的混入对高速公路交通流产生了较大的影响,尤其是在交通事故情景下。为了引导事故条件下驾驶人和组织者做出高效准确的决断,将考虑了大型车混入率的动态空间占有率模型引入到交通波模型,构建干涉与非干涉情景下的交通事故影响模型。以郑尧高速为例,对模型的准确性和可行性进行了验证,分别对干涉情景下的疏散时间、疏散量以及事故发生的位置,车辆数等指标与事故影响程度的指标（包含事故最远排队长度,事故持续时间）关系进行分析。研究结果表明：疏散时间与事故影响程度成正相关关系,疏散量与事故影响程度成负相关关系,而事故发生点与上游匝道之间的距离与其关系不大;道路服务水平为0.456,车辆数为1 321 veh·h^-1时,为了使得分合流区不受影响,在不采取任何措施的情景下,应将大型车混入率控制在50.1%以下,使得最远排队长度在10 km内;当大型车混入率大于58%时,将很难通过干涉引导避免对上游分合流区产生影响;在35 min以内采取干涉措施的效果最为明显,而大于35 min时,事故持续时间会发生一个急剧的增加,不利于路网恢复,之后事故恢复时间将趋于平稳;对道路交通量进行模拟可知交通量每增加50 veh,疏散时间和距离增加的范围为[1.5 min,3.6 min]和[1.209 km,1.543 km]。研究结果可为高速公路事故诱导策略制定和疏散效果提升提供参考。     

人机混驾环境下基于LSTM的无人驾驶车辆换道行为模型

道路系统中的人机混驾交通环境是指人工驾驶车辆与自动驾驶车辆混合运行的交通环境,其中换道行为建模是人机混驾环境下无人驾驶车辆行为研究的热点。基于深度学习理论,构建人机混驾环境下基于长短期记忆神经网络的无人驾驶车辆换道行为模型（Long-short-term-memory-based Autonomous Vehicles Lane Changing,LSTM-LC）。通过研究人工驾驶车辆在换道过程中与周边车辆的相互作用,对换道行为影响因素进行分析;同时,为了提升模型的迁移性,引入道路横向偏移量信息。结合LSTM神经网络的输入要求,使用美国公开交通数据集Next Generation SIMulation（NGSIM）构建换道行为样本库。针对LSTM-LC模型,以均方差MSE作为损失函数,使用RMSprop优化方法进行训练,对LSTM网络结构、历史序列长度N及训练样本量3个重要参数进行标定。最后,针对道路横向偏移量M对LSTM-LC模型性能的影响进行对比试验。研究结果表明：相比GRU-LC模型,LSTM-LC模型对换道行为的表征更准确,在模型的精度和迁移性上有着显著的提升;GRU-LC模型的均方差为4.64 m²,迁移性均方差为119.82 m²,而LSTM-LC模型的均方差为3.18 m²,迁移性均方差为79.58 m²,分别优化了31.5%和39.71%;通过引入道路横向偏移量M,可将LSTM-LC模型精度和迁移性提升约10%,且模型稳定性更强。     

城市平面交叉口左转车辆规避效应特性

城市道路交叉口交通隔离栏侵入内侧车道建筑限界,导致车辆横向偏移,增加行车风险。为了解城市平面交叉口交通隔离栏对左转车辆规避行为的影响,通过无人机采集3个设有交通隔离栏的平面交叉口车辆视频,提取车辆轨迹、速度、加速度等参数。分析交叉口出口不同车道车辆偏移和速度的分布特性,研究左转车辆规避特性。结果表明：①两侧车道上行驶的车辆更倾向于向中间车道偏移,中间车道行驶轨迹则较为稳定;②20 m的行程可供驾驶人稳定行驶方向,保持与交通隔离栏的安全横向距离;③左侧车道上85%以上车辆远离交通隔离栏行驶,平均偏移距离为0.278 m;右侧车道上60%左右车辆远离右侧行驶,平均偏移距离为0.116 m。④左转车辆在出口不同车道的速度分布存在显著差异,其中左侧车道和右侧车道上左转车辆速度分布峰值、横向加速度均值、纵向加速度均值均小于中间车道。以此提出城市道路交叉口的改善方法：①增加中分带宽度,提升路侧净距,实现左侧车道名义路权宽度与实际路权宽度一致;②增大硬质设施与驾驶人的横向距离;③开口段硬质设施优化为柔性,减弱设施心理冲击,降低驾驶负荷;④增设路面导流线和反光设施,保证诱导设施的连续性和一致性,提升方向感和速度感,从而减少规避效应过度或不足所带来的安全隐患。     

车辆荷载和车道荷载对桥梁结构可靠度的影响

公路桥梁结构的整体计算采用车道荷载,结构的局部计算采用车辆荷载,车辆荷载与车道荷载的作用不得叠加.将采用这2种荷载设计的结构进行可靠度对比,结果表明,按车辆荷载设计的结构满足正常使用功能的可靠度偏低,更容易发生损坏,这些损坏会影响到结构的正常使用.提出通过调整重型车辆通过桥梁时的交通行驶规则,增大结构按正常使用极限状态设计时车辆荷载的代表值,从而提高按车辆荷载设计的结构可靠度.     

弹性需求下高速公路超限补偿费率优化模型

为了准确刻画超限需求弹性对补偿费率的影响,从用户和系统的角度分别对超限运输的收益和成本进行分析和建模,构造超限运输弹性需求函数,反映超限运输需求量与其运输效益之间的变化关系,将超限运输业者运输行为的选择归结为弹性需求下的用户均衡配流问题,进而利用高速公路管理者与超限运输业者之间的Stackelberg博弈关系,建立了基于弹性需求的高速公路超限补偿费率的双层规划优化模型,并设计了基于模拟退火算法求解的优化算法。结果表明：模型能较好地优化超限补偿费率,使之对超限运输业者进行合理补偿收费和适度惩罚,有效遏制超限运输,从而产生更大的社会与经济效益。     

A closed-loop dynamic simulation-based design method for articulated heavy vehicles with active trailer steering systems

This paper presents a closed-loop dynamic simulation-based design method for articulated heavy vehicles (AHVs) with active trailer steering (ATS) systems. AHVs have poor manoeuvrability at low speeds and exhibit low lateral stability at high speeds. From the design point of view, there exists a trade-off relationship between AHVs’ manoeuvrability and stability. For example, fewer articulation points and longer wheelbases will improve high-speed lateral stability, but they will degrade low-speed manoeuvrability. To tackle this conflicting design problem, a systematic method is proposed for the design of AHVs with ATS systems. In order to evaluate vehicle performance measures under a well-defined testing manoeuvre, a driver model is introduced and it ‘drivers’ the vehicle model to follow a prescribed route at a given speed. Considering the interactions between the mechanical trailer and the ATS system, the proposed design method simultaneously optimises the active design variables of the controllers and passive design variables of the trailer in a single design loop (SDL). Through the design optimisation of an ATS system for an AHV with a truck and a drawbar trailer combination, this SDL method is compared against a published two design loop method. The benchmark investigation shows that the former can determine better trade-off design solutions than those derived by the latter. This SDL method provides an effective approach to automatically implement the design synthesis of AHVs with ATS systems.     

Design of safety-oriented control allocation strategies for overactuated electric vehicles

The new vehicle platforms for electric vehicles (EVs) that are becoming available are characterised by actuator redundancy, which makes it possible to jointly optimise different aspects of the vehicle motion. To do this, high-level control objectives are first specified and solved with appropriate control strategies. Then, the resulting virtual control action must be translated into actual actuator commands by a control allocation layer that takes care of computing the forces to be applied at the wheels. This step, in general, is quite demanding as far as computational complexity is considered. In this work, a safety-oriented approach to this problem is proposed. Specifically, a four-wheel steer EV with four in-wheel motors is considered, and the high-level motion controller is designed within a sliding mode framework with conditional integrators. For distributing the forces among the tyres, two control allocation approaches are investigated. The first, based on the extension of the cascading generalised inverse method, is computationally efficient but shows some limitations in dealing with unfeasible force values. To solve the problem, a second allocation algorithm is proposed, which relies on the linearisation of the tyre–road friction constraints. Extensive tests, carried out in the CarSim simulation environment, demonstrate the effectiveness of the proposed approach.     

Models and methodology for optimal trajectory generation in safety-critical road–vehicle manoeuvres

There is currently a strongly growing interest in obtaining optimal control solutions for vehicle manoeuvres, both in order to understand optimal vehicle behaviour and, perhaps more importantly, to devise improved safety systems, either by direct deployment of the solutions or by including mimicked driving techniques of professional drivers. However, it is non-trivial to find the right combination of models, optimisation criteria, and optimisation tools to get useful results for the above purposes. Here, a platform for investigation of these aspects is developed based on a state-of-the-art optimisation tool together with adoption of existing vehicle chassis and tyre models. A minimum-time optimisation criterion is chosen for the purpose of gaining an insight into at-the-limit manoeuvres, with the overall aim of finding improved fundamental principles for future active safety systems. The proposed method to trajectory generation is evaluated in time-manoeuvres using vehicle models established in the literature. We determine the optimal control solutions for three manoeuvres using tyre and chassis models of different complexities. The results are extensively analysed and discussed. Our main conclusion is that the tyre model has a fundamental influence on the resulting control inputs. Also, for some combinations of chassis and tyre models, inherently different behaviour is obtained. However, certain variables important in vehicle safety-systems, such as the yaw moment and the body-slip angle, are similar for several of the considered model configurations in aggressive manoeuvring situations.     

基于光电导航无人驾驶电动汽车自动寻迹控制系统研究

在轮毂电机驱动电动汽车技术的基础上,采用光电传感器自动辨识行驶路径,利用车辆行驶预瞄理论,开发了无人驾驶汽车自动寻迹行驶控制系统.试验表明,该系统稳定性好、控制精度高和响应速度快.