Lateral dynamics of single unit skid-steered tracked vehicle

In the design and development of high-speed tracked vehicles, it is necessary to have an understanding of the interrelationship between the terrain factors and the vehicle characteristics during steering. The handling behavior of skid-steered tracked vehicles is more complex than that of wheeled vehicles because of non-linear characteristics arising from the sliding interface between the track and the ground. In the present work, a five degree-of-freedom (DOF) steering model of a tracked vehicle is developed, and the handling behavior during non-stationary motion is studied when operating at high and low speeds. It is demonstrated that the inclusion of roll and pitch DOF changes the steering response when compared to the response from three DOF models proposed earlier by several researchers. This is due to the strong coupling between the pitch and yaw motions. The effect of the initial forward velocities on the trajectory of the vehicle during non-stationary motion is also studied. It is observed from the results that the stability is influenced by the type of steering input, steering ratio and vehicle forward speed.     

Performance of spade-less wheeled military vehicles with passive and semi-active suspensions during mortar firing

Many armies are replacing heavy slow tracked vehicles with their lighter wheeled counterparts for their high mobility and better shoot and scoot capabilities. These features make the vehicle hard to track and target in counter-battery fire. However, when firing high calibre guns, spades are needed to connect the vehicle chassis to the ground, so as to transmit parts of the large firing force directly to the ground. Use of spades hinders the vehicle mobility, while elimination of them paves the way for having quicker and more mobile wheeled vehicles. In this article, vibration response of a spade-less High Mobility Multi-purpose Wheeled Vehicle with a mounted mortar is studied and controlled using stock passive, optimised passive, and optimised semi-active dampers as primary suspensions. The spade-less vehicle with optimised passive and semi-active dampers has a better response in heave, pitch, and fore-aft motions and can fire with better accuracy compared to a spade-less vehicle with stock passive dampers. Simulation results indicate that the spades can be removed from wheeled military vehicles if the precautions are taken for the tyres.     

Analytical Wheel Models for Ride Dynamic Simulation of Off-road Tracked Vehicles

This paper outlines various analytical approaches of varying complexities to model the wheel in the ride dynamic formulation of off-road tracked vehicles. In addition to a proposed model, four analytical models available in the literature are compared to study their effectiveness in modeling the wheel/track-terrain interaction for ride dynamic evaluation of typical high mobility tracked vehicles. The ride dynamic model used in this study describes the bounce-pitch plane motion of an armoured personnel carrier (Ml 13 APC) traversing over an arbitrary rigid terrain profile at constant speed. The ride dynamic response of the tracked vehicle is evaluated with different wheel models, and compared against field-measured ride data. The relative performance of different wheel models are assessed based on the accuracy of response prediction and associated computational time. The proposed wheel model is found to perform very well in comparison, and is equally applicable for the case of wheeled vehicles.     

基于车联网BSM数据与路侧视频融合的港口集装箱卡车碰撞危险辨识方法

大型港口集装箱码头运输车辆调度频繁,堆场过道和交换区等区域视距狭窄,容易导致港口集装箱卡车与设施、作业人员和车辆发生擦碰事故。为提高智能集装箱卡车在港口密集区域的轨迹跟踪精度和行车安全感知能力,提出了一种车联网条件下融合车载终端基本安全消息（Basic Safety Messages,BSM）数据和路侧视频数据的集装箱卡车碰撞风险辨识方法。采用YOLOv5s算法提取视频监控范围内的目标车辆和作业人员,根据目标集卡大尺寸特点设计非极大值抑制锚框来提高目标识别准确度。运用透视变换原理将目标像素坐标转换成地理坐标,并应用Deep-SORT算法匹配每帧图像的车辆轨迹信息。应用交互式多模型方法（interactive multi-model,IMM）融合视频轨迹信息和车载单元（on-board units,OBU）定位数据,减小了目标机动过程中的观测误差。基于集卡融合轨迹结果,提出了1种新型的轨迹冲突风险评估模型,能够根据目标集卡与周围目标轨迹的相对运动状态实时感知车辆碰撞危险,该碰撞危险检测结果在实际场景中可通过路侧设备对车载终端和作业人员终端实时播发预警信息。针对集卡跟踪误差的实验结果表明：...     

混合动力与现代陆军装备

简要介绍了美国陆军与戴克集团、通用公司等合作在陆军装备的履带车辆和轮式车辆上应用混合动力的研制和试验情况,日本三菱公司等在民用车辆采用混合动力方面取得的成果,德国磁电机公司在军用车辆上的研究情况;论述了混合动力在燃油经济性、加速性、可靠性和排放等方面所具备的优势及应重点掌握的关键技术;对发展我国军民用混合动力时应注意的一些原则提出了自己的建议。     

车路协同条件下智能网联汽车一体化决策模型

为了探索当前有限数据条件下面临的无限交通场景问题,提出车路协同条件下基于深度强化学习智能网联汽车决策模型。利用Actor-Critic机制,以highway-env为数据来源,抽取144 h交通数据作为训练数据并进行验证,分析了智能网联汽车在不同车道数条件下的驾驶行为。结果显示,本模型汽车行程时间减少20%以上,碰撞概率减少25%以上,换道轨迹可以通过动力学跟踪。     

某轮式装甲人员输送车技术性能及特点

介绍了轮式装甲人员输送车的地位和现状,分析了国内外装甲车市场的形势,并以某轮式装甲人员输送车为例,详细阐述了该车辆的技术性能及特点。     

基于车辆运行数据的纯电动汽车用户驾驶风格识别与驾驶能耗分析

驾驶风格是用来体现驾驶员在车辆运行状态下对车辆操作的行为特征,对用户驾驶风格进行识别与分析,有利于推进智能驾驶的发展。根据基于116 辆纯电动汽车的车辆运行数据,通过主成分分析方法与K-means 聚类算法,对用户驾驶行为进行分类分析,对驾驶风格进行了分类识别。利用XGBoost 算法构建纯电动汽车驾驶行为与能耗输入模型,利用SHAP 对模型进行解释。结果表明,将驾驶风格聚为3 类具有较好的分类效果,可分别对应冷静型、普通型与激进型;当驾驶员的驾驶风格趋向于激进型时时,车辆的驾驶能耗越高,驾驶风格激进一个层级,车辆百公里电耗增加3~4倍。当驾驶员行车时,其车速越高,油门踏板踩得越深,车辆加速度的绝对值越大,车辆的驾驶能耗越高。驾驶员的驾驶风格越激进,车辆的驾驶能耗越高。     

全挂汽车列车弯路运动轨迹计算机仿真

本文建立了全挂汽车列车转弯模型，并由此引申出全轮转向汽车轨迹的算法，使公路行驶轮式车辆轨迹的描述得到了统一；进行了计算机仿真。     

Influence of the transmission configuration of a multiple axle vehicle on the obstacle surmounting capacity

Conventional wheeled vehicles have serious mobility limitations in rough terrain while walking vehicles have inherent drawbacks such as a high number of DOF and actuators, control complexity and low-energy efficiency. Vehicles that passively adapt the position of multiple wheels to maintain contact with the ground can be a good compromise between both conventional wheeled and walking vehicles. One way to increase the number of wheels in contact with the ground is using bogies. However, the kinematics of a multiple axle vehicle moving on irregular terrain is quite complex since every wheel can require different angular speed to avoid slippage. The present work aims to quantify the obstacle surmounting capacity of a four axle, double-bogie vehicle depending on the transmission configuration, since it can provoke the slippage of some of its wheels.

Some results are presented corresponding to the vehicle moving on a straight upward slope of different angles and facing variable obstacles in any of its axles.

It can be observed that as more restricted the transmission is, more wheels are forced to slip and less traction the vehicle has, and, as a consequence, less obstacle surmounting capacity.     

基于模式识别与ST-MRF相结合的车辆检测方法

车辆检测技术的主要难点是在于解决车辆之间的遮挡,以及由于光照变化引起的车辆与其阴影之间的遮挡问题,这些问题将直接影响检测的精度.针对这个问题,在原ST-MRF方法上研究了基于模式识别与ST-MRF相结合的车辆检测方法.模式识别技术分割相互遮挡的2辆车之间的边界,并识别相互遮挡车辆的边缘间隙以及边界信息,模式识别结果反馈...     

江苏响水滩涂土壤圆锥指数试验研究

圆锥指数法(WES)是一种用来快速判断车辆通过性的方法。江苏沿海滩涂风力资源丰富,但滩涂土壤松软,普通车辆难以行驶,为保证风电开发施工设备在江苏沿海滩涂安全行驶通过而不发生陷车,三一电气有限责任公司自行设计了一种圆锥指数仪,用以测量滩涂土壤圆锥指数,判断车辆通过性。对响水滩涂T4风机位附近土壤的圆锥指数进行测量,得到了该区域扰动和非扰动两种情况下的土壤圆锥指数曲线,并对滩涂履带运输车的车辆圆锥指数进行了理论计算,根据试验和理论计算的结果进行了滩涂履带运输车实地行驶试验。试验表明,该型运输车在此区域通过性良好。该试验也为评估其它各种车辆在该地区的行驶通过性提供了数据参考。     

基于深度强化学习的车辆跟驰控制

针对自适应巡航控制系统在控制主车跟驰行驶中受前车运动状态的不确定性影响问题，在分析车辆运动特点的基础上，提出一种能够考虑前车运动随机性的跟驰控制策略。搭建驾驶人实车驾驶数据采集平台，招募驾驶人进行实车跟驰道路试验，建立驾驶人真实驾驶数据库。假设车辆未来时刻的加速度决策主要受前方目标车辆运动影响，建立基于双前车跟驰结构的主车纵向控制架构。将驾驶数据库中的驾驶数据分别视作前车和前前车运动变化历程，利用高斯过程算法建立了前车纵向加速度变化随机过程模型，实现对前方目标车运动状态分布的概率性建模。将车辆跟驰问题构建为一定奖励函数下的马尔可夫决策过程，引入深度强化学习研究主车跟驰控制问题。利用近端策略优化算法建立车辆跟驰控制策略，通过与前车运动随机过程模型进行交互式迭代学习，得到具有运动不确定性跟驰环境下的主车纵向控制策略，实现对车辆纵向控制的最优决策。最后基于真实驾驶数据，对控制策略进行测试。研究结果表明：该策略建立了车辆纵向控制与主车和双前车状态之间的映射关系，在迭代学习过程中对前车运动的随机性进行考虑，跟驰控制中不需要对前车运动进行额外的概率预测，能够以较低的计算量实现主车稳定跟随前车行驶。     

Two-Dimensional Motion of Four-Wheel Vehicles

This paper deals with two-dimensional motion of vehicles. Since the general four-wheel vehicle model is statically indeterminate, the motion of vehicles has been analyzed by replacing the vehicle with the equivalent two-wheel one proposed by E. Marquard. Because this approximation is based on the axisymmetry of vehicles, it causes significant errors in the general case. To improve the accuracy of the analysis of vehicle motion, a four-wheel model is suggested. In this model, it is assumed that the chassis remains in a flat plane during motion. By introducing this condition, the motion of the vehicle can be analyzed. Several results from the four-wheel model and the equivalent two-wheel model are shown for comparison, and the vehicle trajectories with time are discussed.     

Two-Dimensional Motion of Four-Wheel Vehicles

This paper deals with two-dimensional motion of vehicles. Since the general four-wheel vehicle model is statically indeterminate, the motion of vehicles has been analyzed by replacing the vehicle with the equivalent two-wheel one proposed by E. Marquard. Because this approximation is based on the axisymmetry of vehicles, it causes significant errors in the general case. To improve the accuracy of the analysis of vehicle motion, a four-wheel model is suggested. In this model, it is assumed that the chassis remains in a flat plane during motion. By introducing this condition, the motion of the vehicle can be analyzed. Several results from the four-wheel model and the equivalent two-wheel model are shown for comparison, and the vehicle trajectories with time are discussed.     

Road boundary detection and tracking for structured and unstructured roads using a 2D lidar sensor

Road boundaries can give useful information for evaluating safe vehicle paths in intelligent vehicles. Much previous research has studied road boundary detection, using different types of sensors such as vision, radar, and lidar. Lidar sensors, in particular, show advantages for road boundary extraction including high resolution and wide field of view. However, none of the previous studies examined the problem of detecting road boundaries when roads could be either structured or unstructured. In this study, we developed a road boundary detection and tracking algorithm using lidar sensing for both structured and unstructured roads. The algorithm extracts road features as line segments in polar coordinates relative to the lidar sensor. The extracted road features are then tracked with respect to a vehicle’s local coordinates using a nearest neighbor filter. The proposed algorithm accurately detected the road boundaries regardless of the road type.     

Frequency-domain method for evaluating the ride comfort of a motorcycle

In many European towns, the demand for fast and efficient mobility is frequently satisfied by means of two-wheeled vehicles. The improvement of comfort of two-wheeled vehicles used by tired and busy workers can increase safety in ground transport. Nowadays, multibody codes make it possible to predict the ride comfort of two-wheeled vehicles by means of time-domain or frequency-domain simulations. Comfort indices can be developed by post-processing the results of numerical simulations. This task is difficult, because the indices should depend on vehicle characteristics and should be independent of road quality and vehicle speed. Poor quality roads may generate nonlinear effects. Speed influences the trim of the vehicle and the wheelbase filtering, which takes place because the same road unevenness excites the front and rear wheel with a time delay which depends on the vehicle’s speed.

In this paper, the comfort of two-wheeled vehicles is studied by means of a frequency-domain approach. The wheelbase filtering is averaged considering typical missions of the vehicle. The missions are journeys with a forward speed that assumes different values according to a probability density function. Indices of comfort are calculated taking into account the human sensitivity. The examples show that the proposed comfort indices depend on suspensions’ characteristics and, hence, are useful design tools. Finally, some time-domain calculations are carried out to give emphasis to nonlinear effects and to show the limits of the frequency-domain analysis.     

Dynamics of Tracked Vehicles

This paper provides a brief review of the state-of-the-art of tracked vehicle dynamics, including mobility over soft terrain, ride dynamics over rough surfaces and manoeuvrability. It is found that considerable progress has been made in the development of analytical frameworks for evaluating and predicting tracked vehicle mobility over soft terrain, taking into account the characteristics of terrain response to normal and shear loading. Certain computer simulation models for tracked vehicle mobility have been gaining increasingly wide acceptance by industry and governmental agencies in product development and in procurement. It is also found that most of the research on tracked vehicle ride dynamics and manoeuvrability is confined to operations on rigid surfaces. To achieve a realistic evaluation and prediction of the dynamic behaviour of tracked vehicles in the field, the key is to have a better understanding of terrain response to dynamic vehicular loading, including its dynamic stiffness and damping. Challenges that face vehicle dynamicists in this emerging field are identified.     

Robust detection of preceding vehicles in crowded traffic conditions

This paper introduces an adaptive scheme for robustly detecting multiple preceding vehicles in crowded traffic conditions. The scheme focuses on issues frequently observed in the interpretation of traffic scenes recorded by cameras installed in vehicles: stable extraction of features and accurate classification in spite of the vehicle??s constant vibrations and dynamic changes in the distance between vehicles. To address these issues, we introduce the concept of integral features and a method of utilizing the scene geometry information. Each of the simple attributes, such as edges, shadows, and symmetry, is compiled in the window confined by the scene geometry to improve the expressiveness and robustness of the extracted features. The scene geometry information that is then estimated from the perspective view is extensively utilized in constituent system components, including not only feature extraction/integration but also neural network-based classification and distance-adaptive clustering. In addition, employing the Kalman filter along with a confidence measure makes the detection and tracking of potential vehicles robust. Experimental results prove that the system employing the proposed scheme detects and tracks multiple vehicles more effectively, even in crowded traffic conditions, with a lower rate of false positives.     

基于子波能量和神经网络分类器的机动车车型识别

为了使交通管理系统能进行可靠的机动车分类,研究了轿车、轻型越野车和货车3种机动车目标的声信号,提出了一种采用子波分解后不同尺度上声信号能量作为特征向量的特征提取算法,并设计了kNN(k近邻)分类器和改进BP神经网络分类器用于目标分类。目标识别和分类试验结果表明:所提出的特征提取算法能够很好地体现不同类型目标之间的差异,提取的特征向量稳健;设计的改进BP神经网络分类器的分类精度可达92.6%,且分类效果优于kNN分类器。