应用Cruise(v3.0)的纯电动汽车仿真方法

本文阐述了利用奥地利AVL公司开发的Cruise(V3.0)软件进行纯电动汽车整车建模、制定仿真计算任务、运行计算并分析计算结果等的具体方法。着重介绍了Cruise、Matlab\Simulink联合仿真技术,从而将整车控制策略、电源管理策略、电机控制策略和制动回收策略应用到仿真技术中的过程和方法。     

Dynamic response of the non-contact underwater explosions on naval equipment

Shock resistance capacity of the shipboard equipment especially for large ones, has been a strong concern of navies all over the world for a long time. The shipboard equipment have previously generally been studied separate from hull structure before. In this paper the coupling elastic effect between equipment and hull structure is taken into account. With the ABAQUS software, the integrated model of the equipment coupled with the hull structure is established to study the dynamic response of the shipboard equipment to the shock wave load as well as the bubble pulsation load. In order to verify the numerical method, the simulated results are compared to the experimental data, which are from a specific underwater explosion on an actual ship. On this basis, by changing the charge location, attack angle, equipment installation location and other parameters, the characteristics of dynamic response under different conditions can be obtained. In addition, the results of the integrated calculation and the non-integrated one are compared and the characteristic parameters which affect the equipment shock response are analyzed. Some curves and conclusions are obtained for engineering applications, which provides some insights into the shock resistance of shipboard equipment.     

嵌入式计算机系统在水下航行器的应用

针对小型水下航行器航行和工作特点,论述了采用嵌入式ＭＣＵ与ＥＤＳＰ器件和Ｉ＾２Ｃ总线技术构成的监测与控制系统。     

Camera calibration and vehicle tracking: Highway traffic video analytics

We describe a real-time highway surveillance system (RHSS), which operates autonomously to collect statistics (speed and volume) and generates incident alerts (e.g., stopped vehicles). The system is designed to optimize long-term real-time performance accuracy. It also provides convenient integration to an existing surveillance infrastructure with different levels of service. Innovations include a novel 3-D Hungarian algorithm which is utilized for object tracking and a practical, hands-off mechanism for camera calibration. Speed is estimated based on trajectories after mapping/alignment with respect to dominant paths learned based on an evolutionary dynamics model. The system, RHSS, is intensively evaluated under different scenarios such as rain, low-contrast and high-contrast lightings. Performance is presented in comparison to a current commercial product. The contribution is innovation of new technologies that enable hands-off calibration (i.e., automatic detection of vanishing points) and improved accuracy (i.e., illumination balancing, tracking via a new 3-D Hungarian algorithm, and re-initialization of background detection on-the-fly). Results indicate the capability and applicability of the proposed system in real-time and real-world settings.     

Roads in transition: Integrated modeling of a manufacturer-traveler-infrastructure system in a mixed autonomous/human driving environment

This paper develops an integrated model to characterize the market penetration of autonomous vehicles (AVs) in urban transportation networks. The model explicitly accounts for the interplay among the AV manufacturer, travelers with heterogeneous values of travel time (VOTT), and road infrastructure capacity. By making in-vehicle time use more leisurely or productive, AVs reduce travelers’ VOTT. In addition, AVs can move closer together than human-driven vehicles because of shorter safe reaction time, which leads to increased road capacity. On the other hand, the use of AV technologies means added manufacturing cost and higher price. Thus, traveler adoption of AVs will trade VOTT savings with additional out-of-pocket cost. The model is structured as a leader (AV manufacturer)-follower (traveler) game. Given the cost of producing AVs, the AV manufacturer sets AV price to maximize profit while anticipating AV market penetration. Given an AV price, the vehicle and routing choice of heterogeneous travelers are modeled by combining a multinomial logit model with multi-modal multi-class user equilibrium (UE). The overall problem is formulated as a mathematical program with complementarity constraints (MPCC), which is challenging to solve. We propose a solution approach based on piecewise linearization of the MPCC as a mixed-integer linear program (MILP) and solving the MILP to global optimality. Non-uniform distribution of breakpoints that delimit piecewise intervals and feasibility-based domain reduction are further employed to reduce the approximation error brought by linearization. The model is implemented in a simplified Singapore network with extensive sensitivity analyses and the Sioux Falls network. Computational results demonstrate the effectiveness and efficiency of the solution approach and yield valuable insights about transportation system performance in a mixed autonomous/human driving environment.     

Influence of connected and autonomous vehicles on traffic flow stability and throughput

The introduction of connected and autonomous vehicles will bring changes to the highway driving environment. Connected vehicle technology provides real-time information about the surrounding traffic condition and the traffic management center’s decisions. Such information is expected to improve drivers’ efficiency, response, and comfort while enhancing safety and mobility. Connected vehicle technology can also further increase efficiency and reliability of autonomous vehicles, though these vehicles could be operated solely with their on-board sensors, without communication. While several studies have examined the possible effects of connected and autonomous vehicles on the driving environment, most of the modeling approaches in the literature do not distinguish between connectivity and automation, leaving many questions unanswered regarding the implications of different contemplated deployment scenarios. There is need for a comprehensive acceleration framework that distinguishes between these two technologies while modeling the new connected environment. This study presents a framework that utilizes different models with technology-appropriate assumptions to simulate different vehicle types with distinct communication capabilities. The stability analysis of the resulting traffic stream behavior using this framework is presented for different market penetration rates of connected and autonomous vehicles. The analysis reveals that connected and autonomous vehicles can improve string stability. Moreover, automation is found to be more effective in preventing shockwave formation and propagation under the model’s assumptions. In addition to stability, the effects of these technologies on throughput are explored, suggesting substantial potential throughput increases under certain penetration scenarios.     

Geometric design safety estimation based on tire–road side friction

A closed-loop drive–vehicle–road–environment system (DVRES) model was established using Adams/Car and Matlab/Simulink. Dynamic responses of lateral tire forces based on tire–road side friction and road geometric characteristics are used to investigate vehicle side slip for geometric design safety estimation. The root mean square, the maximum values of lateral tire forces, comfort limit on curves and vehicle trajectories are used to quantify the safety margin of side friction. The simulation results show that the safety margins of lateral tire forces for radius, operating speed and superelevation rate were 18.2%, 19.3% and 17.6%, respectively, to guarantee good vehicle lateral reliability and ride comfort, while lower speeds are optimal in wet and slippery roads. Finally, a case study was conducted to illustrate the analysis of road design safety, and on-site experiment testing further validated the accuracy and reliability of the closed-loop DVRES model.     

Scheduling of Intelligent and Autonomous Vehicles under pairing/unpairing collaboration strategy in container terminals

A new class of Intelligent and Autonomous Vehicles (IAVs) has been designed in the framework of Intelligent Transportation for Dynamic Environment (InTraDE) project funded by European Union. This type of vehicles is technologically superior to the existing Automated Guided Vehicles (AGVs), in many respects. They offer more flexibility and intelligence in maneuvering within confined spaces where the logistic operations take place. This includes the ability of pairing/unpairing enabling a pair of 1-TEU (20-foot Equivalent Unit) IAVs dynamically to join, transport containers of any size between 1-TEU and 1-FFE (40-foot Equivalent) and disjoin again. Deploying IAVs helps port operators to remain efficient in coping with the ever increasing volume of container traffic at ports and eliminate the need for deploying more 40-ft transporters in the very confined area of ports. In order to accommodate this new feature of IAVs, we review and extend one of the existing mixed integer programming models of AGV scheduling in order to minimize the makespan of operations for transporting a set of containers of different sizes between quay cranes and yard cranes. In particular, we study the case of Dublin Ferryport Terminal. In order to deal with the complexity of the scheduling model, we develop a Lagrangian relaxation-based decomposition approach equipped with a variable fixing procedure and a primal heuristics to obtain high-quality solution of instances of the problem.     

自律分布数字化列车控制系统及在线扩展技术

现行ATC系统控制模式存在自动闭塞区间长度以性能最差的列车确定,多级制动时加减速度急剧变化,降低乘坐舒适度等缺点,需要构建车载设备智能化程度高的自律数字化列车控制系统(D ATC),以提高我国CTCS等级。有综合车载系统与独立车载系统两种方法实现系统在线构建。用测试方法进行确信性评估,证明综合车载系统便于进行高效率的在线测试和安全运行。     

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters’ responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers’ behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief–desire–intention agent architecture.