考虑次干道出入车辆和行人过街影响的单向绿波相位差优化方法

针对干线绿波控制效果受次干道出入车辆和行人过街影响的实际问题,首先在分析上游次干道左转车辆对下游交叉口排队影响的基础上,将两相位排队消散模型改进为4相位排队消散模型,并依据该模型对传统相位差进行优化;然后分析行人过街对干线车流的影响,采用加权平均法计算车辆因行人过街干扰而产生的时间延误,并据此进一步对相位差进行优化.最后利用Vissim进行仿真验证,结果表明:改进的绿波控制优化方法和传统绿波控制方法相比,车均延误减少了20.5%,车均停车时间减少了17.6%,车均停车次数减少了8.7%,平均行程时间减少了3.5 s,对于干线绿波协调具有更好的控制效果.     

Policy challenges of increasing automation in driving

The convergence of information and communication technologies (ICT) with automotive technologies has already resulted in automation features in road vehicles and this trend is expected to continue in the future owing to consumer demand, dropping costs of components, and improved reliability. While the automation features that have taken place so far are mainly in the form of information and driver warning technologies (classified as level I pre-2010), future developments in the medium term (level II 2010–2025) are expected to exhibit connected cognitive vehicle features and encompass increasing degree of automation in the form of advanced driver assistance systems. Although autonomous vehicles have been developed for research purposes and are being tested in controlled driving missions, the autonomous driving case is only a long term (level III 2025 +) scenario. This paper contributes knowledge on technological forecasts regarding automation, policy challenges for each level of technology development and application context, and the essential instrument of cost-effectiveness for policy analysis which enables policy decisions on the automation systems to be assessed in a consistent and balanced manner. The cost of a system per vehicle is viewed against its effectiveness in meeting policy objectives of improving safety, efficiency, mobility, convenience and reducing environmental effects. Example applications are provided that illustrate the contribution of the methodology in providing information for supporting policy decisions. Given the uncertainties in system costs as well as effectiveness, the tool for assessing policies for future generation features probabilistic and utility-theoretic analysis capability. The policy issues defined and the assessment framework enable the resolution of policy challenges while allowing worthy innovative automation in driving to enhance future road transportation.     

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.     

不同路面下汽车ABS仿真检测研究

进行不同路面下汽车ABS性能仿真检测,开发了汽车ABS性能仿真检测系统,对ABS的ECU进行了几种典型路面下的仿真检测,并对试验结果进行分析.结果表明开发的ABS性能检测系统具有良好的路面仿真功能与测试功能,可以用于ABS ECU生产的在线检测.     

Lane-following method for high speed autonomous vehicles

This paper presents a steering control method for lane-following in a vehicle using an image sensor. With each image frame acquired from the sensor, the steering control method determines target position and direction, and constructs a travel path from the current position to the target position either as an Arc-path or S-path. The steering angle is calculated from the travel path thus generated, and the vehicle follows the travel path via motor-control. The method was tested using a vehicle dubbed as KAV (Korea Autonomous Vehicle) along an expressway (Seoul Inner Beltway) trajectory with a variety of radii (50 m ∼ 300 m) while traveling at a speed of 60 km/h to 80 km/h. Compared with an experienced human driver, the method showed little much difference in performance in terms of lane-center deviation. The proposed method is currently employed for high speed autonomous driving as well as for stop and go traffic.     

上海轨道交通1、2号线列车编组“6改8”项目的技术对策及实施效果分析

介绍了上海轨道交通1、2号线运能与日益增长的客流之间的矛盾,提出了通过对既有列车进行“6改8”扩编改造的解决方案.以AC01、AC02和DC01型列车增扩编改造为例,对其技术难度和改造内容进行了分析和说明.已实施的该项扩编改造工作不仅克服了车辆改造所遇到的若干技术难题,而且还有效解决了在列车扩编改造期间所造成的运能不足的问题.     

用于目标检测和精确定位的水下机器人视觉系统

基于目标检测和精确定位的ＡＵＶ（Ａｕｔｏｎｏｍｏｕｓ Ｕｎｄｅｒｗａｔｅｒ Ｖｅｈｉｃｌｅ）视觉系统是水下智能机器人感知水下环境信息、进行自主作业的关键技术。本文着重介绍了视觉系统的工作原理、模块结构、特征提取和目标检测与定位算法。最后给出了仿真试验结果,以说明系统工作的有效性和实用性。