商用车底盘线控技术研究现状及应用进展

底盘线控技术是实现商用车自动驾驶和辅助驾驶功能的关键基础技术,是当今汽车行业的研发热点。底盘线控技术包括线控执行系统和线控集成控制技术两大部分。分别对商用车的线控转向、线控制动、线控悬架、线控驱动和线控换挡等线控执行系统,以及自动紧急制动 （Autonomous Emergency Braking,AEB） 系统、自适应巡航 （Adaptive Cruise Control,ACC） 系统和车道保持辅助 （Lane Keeping Assist,LKA） 系统等线控集成控制技术的构成、控制原理与研究应用现状进行了概述,重点分析了商用车各类构型的线控转向和线控制动系统及其应用场景。结合最新发布的国家智能底盘技术路线框架图和商用车未来的客户需求,给出了商用车线控底盘各技术方向的发展趋势,为商用车线控底盘技术发展提供了参考。     

山区公路穿村镇路段过境车辆事故严重程度推理分析

为获取道路线形、驾驶员属性、车辆类型、事故形态等因素对山区公路穿村镇路段过境车辆事故严重程度的影响机制。本文基于元双公路(元谋—牟定)2012—2017年事故数据,利用社会网络分析法从人、车、路、环境等方面筛选出15个影响因素;基于机器学习方法构建贝叶斯网络模型;以事故严重程度为决策变量,分析不同证据变量与驾驶员行为共同作用的推理结果。结果表明：不安全驾驶行为与危险事故因素的共同作用,将会增加事故严重程度;当涉及货车时,由于未保持安全距离,伤人事故率增加8.2%;在弯坡组合路段,由于驾驶员判断失误,伤人事故率增加 19.6%;阴雨天行驶时,由于驾驶员判断失误,伤人事故率增加5.4%;由于操作不当,发生侧翻事故时,伤人事故概率增加3.1%。     

地铁基础减振地段钢轨异常波磨 治理方案研究

针对地铁线路产生的钢轨异常波磨问题,调研了某地铁线路的钢轨波磨情况以及基本特征,对轨道刚度、 钢轨廓形、轨距以及轨道动力特征进行测试,提出钢轨异常波磨的治理思路,并对波磨治理效果进行跟踪测试, 提出既有线以及新建地铁线路钢轨波磨的治理以及预防方案。研究表明：地铁钢轨波磨较为严重,波长在 25～ 100 mm 之间;轨道垂向刚度、横向刚度整体较弱,钢轨位移大,保持轨距能力差,轮轨关系恶化,在特定频段 范围内轮轨振动加剧,从而引起钢轨波磨的产生和发展。通过更换扣件及垫板、轨道精测精调、钢轨打磨措施可 以使车内噪声降低 5～10 dB,轨面不平顺显著降低,打磨周期延长至 1 倍以上;既有线路可通过“细调查、调参 数、精维修、动态检查”治理钢轨波磨,新建地铁线路应在规划、设计、运营维护、动态验收阶段严格把关,合 理采用减振轨道,避免钢轨异常波磨的产生和发展。     

地铁车辆部件隔声性能指标研究

地铁车辆部件作为重要噪声传递路径,其隔声性能对车内噪声有重要影响。文章以我国某型地铁车辆部件为研究对象,通过建立车内噪声预测分析模型,研究了车辆部件的隔声性能指标。结果表明,改变车门、车窗和风挡的隔声量,对车内噪声的抑制效果最显著。     

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车路协同系统能实时获取车辆个体的运行状态信息,并能通过速度引导实现车辆与交通控制系统之间的动态交互,为交通信号控制提供了新的数据源和技术手段.分析了现有车路协同下交通信号控制方法存在的不足,引入基于时间窗的滚动预测方法,提出了改进的交叉口信号控制优化流程;将相位饱和度作为表征信号控制效果的指标,在考虑速度引导对车辆运行状态影响基础上,建立了车路协同环境下道路交叉口信号控制优化方法和模型.运用VISSIM软件进行了仿真实验,结果表明,本文方法优于感应控制方法,在各种交通流量下均能有效降低交叉口平均延误和停车次数.     

Human driving data-based design of a vehicle adaptive cruise control algorithm

This paper presents a vehicle adaptive cruise control algorithm design with human factors considerations. Adaptive cruise control (ACC) systems should be acceptable to drivers. In order to be acceptable to drivers, the ACC systems need to be designed based on the analysis of human driver driving behaviour. Manual driving characteristics are investigated using real-world driving test data. The goal of the control algorithm is to achieve naturalistic behaviour of the controlled vehicle that would feel natural to the human driver in normal driving situations and to achieve safe vehicle behaviour in severe braking situations in which large decelerations are necessary. A non-dimensional warning index and inverse time-to-collision are used to evaluate driving situations. A confusion matrix method based on natural driving data sets was used to tune control parameters in the proposed ACC system. Using a simulation and a validated vehicle simulator, vehicle following characteristics of the controlled vehicle are compared with real-world manual driving radar sensor data. It is shown that the proposed control strategy can provide with natural following performance similar to human manual driving in both high speed driving and low speed stop-and-go situations and can prevent the vehicle-to-vehicle distance from dropping to an unsafe level in a variety of driving conditions.     

On the equivalent wheelbase of a three-axle vehicle

The steady-state handling properties of a rigid vehicle with a tandem rear axle configuration are developed. This work uses conventions resulting in a parsimonious characterisation of steady-state handling of such three-axle vehicles that is shown to be a simple extension of the well-known two-axle bicycle model. Specifically the concepts of understeer and wheelbase are developed for a three-axle vehicle, and shown to play the same role in characterising vehicle handling as they do in the well-known two-axle vehicle model. An equivalent wheelbase of a three-axle vehicle is expressed in terms of vehicle geometry and cornering stiffness of each axle. The model developed in this work is reconciled with previous models that make use of simplifying assumptions found in the literature.     

A fundamental investigation of tilt control systems for narrow commuter vehicles

One way of addressing traffic congestion is by efficiently utilizing the existing highway infrastructure. Narrow tilting vehicles that need a reduced width lane can be part of the solution if they can be designed to be safe, stable, and easy to operate. In this paper, a control system that stabilizes the tilt mode of such a vehicle without affecting the handling of the vehicle is proposed. This control system is a combination of two different types of control schemes known as steering tilt control (STC) and direct tilt control (DTC) systems. First, different existing variations of both STC and DTC systems are considered and their shortcomings analysed. Modified control schemes are then suggested to overcome the deficiencies. Then a new method of integrating these two control schemes that guarantees smooth switchover between the controllers as a function of vehicle velocity is proposed. The performance of the proposed STC, DTC, and integrated systems is evaluated by carrying out simulations for different operating conditions and some experimental work. The design of a second-generation narrow tilting vehicle on which the developed control system has been implemented is presented.     

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.     

Optimisation of lateral car dynamics taking into account parameter uncertainties

Simulation studies on an active all-wheel-steering car show that disturbance of vehicle parameters have high influence on lateral car dynamics. This motivates the need of robust design against such parameter uncertainties. A specific parametrisation is established combining deterministic, velocity-dependent steering control parameters with partly uncertain, velocity-independent vehicle parameters for simultaneous use in a numerical optimisation process. Model-based objectives are formulated and summarised in a multi-objective optimisation problem where especially the lateral steady-state behaviour is improved by an adaption strategy based on measurable uncertainties. The normally distributed uncertainties are generated by optimal Latin hypercube sampling and a response surface based strategy helps to cut down time consuming model evaluations which offers the possibility to use a genetic optimisation algorithm. Optimisation results are discussed in different criterion spaces and the achieved improvements confirm the validity of the proposed procedure.