基于模糊神经网络的驾驶员弯道安全感受预测模型研究

论述了在人-车-路(环境)系统中驾驶员弯道安全感受的非线性特性。为了体现车辆、道路结构对驾驶员认知过程的作用和认知结果形成的影响,驾驶员弯道安全感受模型采用弯道平曲半径、车辆运行速度和驾驶员驾龄作为道路线形、车辆结构动力性、驾驶员经验的主要特征参数集,在增加积极和消极补偿运算的基础上,构建出模糊逻辑推理规则与神经网络优化逼近运算相互结合的5层推理预测模型,并结合实例数据,进行了对比分析验证,表明5层结构模型能够较好的满足特定弯道条件下驾驶员主观安全感受的认知推理预测要求,能够准确的、稳定的再现出驾驶员主观安全感受同驾龄、平曲半径和车辆运行速度间的相互作用关系。     

威海市公路网发展规模预测及适应性评价

通过对威海市现有公路网总体布局、公路等级结构分析，在充分考虑威海市制造业基地的发展基础上，对社会经济发展水平进行预测，同时分析了公路网规模与国民经济、人口的相互关系，采用国土系数法、人口密度法定量预测未来规划年的威海市公路网合理规模，结合专家意见等定性：方法，给出了满足威海市发展需求的路网规模，并从公路网技术指标，宏观经济和社会效益等方面：鞋行适应性分析评判。     

基于期望间距的车辆跟驰模型的建立

以“期望间距”为基准参理，考虑驾驶员的心理和生理因素，建立了车辆跟驰模型，为研究驾驶行为提供了一种新的思路。     

汽车驾驶员不安全行为评价分析

为稳步增强汽车驾驶的安全性,减少安全事故的发生,驾驶人员除了需要具备足够的应急应变能力之外,还需要做好安全行为习惯养成工作,形成良好的驾驶习惯。文章以汽车驾驶员不安全行为作出研究对象,在明确不安全行为表现的基础上,深刻分析影响汽车驾驶人员不安全行为的因素,在此基础上,制定合理的应对策略,旨在引导驾驶人员形成安全行为,以不断提升驾驶员的驾驶能力。     

卫星定位数据驱动的营运车辆驾驶人驾驶风险评估模型

为了提高营运车辆驾驶人安全管理的精细化水平，合理地评估驾驶人驾驶风险程度，有的放矢地降低高风险驾驶人的事故率，基于卫星定位数据特点及驾驶行为与驾驶风险的相关关系设计26个驾驶行为特征参数。考虑到高速和非高速行驶时相同驾驶行为对驾驶风险的影响区别较大，根据23名营运车辆驾驶人的实测数据有针对性地筛选高速和非高速路段驾驶人风险评估指标，构建营运车辆驾驶人驾驶风险评估指标体系。然后，基于熵权法、独立性权系数法和Spearman相关系数法建立集成赋权法，确定各评估指标的权重。最后，雇佣40名营运车辆驾驶人进行实车试验以验证模型的合理性。结果表明：车辆速度和加速度方面的驾驶行为特征可以用于评估驾驶人的驾驶风险且评估效果较好，驾驶风险评估得分与实际交通冲突次数呈正相关关系，所建立模型可以较为准确地评估营运车辆驾驶人驾驶风险的高低，准确率达到77.50%，该模型在不同地区使用时，准确率存在一定的差异，但在容许范围之内，方法具有较好的鲁棒性。     

Application of time-variant predictive control to modelling driver steering skill

The paper addresses the need for improved mathematical models of human steering control. A multiple-model structure for a driver's internal model of a nonlinear vehicle is proposed. The multiple-model structure potentially offers a straightforward way to represent a range of driver expertise. The internal model is combined with a model predictive steering controller. The controller generates a steering command through the minimisation of a cost function involving vehicle path error. A study of the controller performance during an aggressive, nonlinear steering manoeuvre is provided. Analysis of the controller performance reveals a reduction in the closed-loop controller bandwidth with increasing tyre saturation and fixed controller gains. A parameter study demonstrates that increasing the multiple-model density, increasing the weights on the path error, and increasing the controller knowledge range all improved the path following accuracy of the controller.     

A nonlinear virtual rider for motorcycles

This work presents a virtual rider for the guidance of a nonlinear motorcycle model. The target motion is defined in terms of roll angle and speed. The virtual rider inputs are the steering torque, the rear-wheel driving/braking torque and front-wheel braking torque. The virtual rider capability is assessed by guiding the nonlinear motorcycle model in demanding manoeuvres with roll angles of 50° and longitudinal accelerations up to 0.8 g. Considerations on the effective preview distance used by the virtual rider are included.     

Development of advanced driver assistance systems with vehicle hardware-in-the-loop simulations

This paper presents a new method for the design and validation of advanced driver assistance systems (ADASs). With vehicle hardware-in-the-loop (VEHIL) simulations, the development process, and more specifically the validation phase, of intelligent vehicles is carried out safer, cheaper, and is more manageable. In the VEHIL laboratory, a full-scale ADAS-equipped vehicle is set up in a hardware-in-the-loop simulation environment, where a chassis dynamometer is used to emulate the road interaction and robot vehicles to represent other traffic. In this controlled environment, the performance and dependability of an ADAS is tested to great accuracy and reliability. The working principle and the added value of VEHIL are demonstrated with test results of an adaptive cruise control and a forward collision warning system. On the basis of the ‘V’ diagram, the position of VEHIL in the development process of ADASs is illustrated.     

数字式司机控制器

针对目前现有的司机控制器存在的问题,文章阐述了数字式司机控制器的结构原理、性能特点及其应用情况.