Comprehensive lateral driver model for critical maneuvering conditions

A new comprehensive driver model is presented for critical maneuvering conditions with more accurate dynamic control performance. In order to achieve a safe maneuvering mode, a new path planning scheme to maintain stability of the vehicle was designed. A new steering strategy, considering the errors of vehicle position and yaw angle between the real track and the planned path, was established to obtain the steering angle. Therefore, the vehicle can be adjusted to accurately follow the desired path with the driver model, and the stability of the vehicle and the smoothness of the steering angle input were comprehensively considered. Simulation results were used to validate the control performance in comparison with the optimal preview driver model proposed by Macadam.     

预瞄距离自适应的路径跟踪驾驶员模型

根据驾驶员的前视作用,不同学者建立了不同的预瞄驾驶员模型。但是真实的驾驶员在预瞄前方路径时,往往会根据目标路径的曲率和边界条件对预瞄距离的远近进行动态调节。当目标路径的曲率较大时,此时驾驶员为了提高车辆的稳定性,往往将预瞄视线放得较近。当目标路径的曲率较小时,驾驶员将预瞄距离放得较远。同时,当车速较高时,驾驶员的预瞄视线趋于远距离预瞄。当车速较低时,驾驶员的预瞄视线区域近距离预瞄。因此,真实驾驶员在进行路径跟踪时,应该建立预瞄距离自适应跟踪模型,这样有利逼近真实驾驶员预瞄机理。文章基于以上分析,建立了基于曲率与车速的远近点预瞄跟踪模型。通过预瞄远近点的选择,来适应不同的曲率路径。同时通过调节预瞄距离,来逼近驾驶员的真实预瞄机理,提高路径跟踪的精度和适应性。     

Study on driver model for hybrid truck based on driving simulator experimental results

In this paper, a proposed car-following driver model taking into account some features of both the compensatory and anticipatory model representing the human pedal operation has been verified by driving simulator experiments with several real drivers. The comparison between computer simulations performed by determined model parameters with the experimental results confirm the correctness of this mathematical driver model and identified model parameters. Then the driver model is joined to a hybrid vehicle dynamics model and the moderate car following maneuver simulations with various driver parameters are conducted to investigate influences of driver parameters on vehicle dynamics response and fuel economy. Finally, major driver parameters involved in the longitudinal control of drivers are clarified.     

The risk of whiplash-induced medical impairment in rear-end impacts for males and females in driver seat compared to front passenger seat

The objective of this study was to study whiplash injury outcome in front-seat occupants in rear-end impacts using double paired comparison technique. The combination of gender, seated position, and outcome was analyzed. Folksam, a Swedish insurance company, has a database of whiplash injuries. A questionnaire was used to collect study data. The response rate was 81%. The inclusion criteria included medical impairment one year after the impact, as judged by medical specialists. The study included rear-end impacts between 1990 and 1999 that resulted in at least one permanent neck injury impairment; in total, 430 impacts with 860 occupants and 444 impairments. Of those suffering impairment, 302 were female and 142 male; 235 were seated in the driver's seat and 209 in the front passenger seat. Relative risk estimates for impairing whiplash injury, by gender and seated position:

1.

Driver male (DM)/passenger female (PF) relative risk = 0.5 n = 218     

基于计算机视觉的驾驶员转向操作实时监测研究

为实时监控驾驶员操纵转向盘的状态，构建了基于机器视觉汽车转向盘实时监控系统，并运用阈值分割和边缘检测方法对转向盘图像中感兴趣区域进行了图像分割，提出了转向盘转角的计算公式。试验结果表明，感兴趣区域图像分割与转向盘转角监测方法有效。     

eTS fuzzy driver model for simultaneous longitudinal and lateral vehicle control

In this paper, evolving Takagi-Sugeno (eTS) fuzzy driver model is proposed for simultaneous lateral and longitudinal control of a vehicle in a test track closed to traffic. The developed eTS fuzzy driver model can capture human operator’s driving expertise for generating desired steering angle, throttle angle and brake pedal command values by processing only information which can be supplied by the vehicle’s on-board control systems in real time. Apart from other fuzzy rule based (FRB) models requiring human expert knowledge or off-line clustering, the developed eTS driver model can adapt itself automatically, even ‘from scratch’, by an on-line learning process using eTS algorithm while human driver is supervising the vehicle. Proposed eTS fuzzy driver model’s on-line human driver identification capability and autonomous vehicle driving performance were evaluated on real road profiles created by digitizing two different intercity express ways of Turkey in IPG© CarMaker® software. The training and validation simulation results demonstrated that eTS fuzzy driver model can be used in product development phase to speed up different tests via realistic simulations. Furthermore eTS fuzzy driver model has an application potential in the field of autonomous driving.     

Vehicle dynamic control of a passenger car applying flexible body model

Modern software tools have enhanced modelling, analysis and simulation capabilities pertaining to control of dynamic systems. In this regard, in this paper a full vehicle model with flexible body is exposed by using MSC. ADAMS and MSC. NASTRAN. Indeed, one of the most significant vehicle dynamic controls is directional stability control. In this case, the vehicle dynamic control system (VDC) is used to improving the vehicle lateral and yaw motions in critical manoeuvres. In this paper, for design the VDC system, an optimal control strategy has been used for tracking the intended path with optimal energy. For better performance of VDC system, an anti-lock brake system (ABS) is designed as a lower layer of the control system for maintaining the tyre longitudinal slip in proper value. The performances of the controller on rigid and flexible models are illustrated, and the results show the differences between the control efforts for these models, which are related to the differences of dynamic behaviours of rigid and flexible vehicle dynamic models.     

Handling qualities evaluation method based on actual driver characteristics

The present study proposes an objective handling qualities evaluation method using driver-in-the-loop analysis. The driving simulator experiments were performed for various driving conditions, drivers and vehicle dynamics. The response characteristics of the driver model and the closed-loop system were analyzed. The analysis revealed the driving strategies clearly, indicating the importance of closed-loop analysis. Using the identified driver model and its strategies, a cost function of the handling qualities was constructed. The cost function can be used to estimate the handling qualities analytically from the vehicle dynamics. The proposed method was validated by comparison with the handling qualities evaluation rated by the driver's comments.     

Handling qualities evaluation method based on actual driver characteristics

The present study proposes an objective handling qualities evaluation method using driver-in-the-loop analysis. The driving simulator experiments were performed for various driving conditions, drivers and vehicle dynamics. The response characteristics of the driver model and the closed-loop system were analyzed. The analysis revealed the driving strategies clearly, indicating the importance of closed-loop analysis. Using the identified driver model and its strategies, a cost function of the handling qualities was constructed. The cost function can be used to estimate the handling qualities analytically from the vehicle dynamics. The proposed method was validated by comparison with the handling qualities evaluation rated by the driver's comments.     

一种基于模糊逻辑智能控制的驾驶员模型

模糊逻辑智能控制由于不需要精确的数学模型,能较好的适用于非线性系统,因此被广泛地应用于控制领 域。驾驶员模型主要分析车辆路径跟踪的效果,为了提高车辆路径跟踪精度和适应性,需要建立人-车-路闭环系统。 由于车辆模型具有高度的非线性,无法用精确的数学表达式来建立。同时由于驾驶员具有反应和操作的滞后因素, 因此,难以用精确的数学模型来建立人-车-路闭环系统模型。而驾驶员模型对方向盘的决策主要通过引入控制理论 来处理分析。因此,文章将模糊逻辑智能控制运用于方向盘转角的输入控制。通过模糊逻辑智能控制,建立以侧向误差和车速的二维输入变量,方向盘转角为一维的输出变量控制模型。将车辆的方向盘转角通过模糊化、隶属度函数的选择、模糊规则的制定、解模糊化四个步骤来决策出最优的方向盘转角。避免了对车辆模型的数学表达式的依 赖。通过仿真验证,所建立的驾驶员模型能较好地适应于非线性系统,可有效提高车辆路径跟踪的精度。     

主动悬架最优控制整车模型的研究

以一个车辆的整车模型为研究对象,通过利用轴距预瞄信息,应用最优控制理论设计了一个车辆的悬架控制策略,通过模拟和仿真的结果,验证了该模型和算法的可行性,并分析了轴距预瞄控制对于改进车辆性能的能力,检验了所建立的整车模型。     

基于转向特性的汽车电子控制动力转向系统

电子控制动力转向系统（EPS）可以在低速时减轻转向力,以提高转向系统的操纵稳定性;在高速时则可适当加重转向力,以提高操纵稳定性.文章介绍了EPS及其主要形式和布置方式,在分析汽车助力转向系统工作原理的基础上,阐述了转向特性对汽车操纵性能的影响,并结合具体EPS实例,介绍了电子控制动力转向系统的4种控制形式,为动力转向系统软件开发及实物研制提供了前提条件.     

Development of an errorable car-following driver model

An errorable car-following driver model is presented in this paper. An errorable driver model is one that emulates human driver’s functions and can generate both nominal (error-free), as well as devious (with error) behaviours. This model was developed for evaluation and design of active safety systems. The car-following data used for developing and validating the model were obtained from a large-scale naturalistic driving database. The stochastic car-following behaviour was first analysed and modelled as a random process. Three error-inducing behaviours were then introduced. First, human perceptual limitation was studied and implemented. Distraction due to non-driving tasks was then identified based on the statistical analysis of the driving data. Finally, time delay of human drivers was estimated through a recursive least-square identification process. By including these three error-inducing behaviours, rear-end collisions with the lead vehicle could occur. The simulated crash rate was found to be similar but somewhat higher than that reported in traffic statistics.     

European advanced driver training programs: Reasons for optimism

Post license advanced driver training programs in the US and early programs in Europe have often failed to accomplish their stated objectives because, it is suspected, that drivers gain self perceived driving skills that exceed their true skills—leading to increased post training crashes. The consensus from the evaluation of countless advanced driver training programs is that these programs are a detriment to safety, especially for novice, young, male drivers.Some European countries including Sweden, Finland, Austria, Luxembourg, and Norway, have continued to refine these programs, with an entirely new training philosophy emerging around 1990. These ‘post-renewal’ programs have shown considerable promise, despite various data quality and availability concerns. These programs share in common a focus on teaching drivers about self assessment and anticipation of risk, as opposed to teaching drivers how to master driving at the limits of tire adhesion. The programs focus on factors such as self actualization and driving discipline, rather than low level mastery of skills. Drivers are meant to depart these renewed programs with a more realistic assessment of their driving abilities. These renewed programs require considerable specialized and costly infrastructure including dedicated driver training facilities with driving modules engineered specifically for advanced driver training and highly structured curriculums. They are conspicuously missing from both the US road safety toolbox and academic literature. Given the considerable road safety concerns associated with US novice male drivers in particular, these programs warrant further attention.This paper reviews the predominant features and empirical evidence surrounding post licensing advanced driver training programs focused on novice drivers. A clear articulation of differences between the renewed and current US advanced driver training programs is provided. While the individual quantitative evaluations range from marginally to significantly effective in reducing novice driver crash risk, they have been criticized for evaluation deficiencies ranging from small sample sizes to confounding variables to lack of exposure metrics. Collectively, however, the programs sited in the paper suggest at least a marginally positive effect that needs to be validated with further studies. If additional well controlled studies can validate these programs, a pilot program in the US should be considered.     

Steering disturbance rejection using a physics-based neuromusculoskeletal driver model

The aim of this work is to develop a comprehensive yet practical driver model to be used in studying driver–vehicle interactions. Drivers interact with their vehicle and the road through the steering wheel. This interaction forms a closed-loop coupled human–machine system, which influences the driver's steering feel and control performance. A hierarchical approach is proposed here to capture the complexity of the driver's neuromuscular dynamics and the central nervous system in the coordination of the driver's upper extremity activities, especially in the presence of external disturbance. The proposed motor control framework has three layers: the first (or the path planning) plans a desired vehicle trajectory and the required steering angles to perform the desired trajectory; the second (or the musculoskeletal controller) actuates the musculoskeletal arm to rotate the steering wheel accordingly; and the final layer ensures the precision control and disturbance rejection of the motor control units. The physics-based driver model presented here can also provide insights into vehicle control in relaxed and tensed driving conditions, which are simulated by adjusting the driver model parameters such as cognition delay and muscle co-contraction dynamics.     

汽车主动转向-制动协同控制策略研究

针对汽车主动转向-制动联合工况,以提高汽车稳定性为目标研究了汽车主动前轮转向和防抱死制动系统的协同控制策略,设计了模糊控制转向控制器与比例-积分-微分（PID）制动控制器的协调策略,建立了二自由度转向模型和制动模型。结合 Simulink 和 Adams/Car 中的车辆模型对控制策略进行了测试和仿真分析。结果表明,在主动转向-制动联合工况下,该协同控制策略能够有效降低车辆制动距离,提高汽车行驶稳定性。     

A methodology to increase driver trust in rear-obstacle warning systems with imperfect sensing results — Proposal for a warning system using sensor reliability information

Driver's workload tends to be increased during driving under complicated traffic environments like lane-changing operation. In such cases, rear collision warning is effective for reduction of cognitive workload. On the other hand, it is pointed out that false alarm or missing alarm caused by sensor errors leads to decrease of driver trust in the warning system and it can result in low efficiency of the system. Suppose that sensor reliability information is provided in real-time. In this paper, we propose a novel warning method to increase driver trust in the system even with low sensor reliability by utilizing sensor reliability information. We investigate the effectiveness of the warning methods in high and low workload situations by driving simulator experiments.