Understanding and Modeling the Human Driver

Summary This paper examines the role of the human driver as the primary control element within the traditional driver-vehicle system. Lateral and longitudinal control tasks such as path-following, obstacle avoidance, and headway control are examples of steering and braking activities performed by the human driver. Physical limitations as well as various attributes that make the human driver unique and help to characterize human control behavior are described. Example driver models containing such traits and that are commonly used to predict the performance of the combined driver-vehicle system in lateral and longitudinal control tasks are identified.     

考虑驾驶人特性的一主多从混合博弈容错控制

为保证线控底盘电动汽车在遭遇执行器失效时的稳定性，并考虑人-车交互行为，提出了以驾驶人为领导者的一主多从（Single-leader-multiple-follower，SLMF）混合博弈容错控制框架。为实现驾驶人-车辆的交互控制，首先建立了两者的耦合模型。其次，将驾驶人及5个底盘子系统即主动前轮转向（Active Front Steering，AFS）系统和4个轮毂电机建模为博弈中的6个参与者，基于Stackelberg主从博弈与多人合作博弈设计了SLMF混合博弈控制框架。考虑驾驶人具有优先控制权限及执行器对驾驶人行为的补偿作用，基于Stackelberg博弈理论建立了驾驶人与底盘子系统的主从博弈模型，其中驾驶人作为领导者通过感知跟随者的行为做出转向决策，而5个底盘子系统被建模为跟随者。由于跟随者追求共同的横向稳定控制目标，因此基于合作博弈理论建立了合作模型，并对领导者的转向策略做出最优响应。最后，为研究跟随者之间追求不同目标导致不合作时的控制效果，设计了非合作Nash博弈与Stackelberg博弈相结合的混合博弈为对比方法，通过实时硬件在环测试验证并对比了2种方法。结果表明：针对不同风格的驾驶人，所设计的方法可以保证遭遇执行器卡死失效车辆的稳定性。与不合作的情况相比，2种不同风格的驾驶人驾驶的车辆在底盘子系统合作时，车辆稳定性分别提升了54.62%和53.78%，驾驶人工作负荷分别降低了31.79%和36.07%。     

Development of a Strategy Model of the Driver in Lane Keeping

Based on vehicle constraints and known human operator characteristics, a strategy model was postulated for describing behavior in the lane keeping task. This model includes nonlinear thresholds operating on vehicle yaw and lateral translation, random input sources to account for spurious driver activity, and smoothing to account for driver response lag. The output of the model is steering wheel position

To determine model parameters and model suitability in describing driver behavior, recordings were made for driver-subjects performing a lane-keeping task in a moving base driving simulator having a computer generated display. A procedure involving both analytic and experimental techniques was then developed for determining the model parameters of each driver

Statistical comparisons and visual inspections made between driver-vehicle and model-vehicle time histories indicate a high degree of correspondence. Models such as these show promise in obtaining a better understanding of driver behavior and driver-vehicle response by incorporating nonlinear elements in the driver model.     

Driver-Vehicle-Lateraldynamics under Regular Driving Conditions

In order to minimize accidents and achieve comfortable handling it is necessary to analyse the control behaviour of the driver-vehicle system and adapt the vehicle to the driver. However, most of the tests have shown, that under normal driving conditions the driver adapts himself to the vehicle, which is exactly the other way round as it was originally thought. In this paper it would be shown, how the driver adapts himself to the vehicle and which technical parameters may effect this adaptation.     

Driver-Vehicle-Lateraldynamics under Regular Driving Conditions

SUMMARY

In order to minimize accidents and achieve comfortable handling it is necessary to analyse the control behaviour of the driver-vehicle system and adapt the vehicle to the driver. However, most of the tests have shown, that under normal driving conditions the driver adapts himself to the vehicle, which is exactly the other way round as it was originally thought. In this paper it would be shown, how the driver adapts himself to the vehicle and which technical parameters may effect this adaptation.     

Modeling of Double Lane Change Maneuver of Vehicles

Lane change maneuver is one of most riskiest driving tasks. In order to increase the safety level of the vehicles during this maneuver, design of lane change assist systems which are based on dynamics behavior of driver-vehicle unit is necessary. Therefore, modeling of the maneuver is the first step to design the driver assistance system. In this paper, a novel method for modeling of lateral motion of vehicles in the standard double-lane-change (DLC) maneuver is proposed. A neuro-fuzzy model is suggested consisting of both the vehicle orientation and its lateral position. The inputs of the model are the current orientation, lateral position and steering wheel angle, while the predicted lateral position and orientation of the vehicle are the outputs. The efficiency of the proposed method is verified using both simulation results and experimental tests. The simulation and experimental maneuvers are performed in different velocities. It is shown that the proposed method can effectively reduce the undesirable effects of environmental disturbances and is significantly more accurate in comparisons with the results in the recent available papers. This method can be used to personalize the advanced driver assistance systems.     

驾驶员统计特性对人—车闭环系统响应的影响与汽车主动安全性评价

基于预瞄跟随理论，本文应用一般随机摄动法，对考虑驾驶员不确定性的人－车闭环系统进行响应分析，结合实例，说明该方法在汽车主动安全性评价中的应用。     

认知分心对车辆跟驰过程操控安全性的影响

为了研究车辆跟驰过程中驾驶人认知分心与驾驶安全的关系,采用驾驶模拟器构建城市道路车辆跟驰场景,并设计3种难度等级的认知分心次任务,采集35名被试驾驶人在试验过程中的方向盘转角、油门开度、制动踏板力等操作参数,以及车辆位置、速度、加速度等车辆运动参数。采用重复测量一般线性模型,分析不同等级认知分心对上述参数的影响。研究结果表明：在横向操控方面,随着认知分心程度增高,方向盘回转率增大,但车辆横向位置标准差减小,表明驾驶人处于认知分心时,采取频繁修正方向盘的补偿方式,降低车辆横向位置波动,过度补偿车辆横向安全性,且该补偿行为与认知分心程度正相关;在纵向操控方面,认知分心时,油门开度、制动踏板位置方差增大,且制动踏板位置均值增大,同时车头间距及时距未观察到显著性变化,表明认知分心时驾驶人采取频繁操作油门、制动踏板,增大制动幅度等方式进行补偿,使车头间距及车头时距等表征车辆纵向跟车安全性参数处于正常驾驶水平,但加速度标准差增大,表明跟车稳定性降低。研究结果为涉及分心的人车交互装置优化设计及考虑分心状态的驾驶人状态管理系统开发提供了一定的理论依据。     

Application of a driving simulator to the development of in-vehicle human-machine-interfaces

The use of a driving simulator in the development of human-machine-interfaces (HMI) such as a navigation, information or entertainment system is discussed. Such use addresses the need to study and evaluate the characteristics of a candidate HMI early in the R&D and design stage to ensure that it is likely to meet various objectives and requirements, and to revise the HMI as may be necessary. Those HMI requirements include such things as usability, driver comfort, and an acceptable level of attentional demand in dual task conditions (driving while using an HMI). Typically, such an HMI involves an information display to the driver, and a means for driver input to the HMI. Corresponding simulator requirements are discussed, along with typical simulator features and components. The latter include a cab, control feel systems, visual image generator, real time scenario control (task definitions), a motion system (if provided), and data acquisition. Both fixed and moving base systems are described, together with associated benefits and tradeoffs. Considerations in the design of the evaluation experiment are discussed, including definition of primary and secondary tasks, and number of driver subjects (experimental participants). Possible response and performance measures for the primary and secondary tasks are noted, together with subjective measures such as task difficulty and ease of using the HMI. The advantages of using a driving simulator to support R&D are summarized. Some typical and example simulator uses are noted.     

Application of Elementary Neural Networks and Preview Sensors for Representing Driver Steering Control Behaviour

This paper demonstrates the use of elementary neural networks for modelling and representing driver steering behaviour in path regulation control tasks. Areas of application include uses by vehicle simulation experts who need to model and represent specific instances of driver steering control behaviour, potential on-board vehicle technologies aimed at representing and tracking driver steering control behaviour over time, and use by human factors specialists interested in representing or classifying specific families of driver steering behaviour. Example applications are shown for data obtained from a driver/vehicle numerical simulation, a basic driving simulator, and an experimental on-road test vehicle equipped with a camera and sensor processing system.     

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters.

The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced.

For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.     

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters.

The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced.

For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.     

Electro-hydraulic braking system for autonomous vehicles

Reducing the number of traffic accidents is a declared target of most governments. Since dependence on driver reaction is the main cause of road accidents, it would be advisable to replace the human factor in some driving-related tasks with automated solutions. To automate a vehicle, it is necessary to control the actuators of a car, i.e., the steering wheel, accelerator, and brake. This paper presents the design and implementation of an electro-hydraulic braking system consisting of a pump and various valves, allowing the control computer to stop the car. It is assembled in conjunction with the original circuit for the sake of robustness and to permit the two systems to halt the car independently. This system was developed for installation in a commercial Citroën C3 Pluriel of the AUTOPIA program. Various tests were carried out to verify its correct operation, and an experiment showing the integration of the system into the longitudinal control of the car is described.     

Dynamic Identification of Driver-Vehicle System Using AR-method

When investigating dynamics of a driver-vehicle system, isolation between driver dynamics and vehicle dynamics becomes important, because interaction between them exists in the closed-loop system. The subject of this study is to examine effectiveness of AR-method by which each dynamics can be identified. The AR-method applied to lane changes, usually having rather short duration data, provides usefullness for the isolation. This method well reflects variation of subject drivers in identified results, and time series data recoverd by identified VAR-model is consistent with field data.     

驾驶员最优预瞄纵向加速度模型

利用预瞄跟踪理论、模糊决策理论和非线性系统描述函数法建立了一个驾驶员速度控制模型，即加强员最优预瞄纵向加速度模型，仿真结果表明，该模型通过对驾驶安全性、合法性、轻便性、驾驶员自身滞后特性及汽车动力学系统强非线性特性的考虑，可以有效地模拟驾驶员控制汽车速度的行为特性，为人-车-路闭环系统中速度控制研究提供了一条可行途径。     

Closed-loop analysis of vehicle behavior during braking in a turn

This paper discusses an analysis of “driver-vehicle” behavior during braking in a turn. In this study, a new braking model was developed in consideration of actual driver's operation, and experiments were conducted on mountain roads to identify one novice and one skilled driver's braking model parameters.The computer simulations have shown the following tendency. The novice driver needed more compensatory steering operation than the skilled driver to trace the course. A controlled braking force distribution was particularly effective for the novice driver.     

A curving ACC system with coordination control of longitudinal car-following and lateral stability

The paper presents a curving adaptive cruise control (ACC) system that is coordinated with a direct yaw-moment control (DYC) system and gives consideration to both longitudinal car-following capability and lateral stability on curved roads. A model including vehicle longitudinal and lateral dynamics is built first, which is as discrete as the predictive model of the system controller. Then, a cost function is determined to reflect the contradictions between vehicle longitudinal and lateral dynamics. Meanwhile, some I/O constraints are formulated with a driver permissible longitudinal car-following range and the road adhesion condition. After that, desired longitudinal acceleration and desired yaw moment are obtained by a linear matrix inequality based robust constrained state feedback method. Finally, driver-in-the-loop tests on a driving simulator are conducted and the results show that the developed control system provides significant benefits in weakening the impact of DYC on ACC longitudinal car-following capability while also improving lateral stability.     

Dynamic Identification of Driver-Vehicle System Using AR-method

SUMMARY

When investigating dynamics of a driver-vehicle system, isolation between driver dynamics and vehicle dynamics becomes important, because interaction between them exists in the closed-loop system. The subject of this study is to examine effectiveness of AR-method by which each dynamics can be identified. The AR-method applied to lane changes, usually having rather short duration data, provides usefullness for the isolation. This method well reflects variation of subject drivers in identified results, and time series data recoverd by identified VAR-model is consistent with field data.     

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.     

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.