Simulation of Man-Automobile Systems by the Driver's Steering Model with Predictability

Yoshimoto, Kenichi

doi:10.1299/jsme1958.12.495

Cited by 29 publications

(10 citation statements)

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“…Driving cannot simply be considered as a continuous closed-loop steering task to maintain the vehicle within a driving lane [53]. In the vehicle dynamics domain, preview-predictor models [54] as continuous closed-loop tasks based on visual feedback are often used to mimic the driver's action. Although drivers implement steering actions such as error-correcting mechanisms, they may pay attention to other aspects of the driving task, and drivers who are aware of their drowsiness may not be able to sufficiently maintain the continuous closed-loop task.…”

Section: E Sleepy Driver Behavior and Hypothesismentioning

confidence: 99%

Driver Assistance System With a Dual Control Scheme: Effectiveness of Identifying Driver Drowsiness and Preventing Lane Departure Accidents

Saito

Itoh

Inagaki

2016

IEEE Trans. Human-Mach. Syst.

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Driver drowsiness is a common cause of fatal traffic accidents. In this study, a driver assistance system with a dual control scheme is developed; it attempts to perform simultaneously the safety control of the vehicle and identification of the driver's state. The assistance system implements partial control in the event of lane departure and gives the driver the chance to voluntarily take the action needed. If the driver fails to implement the steering action needed within a limited time, the assistance system judges that "the driver's understanding of the given situation is incorrect", and executes the remaining control. We used a driving simulator equipped with the assistance system to investigate the effectiveness of identifying driver drowsiness and preventing lane departure accidents. Twenty students participated in three trials on a straight expressway, and they were required to implement only lateral control. We hypothesized that a participant cannot implement the action needed to maintain safety when he/she falls asleep, and that in such a case, the assistance system will implement the safety control repeatedly. The assistance system assisted the participants only when almost really needed, such as when their eyelids were closed. The results validated the hypothesis, showing that the assistance system implemented the safety control repeatedly when a participant fell asleep. In addition, the algorithms used by the assistance system to determine whether the driver can continue driving were evaluated through a leave-one-out cross-validation, and they were proven to be effective for identifying driver drowsiness.

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Section: E Sleepy Driver Behavior and Hypothesismentioning

confidence: 99%

Driver Assistance System With a Dual Control Scheme: Effectiveness of Identifying Driver Drowsiness and Preventing Lane Departure Accidents

Saito

Itoh

Inagaki

2016

IEEE Trans. Human-Mach. Syst.

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“…The principal roots of driver modeling as it relates to these control activities extend back to the early years of human-machine and aircraft pilot studies [1][2][3][4][5][6][7][8][9][10][11][12][13][14]. Those studies helped to reveal various properties unique to, or characteristic of, the human as a controller of dynamical plants [1,4,8,14,15] and certain vehicles [6,[16][17][18][19][20]. For example, in 1961 Ornstein [8] proposed the following transfer function, H(s), model of the human operator for pursuit-type manual tracking tasks,…”

Section: Introductionmentioning

confidence: 99%

“…The parameter t was an effective transport time delay. More specific studies aimed at understanding the human as an automobile driver [16,[19][20][21][22][23][24][25][26][27][28][29][30][31] followed from or paralleled this type of manual control work. One example is a series of publications by Rashevsky in the late 1950s and early 1960s that addressed the topic of ''Mathematical Biology of Automobile Driving'' [25] wherein the basic model of the driver as a steering controller was treated in a purely geometric/ kinematic manner.…”

Section: Introductionmentioning

confidence: 99%

“…More complete treatments of the driver modeling effort and associated measurements of driver-vehicle system responses were also emerging in this same time frame, particularly with the increased use of computers and driving simulators. Example works that studied driver control behavior and accounted for the dynamics of the vehicle include studies by Wierwille [19], McRuer [22], Weir [18,[29][30][31], Kondo [17], Yoshimoto [20] as well as many others [16,[26][27][28][34][35][36][37]. Key findings from these studies and others that followed are discussed further in subsequent sections of the paper.…”

Section: Introductionmentioning

confidence: 99%

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Understanding and Modeling the Human Driver

MacAdam¹

2003

Vehicle System Dynamics

402

215

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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.

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“…In the sight point model, the driver looks down the road some prescribed distance and steers as a function of the difference between the point he is headed toward and the desired path. A similar model was proposed by Yoshimoto [36] in which the driver predicts the future position of the vehicle system using the systems present position, yaw angle and yaw velocity. Again, the driver steers as a function of the difference between the predicted position and the desired position.…”

Section: A Vehicle Literaturementioning

confidence: 99%

Lateral stability of the driver/vehicle system: analytical results

Johnson

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LIST OF SYMBOLS Coefficients of the quartic Coefficients of the equations of motion Cornering stiffness of front and rear tires, respectively Constant gains of driver associated with lateral displacement and yaw angle, respectively Expressions in quartic solution Forces on front tire in the longitudinal and normal directions, respectively Forces on rear tire in the longitudinal and normal directions, respectively Acceleration of gravity Moment of inertia of the automobile about a vertical axis through the mass center Uhdersteer coefficient Expressions in the equation for the critical velocity of the driver/vehicle system Lengths from the mass center to the front and rear axles, respectively Mass of the vehicle Matrices in the Lyapunov matrix equation Expression in quartic solution Time Unit vectors in the x and y directions, respectively VcRiT Critical speed from classical result VcRiT Critical speed of the driver/vehicle system D/V-tl*-t2 Velocity of the front and rear tires, respectively V^, Vy Speeds in the x and y directions, respectively V Trial Lyapunov function X, y Coordinate directions fixed in the vehicle X, Y Absolute coordinate directions Slip angles of front and rear tires, respectively 6 Steer angle of front wheels

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Simulation of Man-Automobile Systems by the Driver's Steering Model with Predictability

Cited by 29 publications

References 0 publications

Driver Assistance System With a Dual Control Scheme: Effectiveness of Identifying Driver Drowsiness and Preventing Lane Departure Accidents

Driver Assistance System With a Dual Control Scheme: Effectiveness of Identifying Driver Drowsiness and Preventing Lane Departure Accidents

Understanding and Modeling the Human Driver

Lateral stability of the driver/vehicle system: analytical results

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